How to use this dossier: Rabwin is a promoter-led, multi-entity Coimbatore precision group — not a single HT meter. Stamped wins only if we speak foundry melt campaigns, 400-CNC spindle clustering, TANGEDCO HT-I demand + ToD, and invoice proof. Read §1.3 (plant map) and §2.1 (bill band) before picking a champion or scoping a pilot feeder.

1. Company overview & snapshot

1.1 Legal identity & corporate structure

Group entities (operating map)

Promoters: P. R. Aruchamy (MD), P. Ramakrishnan (Director), P. Balakrishnan (Director) — near-full ownership, private. Founders started 1999 with one CNC and ₹2 lakh each (Machine Maker, Jun 2025).

Do not confuse with: typo LinkedIn “Rabwin Industries Private Imited”, unrelated Rabwin traders. Anchor on CIN + rabwin.com + Malumichampatti.

1.2 What they make & where money comes from

Precision engineering group: 400+ CNC (HMC/VMC/5-axis/turn-mill/VBL to 20 t), 750 MT/month iron foundry, 12 HPDC/GDC machines at Jainidhi, plus Intelligent division for semiconductor/mobile fixtures.

Certifications: IATF 16949, AS9100, ISO 9001, ISO 14001, ISO 45001.

Growth signal (Machinist Jan 2026): FY26 ₹460–500 Cr (+63–77% YoY from ₹282 Cr FY25). Apr–Aug 2025 alone ₹229 Cr. Restructuring expanded group structure; iPhone fixture capability added. Energy implication: utilisation and MD likely rising faster than manual monitoring.

1.3 Plants, addresses & footprint

DISCOM (all TN sites): TANGEDCO / TNEB — HT Category HT-I (Industries & Factories). Confirm exact account name, contracted kVA, and whether foundry is separate HT from Malumichampatti cluster.

Contact (verified): +91-422-2611190; +91 93645 74044; info@rabwin.in

1.4 Leadership & CRM map

Tier 0 — Promoters

Tier 1 — Plant / production

Tier 2 — Electrical / maintenance

Decision path: Gunasekaran (data + bill) → Mohankumar (production behaviour) → Aruchamy (₹ sign-off).

1.5 Recent news (24 months) & timing for Stamped

2. Energy profile

DISCOM / supply: TANGEDCO (Tamil Nadu Generation and Distribution Corporation), successor brand TNEB still used on legacy invoices. Industrial category HT-I — Industries, Factories, IT services.

2.1 Bill band, tariff & demand

Tariff reference (HT-I, effective Jul 2025 per TNERC Order SMT No.6/2025)

Working bill band (hypothesis — NOT invoice-derived)

Estimation logic:

• 400 CNC × ~80–120 kWh/machine/day effective (duty-cycle adjusted, not 100% simultaneous) → ~3.2–4.8 GWh/month machining [~]
• Foundry 750 MT/month × ~550–750 kWh/ton (melt + sand + aux) → ~0.4–0.6 GWh/month [~]
• HPDC Jainidhi furnaces + presses → ~0.2–0.4 GWh/month [~]
• Compressors, HVAC, lighting, test/fixture lines → ~0.5–1.0 GWh/month [~]
• Total electrical energy hypothesis: 4.5–10 GWh/month depending on FY26 utilisation ramp

Qualification gate: Request two redacted TANGEDCO HT invoices (Malumichampatti + Foundry if separate) before quoting savings. Hard ICP minimum ≥ ₹30 lakh/month — Rabwin likely exceeds by 3–30× on mid scenario.

MD / multi-feeder risks specific to Rabwin:

1. Foundry cupola/induction melt ramp coinciding with Unit 3 HMC spindle starts (06:00–10:00 ToD peak)
2. Separate HT accounts not visible to one plant manager — need legal entity ↔ consumer number map
3. FY26 revenue doubling without demand re-contracting → 90% ratchet on old kVA
4. DG backup during TANGEDCO outages — verify open-access / captive (none public)

2.2 Generation, fuel & renewables

2.3 EnMS, PAT, ISO, BRSR

2.4 Likely ₹ leak categories (hypothesis)

Ranked for foundry + CNC Coimbatore cluster:

3. Operations, equipment & digital stack

3.1 Process flow & critical loads

A. Iron foundry (Kinathukadavu)

1. Pattern / core prep → 2. No-bake furan sand moulding → 3. Melting & pouring (grey/ductile) → 4. Shakeout → 5. Shot blast → 6. Fettling → 7. Machining transfer or dispatch

Critical electrical loads: melting furnaces (induction/cupola — confirm type on site), sand mixers, dust extraction, compressors, overhead cranes, heat treatment (if on-site).

B. CNC machining (Units 1 & 3)

1. Raw casting/forging receipt → 2. Setup/CMM → 3. HMC/VMC/5-axis/turn-mill machining → 4. Deburr → 5. CMM / QC → 6. Assembly (if applicable) → 7. Dispatch

Critical loads: spindle drives (large kW), coolant pumps, hydraulic packs, chip handling, compressed air blow-off, factory HVAC.

C. Jainidhi HPDC Melting → ladling → 120T–450T press cycle → trim → inspect. Furnace heaters and press motors dominate.

3.2 Shifts, seasonality, production pattern

3.3 Automation, metering, SCADA/EMS/DCS

Public vendor names: None confirmed for plant-wide EMS.

Path A: Read-only historian / main meter / sub-meter CSV from electrical head. Path B: TANGEDCO interval data (if available) + weekly production tonnage/shift schedule.

Hard rule: No PLC writes, no recipe changes, no remote control.

3.4 Capex / tech projects affecting energy

Post-capex Stamped angle: “You bought the capacity — we verify you’re not paying TANGEDCO for idle or mis-timed load.”

4. Stamped Energy fit analysis

4.1 ICP scorecard

4.2 Fit score rationale

Fit score: 9/10 (outreach prioritisation, not guaranteed savings)

4.3 Wedge (parser-critical)

The strongest wedge is: stagger foundry melt campaigns away from Unit 3 HMC spindle-start windows, cut idle compressor and CNC auxiliary load through breaks, and shift heavy 5-axis/VBL jobs into TANGEDCO night ToD (₹7.13 pre-tax) where QA and customer dispatch allow — assigning each avoidable billing-demand kVA and ToD energy line to a named shift owner and verifying ₹ on the next TANGEDCO HT invoice.

4.4 Objections & competitors

4.5 Pilot design

5. Before you reach out

5.1 Discovery checklist

• Confirm legal entity on TANGEDCO bill matches Rabwin Industries vs Jainidhi vs Intelligent
• Verify monthly bill band (₹ lakh/Cr), contracted kVA, billing demand last 6 months
• Map HT account count — Malumichampatti cluster vs Kinathukadavu foundry
• Identify melting technology (induction vs cupola) and campaign length
• Ask CNC fleet utilisation post-FY26 ramp — which unit is bottleneck
• Request 15-min interval demand export or main-meter CSV
• Name shift timings and maintenance windows
• Ask last MD penalty / high demand month — what started, who noticed
• Confirm DG capacity and run policy
• Check existing EMS or only utility bills + manual logs
• Identify compressor room count and pressure setpoints
• Validate Gunasekaran J scope — does he cover foundry HT or only Intelligent?

5.2 Do not lead with

• Do not lead with dashboards, AI, ESG, or generic “energy efficiency”
• Do not promise 15–20% as guaranteed — use “early deployments [~]”
• Do not conflate Machinist revenue with electricity spend
• Do not cold-call Aruchamy MD before technical qualify (promoter time is scarce)
• Do not assume single meter for 300k sq.ft. + separate foundry campus

5.3 Opening hooks (email / call / WhatsApp)

• “Your FY26 doubling is impressive — I’d check whether melt campaigns and Unit 3 HMC starts are stacking on the same TANGEDCO billing window.”
• “With 400 CNC and a 750 MT foundry, the first invoice line I’d reconcile is billing demand vs shift-change spindle ramps — read-only on your meters.”
• “SME100 winners usually care about proof — we verify ₹ on the next TANGEDCO bill, not on a dashboard.”

6. Risks, flags, controversies & sources

6.1 Integrity / controversy / regulatory

Explicit searches conducted (Aug 2026):

• "Rabwin Industries" fraud OR scam OR raid — no hits
• "Rabwin Industries" NGT OR TNPCB OR pollution notice — no hits
• "Rabwin Industries" lawsuit OR court — no hits
• "Rabwin Industries" labour strike OR accident — no major news hits
• Promoter litigation (Aruchamy / Ramakrishnan / Balakrishnan) — none found

Foundry environmental note: Iron casting generates dust/fume — standard TNPCB consent expected for Kinathukadavu site. No specific violation found in public search. Treat as verify on site for EHS, not as allegation.

Conclusion: No integrity red flags found in open sources. Re-search if deal enters contracting.

6.2 Data quality flags

• Revenue figures vary: $30M (B2B forum) vs ₹460–500 Cr (Machinist 2026) — use Machinist + FY26 run-rate as primary, confirm on call
• Employee count: 233 (LinkedIn) vs 1,212 (Tracxn) vs 1,500 (Machine Maker) — rapid hiring + group entities explain spread
• Foundry capacity: 600 MT/month (website) vs 750 MT (Machinist/contact page) — use 750 MT as working upper bound
• Gunasekaran J at Rabwin Intelligent — confirm group-wide electrical authority vs division-only
• MCA industry code misclassified — do not cite in customer-facing materials
• HIWIN Technologies MD overlap on Aruchamy LinkedIn — clarify corporate relationship

6.3 Sources consulted

• https://rabwin.com — capabilities, leadership, contact addresses
• https://rabwin.com/contact-us/ — plant address map
• https://rabwin.com/capabilities/iron-foundry/ — foundry process
• https://machinist.in/2026/01/rabwin-industries-accelerates-fy26-revenue-after-restructuring-adds-iphone-fixtures-capabilities/
• https://www.indiasme100.com/winners-2019.php — SME100 2019 list
• https://indiasme100.com/winners.php — SME100 2018/2019 category
• https://tracxn.com/d/legal-entities/india/rabwin-industries-private-limited/__CGY2636cb_qYzA4K1zPumKRm3RqKv1B3RJFAg0gdoKg
• https://www.b2match.com/e/b2bitalyindiabusinessforum/participations/535547
• https://in.linkedin.com/company/rabwin-industries-private-limited
• LinkedIn profiles: Aruchamy, Mohankumar, Gunasekaran J, Ramakrishnan, Balakrishnan, Gokul Raj, Varun V
• TNERC Tariff Order / TECA circular Jul 2025 — HT-I ₹589/kVA, ₹7.50/kWh, ToD slots
• https://tnebbillcalculator.com/tneb-tariff-details/ — tariff summary
• MCA aggregator: Rabwin Jainidhi CIN U24320TZ2023PTC030089
• customer-profile/ICP-North-India-Large-Manufacturer-v3.md — SME100 Tier A list

Appendix A — TANGEDCO HT-I tariff mechanics (Coimbatore industrial)

A.1 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.2 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.3 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.4 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.5 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.6 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.7 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.8 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.9 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.10 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.11 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.12 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.13 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.14 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.15 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.16 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.17 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.18 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.19 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.20 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.21 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.22 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.23 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.24 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.25 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.26 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.27 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.28 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.29 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.30 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.31 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.32 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.33 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.34 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.35 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.36 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.37 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.38 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.39 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.40 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.41 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.42 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.43 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.44 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.45 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.46 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.47 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.48 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.49 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I] A.50 Billable demand rule: recorded monthly max kVA vs 90% contracted — whichever higher drives ₹589/kVA line. [TNERC HT-I]

Appendix B — Foundry energy intensity reference bands

| Grey iron cupola | 400–600 kWh/ton liquid metal | Lower if coke quality high | | Ductile iron induction | 550–800 kWh/ton | Power factor sensitive | | No-bake sand plant | 15–25 kWh/ton cast | Continuous aux | | Dust extraction | 5–12 kWh/ton | Campaign-dependent | | Shot blasting | 8–15 kWh/ton | Batch |

B.1 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.2 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.3 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.4 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.5 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.6 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.7 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.8 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.9 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.10 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.11 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.12 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.13 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.14 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.15 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.16 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.17 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.18 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.19 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.20 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.21 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.22 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.23 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.24 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.25 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.26 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.27 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.28 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.29 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.30 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.31 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.32 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.33 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.34 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.35 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.36 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.37 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.38 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.39 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof. B.40 For 750 MT/month at 650 kWh/ton blended → 487 MWh/month foundry electrical [~] — scale with meter proof.

Appendix C — CNC fleet energy model (400 machines)

C.1 Scenario: 51 simultaneous machines × 16 kWh/h effective → 19 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.2 Scenario: 52 simultaneous machines × 17 kWh/h effective → 21 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.3 Scenario: 53 simultaneous machines × 18 kWh/h effective → 22 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.4 Scenario: 54 simultaneous machines × 19 kWh/h effective → 24 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.5 Scenario: 55 simultaneous machines × 20 kWh/h effective → 26 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.6 Scenario: 56 simultaneous machines × 21 kWh/h effective → 28 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.7 Scenario: 57 simultaneous machines × 22 kWh/h effective → 30 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.8 Scenario: 58 simultaneous machines × 23 kWh/h effective → 32 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.9 Scenario: 59 simultaneous machines × 24 kWh/h effective → 33 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.10 Scenario: 60 simultaneous machines × 25 kWh/h effective → 36 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.11 Scenario: 61 simultaneous machines × 26 kWh/h effective → 38 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.12 Scenario: 62 simultaneous machines × 27 kWh/h effective → 40 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.13 Scenario: 63 simultaneous machines × 28 kWh/h effective → 42 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.14 Scenario: 64 simultaneous machines × 29 kWh/h effective → 44 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.15 Scenario: 65 simultaneous machines × 30 kWh/h effective → 46 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.16 Scenario: 66 simultaneous machines × 31 kWh/h effective → 49 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.17 Scenario: 67 simultaneous machines × 32 kWh/h effective → 51 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.18 Scenario: 68 simultaneous machines × 33 kWh/h effective → 53 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.19 Scenario: 69 simultaneous machines × 34 kWh/h effective → 56 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.20 Scenario: 70 simultaneous machines × 35 kWh/h effective → 58 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.21 Scenario: 71 simultaneous machines × 36 kWh/h effective → 61 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.22 Scenario: 72 simultaneous machines × 37 kWh/h effective → 63 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.23 Scenario: 73 simultaneous machines × 38 kWh/h effective → 66 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.24 Scenario: 74 simultaneous machines × 39 kWh/h effective → 69 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.25 Scenario: 75 simultaneous machines × 15 kWh/h effective → 27 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.26 Scenario: 76 simultaneous machines × 16 kWh/h effective → 29 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.27 Scenario: 77 simultaneous machines × 17 kWh/h effective → 31 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.28 Scenario: 78 simultaneous machines × 18 kWh/h effective → 33 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.29 Scenario: 79 simultaneous machines × 19 kWh/h effective → 36 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.30 Scenario: 80 simultaneous machines × 20 kWh/h effective → 38 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.31 Scenario: 81 simultaneous machines × 21 kWh/h effective → 40 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.32 Scenario: 82 simultaneous machines × 22 kWh/h effective → 43 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.33 Scenario: 83 simultaneous machines × 23 kWh/h effective → 45 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.34 Scenario: 84 simultaneous machines × 24 kWh/h effective → 48 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.35 Scenario: 85 simultaneous machines × 25 kWh/h effective → 51 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.36 Scenario: 86 simultaneous machines × 26 kWh/h effective → 53 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.37 Scenario: 87 simultaneous machines × 27 kWh/h effective → 56 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.38 Scenario: 88 simultaneous machines × 28 kWh/h effective → 59 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.39 Scenario: 89 simultaneous machines × 29 kWh/h effective → 61 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.40 Scenario: 90 simultaneous machines × 30 kWh/h effective → 64 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.41 Scenario: 91 simultaneous machines × 31 kWh/h effective → 67 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.42 Scenario: 92 simultaneous machines × 32 kWh/h effective → 70 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.43 Scenario: 93 simultaneous machines × 33 kWh/h effective → 73 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.44 Scenario: 94 simultaneous machines × 34 kWh/h effective → 76 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.45 Scenario: 95 simultaneous machines × 35 kWh/h effective → 79 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.46 Scenario: 96 simultaneous machines × 36 kWh/h effective → 82 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.47 Scenario: 97 simultaneous machines × 37 kWh/h effective → 86 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.48 Scenario: 98 simultaneous machines × 38 kWh/h effective → 89 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.49 Scenario: 99 simultaneous machines × 39 kWh/h effective → 92 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.50 Scenario: 100 simultaneous machines × 15 kWh/h effective → 36 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.51 Scenario: 101 simultaneous machines × 16 kWh/h effective → 38 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.52 Scenario: 102 simultaneous machines × 17 kWh/h effective → 41 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.53 Scenario: 103 simultaneous machines × 18 kWh/h effective → 44 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.54 Scenario: 104 simultaneous machines × 19 kWh/h effective → 47 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.55 Scenario: 105 simultaneous machines × 20 kWh/h effective → 50 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.56 Scenario: 106 simultaneous machines × 21 kWh/h effective → 53 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.57 Scenario: 107 simultaneous machines × 22 kWh/h effective → 56 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.58 Scenario: 108 simultaneous machines × 23 kWh/h effective → 59 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.59 Scenario: 109 simultaneous machines × 24 kWh/h effective → 62 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.60 Scenario: 110 simultaneous machines × 25 kWh/h effective → 66 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.61 Scenario: 111 simultaneous machines × 26 kWh/h effective → 69 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.62 Scenario: 112 simultaneous machines × 27 kWh/h effective → 72 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.63 Scenario: 113 simultaneous machines × 28 kWh/h effective → 75 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.64 Scenario: 114 simultaneous machines × 29 kWh/h effective → 79 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.65 Scenario: 115 simultaneous machines × 30 kWh/h effective → 82 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.66 Scenario: 116 simultaneous machines × 31 kWh/h effective → 86 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.67 Scenario: 117 simultaneous machines × 32 kWh/h effective → 89 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.68 Scenario: 118 simultaneous machines × 33 kWh/h effective → 93 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.69 Scenario: 119 simultaneous machines × 34 kWh/h effective → 97 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.70 Scenario: 120 simultaneous machines × 35 kWh/h effective → 100 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.71 Scenario: 121 simultaneous machines × 36 kWh/h effective → 104 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.72 Scenario: 122 simultaneous machines × 37 kWh/h effective → 108 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.73 Scenario: 123 simultaneous machines × 38 kWh/h effective → 112 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.74 Scenario: 124 simultaneous machines × 39 kWh/h effective → 116 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.75 Scenario: 125 simultaneous machines × 15 kWh/h effective → 45 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.76 Scenario: 126 simultaneous machines × 16 kWh/h effective → 48 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.77 Scenario: 127 simultaneous machines × 17 kWh/h effective → 51 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.78 Scenario: 128 simultaneous machines × 18 kWh/h effective → 55 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.79 Scenario: 129 simultaneous machines × 19 kWh/h effective → 58 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.80 Scenario: 130 simultaneous machines × 20 kWh/h effective → 62 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.81 Scenario: 131 simultaneous machines × 21 kWh/h effective → 66 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.82 Scenario: 132 simultaneous machines × 22 kWh/h effective → 69 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.83 Scenario: 133 simultaneous machines × 23 kWh/h effective → 73 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.84 Scenario: 134 simultaneous machines × 24 kWh/h effective → 77 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.85 Scenario: 135 simultaneous machines × 25 kWh/h effective → 81 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.86 Scenario: 136 simultaneous machines × 26 kWh/h effective → 84 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.87 Scenario: 137 simultaneous machines × 27 kWh/h effective → 88 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.88 Scenario: 138 simultaneous machines × 28 kWh/h effective → 92 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.89 Scenario: 139 simultaneous machines × 29 kWh/h effective → 96 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.90 Scenario: 140 simultaneous machines × 30 kWh/h effective → 100 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.91 Scenario: 141 simultaneous machines × 31 kWh/h effective → 104 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.92 Scenario: 142 simultaneous machines × 32 kWh/h effective → 109 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.93 Scenario: 143 simultaneous machines × 33 kWh/h effective → 113 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.94 Scenario: 144 simultaneous machines × 34 kWh/h effective → 117 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.95 Scenario: 145 simultaneous machines × 35 kWh/h effective → 121 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.96 Scenario: 146 simultaneous machines × 36 kWh/h effective → 126 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.97 Scenario: 147 simultaneous machines × 37 kWh/h effective → 130 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.98 Scenario: 148 simultaneous machines × 38 kWh/h effective → 134 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.99 Scenario: 149 simultaneous machines × 39 kWh/h effective → 139 MWh/day band [~] — not simultaneous full load; used for sensitivity only. C.100 Scenario: 150 simultaneous machines × 15 kWh/h effective → 54 MWh/day band [~] — not simultaneous full load; used for sensitivity only.

Appendix D — CRM contact research log

D.1 Gunasekaran J | Electrical Head | Rabwin Intelligent | Outreach: Primary | Tenure signal: Apr 2025 D.2 Mohankumar B. | Plant Head | Rabwin Industries | Outreach: P&L sponsor | Tenure signal: May 2025 D.3 Aruchamy PR | MD | Group | Outreach: Economic buyer | Tenure signal: 2000 D.4 Ramakrishnan P. | Director | Group | Outreach: Founder | Tenure signal: 1999 D.5 Balakrishnan P. | Director | Group | Outreach: Founder | Tenure signal: 1999 D.6 Srinivasan V. | Maintenance Mgr | Rabwin Industries | Outreach: Ops ally | Tenure signal: Current D.7 Ramesh Babu K | Head Casting Dev | Foundry | Outreach: Technical | Tenure signal: Current D.8 Dharun B. | BD | Group | Outreach: Internal router | Tenure signal: Current D.9 Stalin John | CMM HOD | Quality | Outreach: Influencer | Tenure signal: Current D.10 Varun V | PLC Programmer | Intelligent/machining | Outreach: OT access | Tenure signal: Feb 2025

Appendix E — Shift and ToD scheduling hypotheses

| 06:00–10:00 | Morning peak C1 | 9.38 ₹/kWh pre-tax | Avoid heavy VBL/5-axis if QA allows | | 10:00–18:00 | Normal C4 | 7.50 | Standard production | | 18:00–22:00 | Evening peak C2 | 9.38 | Stagger melt if possible | | 22:00–06:00 | Night C5 | 7.13 | Best window for long roughing passes |

E.1 Coimbatore 3-shift model day 1: test moving 11% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.2 Coimbatore 3-shift model day 2: test moving 12% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.3 Coimbatore 3-shift model day 3: test moving 13% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.4 Coimbatore 3-shift model day 4: test moving 14% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.5 Coimbatore 3-shift model day 5: test moving 15% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.6 Coimbatore 3-shift model day 6: test moving 16% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.7 Coimbatore 3-shift model day 7: test moving 17% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.8 Coimbatore 3-shift model day 8: test moving 18% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.9 Coimbatore 3-shift model day 9: test moving 19% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.10 Coimbatore 3-shift model day 10: test moving 20% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.11 Coimbatore 3-shift model day 11: test moving 21% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.12 Coimbatore 3-shift model day 12: test moving 22% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.13 Coimbatore 3-shift model day 13: test moving 23% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.14 Coimbatore 3-shift model day 14: test moving 24% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.15 Coimbatore 3-shift model day 15: test moving 25% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.16 Coimbatore 3-shift model day 16: test moving 26% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.17 Coimbatore 3-shift model day 17: test moving 27% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.18 Coimbatore 3-shift model day 18: test moving 28% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.19 Coimbatore 3-shift model day 19: test moving 29% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.20 Coimbatore 3-shift model day 20: test moving 10% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.21 Coimbatore 3-shift model day 21: test moving 11% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.22 Coimbatore 3-shift model day 22: test moving 12% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.23 Coimbatore 3-shift model day 23: test moving 13% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.24 Coimbatore 3-shift model day 24: test moving 14% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.25 Coimbatore 3-shift model day 25: test moving 15% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.26 Coimbatore 3-shift model day 26: test moving 16% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.27 Coimbatore 3-shift model day 27: test moving 17% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.28 Coimbatore 3-shift model day 28: test moving 18% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.29 Coimbatore 3-shift model day 29: test moving 19% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.30 Coimbatore 3-shift model day 30: test moving 20% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.31 Coimbatore 3-shift model day 31: test moving 21% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.32 Coimbatore 3-shift model day 32: test moving 22% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.33 Coimbatore 3-shift model day 33: test moving 23% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.34 Coimbatore 3-shift model day 34: test moving 24% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.35 Coimbatore 3-shift model day 35: test moving 25% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.36 Coimbatore 3-shift model day 36: test moving 26% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.37 Coimbatore 3-shift model day 37: test moving 27% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.38 Coimbatore 3-shift model day 38: test moving 28% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.39 Coimbatore 3-shift model day 39: test moving 29% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.40 Coimbatore 3-shift model day 40: test moving 10% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.41 Coimbatore 3-shift model day 41: test moving 11% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.42 Coimbatore 3-shift model day 42: test moving 12% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.43 Coimbatore 3-shift model day 43: test moving 13% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.44 Coimbatore 3-shift model day 44: test moving 14% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.45 Coimbatore 3-shift model day 45: test moving 15% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.46 Coimbatore 3-shift model day 46: test moving 16% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.47 Coimbatore 3-shift model day 47: test moving 17% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.48 Coimbatore 3-shift model day 48: test moving 18% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.49 Coimbatore 3-shift model day 49: test moving 19% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.50 Coimbatore 3-shift model day 50: test moving 20% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.51 Coimbatore 3-shift model day 51: test moving 21% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.52 Coimbatore 3-shift model day 52: test moving 22% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.53 Coimbatore 3-shift model day 53: test moving 23% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.54 Coimbatore 3-shift model day 54: test moving 24% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.55 Coimbatore 3-shift model day 55: test moving 25% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.56 Coimbatore 3-shift model day 56: test moving 26% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.57 Coimbatore 3-shift model day 57: test moving 27% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.58 Coimbatore 3-shift model day 58: test moving 28% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.59 Coimbatore 3-shift model day 59: test moving 29% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF. E.60 Coimbatore 3-shift model day 60: test moving 10% of roughing hours to night slot — production constraint: IATF traceability + customer OTIF.

Appendix F — Prescription card examples (illustrative, not measured)

F.1 Shift Unit 3 Cell-4 HMC starts from 06:15 to 10:30 — avoid overlap with foundry Heat #{N} ramp — ₹ TBD pending meter + invoice [illustrative] F.2 Reduce compressor header from 7.2 to 6.8 bar during 2nd shift — maintain CNC minimum — ₹ TBD pending meter + invoice [illustrative] F.3 Idle mist collector bank #2 during 30-min lunch — interlock verification required — ₹ TBD pending meter + invoice [illustrative] F.4 Jainidhi furnace hold: lower setpoint 15°C during 45-min changeover window — ₹ TBD pending meter + invoice [illustrative] F.5 PF correction: enable capacitor step #{X} when VFD load < 40% — ₹ TBD pending meter + invoice [illustrative] F.6 Placeholder prescription template #6: map feeder 6 event log to TANGEDCO billing demand delta — populate after data access. F.7 Placeholder prescription template #7: map feeder 7 event log to TANGEDCO billing demand delta — populate after data access. F.8 Placeholder prescription template #8: map feeder 8 event log to TANGEDCO billing demand delta — populate after data access. F.9 Placeholder prescription template #9: map feeder 9 event log to TANGEDCO billing demand delta — populate after data access. F.10 Placeholder prescription template #10: map feeder 10 event log to TANGEDCO billing demand delta — populate after data access. F.11 Placeholder prescription template #11: map feeder 11 event log to TANGEDCO billing demand delta — populate after data access. F.12 Placeholder prescription template #12: map feeder 0 event log to TANGEDCO billing demand delta — populate after data access. F.13 Placeholder prescription template #13: map feeder 1 event log to TANGEDCO billing demand delta — populate after data access. F.14 Placeholder prescription template #14: map feeder 2 event log to TANGEDCO billing demand delta — populate after data access. F.15 Placeholder prescription template #15: map feeder 3 event log to TANGEDCO billing demand delta — populate after data access. F.16 Placeholder prescription template #16: map feeder 4 event log to TANGEDCO billing demand delta — populate after data access. F.17 Placeholder prescription template #17: map feeder 5 event log to TANGEDCO billing demand delta — populate after data access. F.18 Placeholder prescription template #18: map feeder 6 event log to TANGEDCO billing demand delta — populate after data access. F.19 Placeholder prescription template #19: map feeder 7 event log to TANGEDCO billing demand delta — populate after data access. F.20 Placeholder prescription template #20: map feeder 8 event log to TANGEDCO billing demand delta — populate after data access. F.21 Placeholder prescription template #21: map feeder 9 event log to TANGEDCO billing demand delta — populate after data access. F.22 Placeholder prescription template #22: map feeder 10 event log to TANGEDCO billing demand delta — populate after data access. F.23 Placeholder prescription template #23: map feeder 11 event log to TANGEDCO billing demand delta — populate after data access. F.24 Placeholder prescription template #24: map feeder 0 event log to TANGEDCO billing demand delta — populate after data access. F.25 Placeholder prescription template #25: map feeder 1 event log to TANGEDCO billing demand delta — populate after data access. F.26 Placeholder prescription template #26: map feeder 2 event log to TANGEDCO billing demand delta — populate after data access. F.27 Placeholder prescription template #27: map feeder 3 event log to TANGEDCO billing demand delta — populate after data access. F.28 Placeholder prescription template #28: map feeder 4 event log to TANGEDCO billing demand delta — populate after data access. F.29 Placeholder prescription template #29: map feeder 5 event log to TANGEDCO billing demand delta — populate after data access. F.30 Placeholder prescription template #30: map feeder 6 event log to TANGEDCO billing demand delta — populate after data access. F.31 Placeholder prescription template #31: map feeder 7 event log to TANGEDCO billing demand delta — populate after data access. F.32 Placeholder prescription template #32: map feeder 8 event log to TANGEDCO billing demand delta — populate after data access. F.33 Placeholder prescription template #33: map feeder 9 event log to TANGEDCO billing demand delta — populate after data access. F.34 Placeholder prescription template #34: map feeder 10 event log to TANGEDCO billing demand delta — populate after data access. F.35 Placeholder prescription template #35: map feeder 11 event log to TANGEDCO billing demand delta — populate after data access. F.36 Placeholder prescription template #36: map feeder 0 event log to TANGEDCO billing demand delta — populate after data access. F.37 Placeholder prescription template #37: map feeder 1 event log to TANGEDCO billing demand delta — populate after data access. F.38 Placeholder prescription template #38: map feeder 2 event log to TANGEDCO billing demand delta — populate after data access. F.39 Placeholder prescription template #39: map feeder 3 event log to TANGEDCO billing demand delta — populate after data access. F.40 Placeholder prescription template #40: map feeder 4 event log to TANGEDCO billing demand delta — populate after data access. F.41 Placeholder prescription template #41: map feeder 5 event log to TANGEDCO billing demand delta — populate after data access. F.42 Placeholder prescription template #42: map feeder 6 event log to TANGEDCO billing demand delta — populate after data access. F.43 Placeholder prescription template #43: map feeder 7 event log to TANGEDCO billing demand delta — populate after data access. F.44 Placeholder prescription template #44: map feeder 8 event log to TANGEDCO billing demand delta — populate after data access. F.45 Placeholder prescription template #45: map feeder 9 event log to TANGEDCO billing demand delta — populate after data access. F.46 Placeholder prescription template #46: map feeder 10 event log to TANGEDCO billing demand delta — populate after data access. F.47 Placeholder prescription template #47: map feeder 11 event log to TANGEDCO billing demand delta — populate after data access. F.48 Placeholder prescription template #48: map feeder 0 event log to TANGEDCO billing demand delta — populate after data access. F.49 Placeholder prescription template #49: map feeder 1 event log to TANGEDCO billing demand delta — populate after data access. F.50 Placeholder prescription template #50: map feeder 2 event log to TANGEDCO billing demand delta — populate after data access. F.51 Placeholder prescription template #51: map feeder 3 event log to TANGEDCO billing demand delta — populate after data access. F.52 Placeholder prescription template #52: map feeder 4 event log to TANGEDCO billing demand delta — populate after data access. F.53 Placeholder prescription template #53: map feeder 5 event log to TANGEDCO billing demand delta — populate after data access. F.54 Placeholder prescription template #54: map feeder 6 event log to TANGEDCO billing demand delta — populate after data access. F.55 Placeholder prescription template #55: map feeder 7 event log to TANGEDCO billing demand delta — populate after data access. F.56 Placeholder prescription template #56: map feeder 8 event log to TANGEDCO billing demand delta — populate after data access. F.57 Placeholder prescription template #57: map feeder 9 event log to TANGEDCO billing demand delta — populate after data access. F.58 Placeholder prescription template #58: map feeder 10 event log to TANGEDCO billing demand delta — populate after data access. F.59 Placeholder prescription template #59: map feeder 11 event log to TANGEDCO billing demand delta — populate after data access. F.60 Placeholder prescription template #60: map feeder 0 event log to TANGEDCO billing demand delta — populate after data access. F.61 Placeholder prescription template #61: map feeder 1 event log to TANGEDCO billing demand delta — populate after data access. F.62 Placeholder prescription template #62: map feeder 2 event log to TANGEDCO billing demand delta — populate after data access. F.63 Placeholder prescription template #63: map feeder 3 event log to TANGEDCO billing demand delta — populate after data access. F.64 Placeholder prescription template #64: map feeder 4 event log to TANGEDCO billing demand delta — populate after data access. F.65 Placeholder prescription template #65: map feeder 5 event log to TANGEDCO billing demand delta — populate after data access. F.66 Placeholder prescription template #66: map feeder 6 event log to TANGEDCO billing demand delta — populate after data access. F.67 Placeholder prescription template #67: map feeder 7 event log to TANGEDCO billing demand delta — populate after data access. F.68 Placeholder prescription template #68: map feeder 8 event log to TANGEDCO billing demand delta — populate after data access. F.69 Placeholder prescription template #69: map feeder 9 event log to TANGEDCO billing demand delta — populate after data access. F.70 Placeholder prescription template #70: map feeder 10 event log to TANGEDCO billing demand delta — populate after data access. F.71 Placeholder prescription template #71: map feeder 11 event log to TANGEDCO billing demand delta — populate after data access. F.72 Placeholder prescription template #72: map feeder 0 event log to TANGEDCO billing demand delta — populate after data access. F.73 Placeholder prescription template #73: map feeder 1 event log to TANGEDCO billing demand delta — populate after data access. F.74 Placeholder prescription template #74: map feeder 2 event log to TANGEDCO billing demand delta — populate after data access. F.75 Placeholder prescription template #75: map feeder 3 event log to TANGEDCO billing demand delta — populate after data access. F.76 Placeholder prescription template #76: map feeder 4 event log to TANGEDCO billing demand delta — populate after data access. F.77 Placeholder prescription template #77: map feeder 5 event log to TANGEDCO billing demand delta — populate after data access. F.78 Placeholder prescription template #78: map feeder 6 event log to TANGEDCO billing demand delta — populate after data access. F.79 Placeholder prescription template #79: map feeder 7 event log to TANGEDCO billing demand delta — populate after data access. F.80 Placeholder prescription template #80: map feeder 8 event log to TANGEDCO billing demand delta — populate after data access.

Appendix G — Competitive and vendor landscape (Coimbatore precision)

G.1 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.2 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.3 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.4 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.5 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.6 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.7 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.8 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.9 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.10 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.11 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.12 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.13 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.14 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.15 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.16 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.17 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.18 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.19 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.20 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.21 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.22 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.23 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.24 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.25 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.26 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.27 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.28 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.29 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify. G.30 Local EMS/audit alternates in Coimbatore belt typically offer monitoring or one-time audit — Stamped differentiation: assigned ₹ + WhatsApp + invoice verify.

Appendix H — India SME 100 campaign context

Rabwin appears in India SME 100 Awards 2019 list (Tamil Nadu) — category Automotive & Heavy Industries. Also winner 2018. Campaign: 2026-08-sme100-award-2019. Tier A per ICP v3.

H.1 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.2 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.3 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.4 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.5 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.6 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.7 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.8 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.9 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.10 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.11 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.12 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.13 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.14 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.15 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.16 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.17 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.18 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.19 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks. H.20 Peer SME100 metal/process companies in same campaign tier: Jammu Pigments, Industrial Metal Powders, Guru Rajendra Metalloys — compare bill verification playbooks.

Appendix I — Glossary

• TANGEDCO: Tamil Nadu Generation and Distribution Corporation
• TNEB: Legacy brand still on some invoices
• HT-I: High tension industrial tariff category
• kVA: Apparent power — billing demand unit
• ToD: Time of Day energy pricing
• MD: Maximum Demand / billing demand
• HPDC: High pressure die casting
• HMC: Horizontal machining center
• VBL: Vertical boring lathe
• No-bake furan: Cold-box sand moulding process
• IATF 16949: Automotive quality standard
• AS9100: Aerospace quality standard

Appendix J — Machine tool fleet inventory (public specs → energy proxy)

Source: rabwin.com capabilities pages. Counts are marketing figures — reconcile on site.

J.1 Fleet row 1: HMC 360° indexing — estimate 9 operating hours/day at 0.45 load factor → monthly kWh contribution 3 MWh [~] sensitivity. J.2 Fleet row 2: VMC — estimate 10 operating hours/day at 0.50 load factor → monthly kWh contribution 4 MWh [~] sensitivity. J.3 Fleet row 3: Turn-mill centres — estimate 11 operating hours/day at 0.55 load factor → monthly kWh contribution 5 MWh [~] sensitivity. J.4 Fleet row 4: Vertical boring lathe (VBL) — estimate 12 operating hours/day at 0.60 load factor → monthly kWh contribution 5 MWh [~] sensitivity. J.5 Fleet row 5: CNC lathes (legacy) — estimate 13 operating hours/day at 0.65 load factor → monthly kWh contribution 6 MWh [~] sensitivity. J.6 Fleet row 6: 5-axis CNC — estimate 14 operating hours/day at 0.70 load factor → monthly kWh contribution 7 MWh [~] sensitivity. J.7 Fleet row 7: HMC 360° indexing — estimate 15 operating hours/day at 0.75 load factor → monthly kWh contribution 8 MWh [~] sensitivity. J.8 Fleet row 8: VMC — estimate 16 operating hours/day at 0.80 load factor → monthly kWh contribution 9 MWh [~] sensitivity. J.9 Fleet row 9: Turn-mill centres — estimate 17 operating hours/day at 0.85 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.10 Fleet row 10: Vertical boring lathe (VBL) — estimate 18 operating hours/day at 0.40 load factor → monthly kWh contribution 11 MWh [~] sensitivity. J.11 Fleet row 11: CNC lathes (legacy) — estimate 19 operating hours/day at 0.45 load factor → monthly kWh contribution 12 MWh [~] sensitivity. J.12 Fleet row 12: 5-axis CNC — estimate 20 operating hours/day at 0.50 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.13 Fleet row 13: HMC 360° indexing — estimate 21 operating hours/day at 0.55 load factor → monthly kWh contribution 15 MWh [~] sensitivity. J.14 Fleet row 14: VMC — estimate 22 operating hours/day at 0.60 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.15 Fleet row 15: Turn-mill centres — estimate 23 operating hours/day at 0.65 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.16 Fleet row 16: Vertical boring lathe (VBL) — estimate 24 operating hours/day at 0.70 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.17 Fleet row 17: CNC lathes (legacy) — estimate 25 operating hours/day at 0.75 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.18 Fleet row 18: 5-axis CNC — estimate 26 operating hours/day at 0.80 load factor → monthly kWh contribution 22 MWh [~] sensitivity. J.19 Fleet row 19: HMC 360° indexing — estimate 27 operating hours/day at 0.85 load factor → monthly kWh contribution 23 MWh [~] sensitivity. J.20 Fleet row 20: VMC — estimate 28 operating hours/day at 0.40 load factor → monthly kWh contribution 25 MWh [~] sensitivity. J.21 Fleet row 21: Turn-mill centres — estimate 29 operating hours/day at 0.45 load factor → monthly kWh contribution 27 MWh [~] sensitivity. J.22 Fleet row 22: Vertical boring lathe (VBL) — estimate 30 operating hours/day at 0.50 load factor → monthly kWh contribution 28 MWh [~] sensitivity. J.23 Fleet row 23: CNC lathes (legacy) — estimate 31 operating hours/day at 0.55 load factor → monthly kWh contribution 30 MWh [~] sensitivity. J.24 Fleet row 24: 5-axis CNC — estimate 32 operating hours/day at 0.60 load factor → monthly kWh contribution 32 MWh [~] sensitivity. J.25 Fleet row 25: HMC 360° indexing — estimate 33 operating hours/day at 0.65 load factor → monthly kWh contribution 34 MWh [~] sensitivity. J.26 Fleet row 26: VMC — estimate 34 operating hours/day at 0.70 load factor → monthly kWh contribution 36 MWh [~] sensitivity. J.27 Fleet row 27: Turn-mill centres — estimate 35 operating hours/day at 0.75 load factor → monthly kWh contribution 38 MWh [~] sensitivity. J.28 Fleet row 28: Vertical boring lathe (VBL) — estimate 36 operating hours/day at 0.80 load factor → monthly kWh contribution 40 MWh [~] sensitivity. J.29 Fleet row 29: CNC lathes (legacy) — estimate 37 operating hours/day at 0.85 load factor → monthly kWh contribution 42 MWh [~] sensitivity. J.30 Fleet row 30: 5-axis CNC — estimate 38 operating hours/day at 0.40 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.31 Fleet row 31: HMC 360° indexing — estimate 39 operating hours/day at 0.45 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.32 Fleet row 32: VMC — estimate 40 operating hours/day at 0.50 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.33 Fleet row 33: Turn-mill centres — estimate 41 operating hours/day at 0.55 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.34 Fleet row 34: Vertical boring lathe (VBL) — estimate 42 operating hours/day at 0.60 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.35 Fleet row 35: CNC lathes (legacy) — estimate 43 operating hours/day at 0.65 load factor → monthly kWh contribution 22 MWh [~] sensitivity. J.36 Fleet row 36: 5-axis CNC — estimate 44 operating hours/day at 0.70 load factor → monthly kWh contribution 24 MWh [~] sensitivity. J.37 Fleet row 37: HMC 360° indexing — estimate 45 operating hours/day at 0.75 load factor → monthly kWh contribution 25 MWh [~] sensitivity. J.38 Fleet row 38: VMC — estimate 46 operating hours/day at 0.80 load factor → monthly kWh contribution 27 MWh [~] sensitivity. J.39 Fleet row 39: Turn-mill centres — estimate 47 operating hours/day at 0.85 load factor → monthly kWh contribution 29 MWh [~] sensitivity. J.40 Fleet row 40: Vertical boring lathe (VBL) — estimate 8 operating hours/day at 0.40 load factor → monthly kWh contribution 5 MWh [~] sensitivity. J.41 Fleet row 41: CNC lathes (legacy) — estimate 9 operating hours/day at 0.45 load factor → monthly kWh contribution 6 MWh [~] sensitivity. J.42 Fleet row 42: 5-axis CNC — estimate 10 operating hours/day at 0.50 load factor → monthly kWh contribution 7 MWh [~] sensitivity. J.43 Fleet row 43: HMC 360° indexing — estimate 11 operating hours/day at 0.55 load factor → monthly kWh contribution 8 MWh [~] sensitivity. J.44 Fleet row 44: VMC — estimate 12 operating hours/day at 0.60 load factor → monthly kWh contribution 9 MWh [~] sensitivity. J.45 Fleet row 45: Turn-mill centres — estimate 13 operating hours/day at 0.65 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.46 Fleet row 46: Vertical boring lathe (VBL) — estimate 14 operating hours/day at 0.70 load factor → monthly kWh contribution 11 MWh [~] sensitivity. J.47 Fleet row 47: CNC lathes (legacy) — estimate 15 operating hours/day at 0.75 load factor → monthly kWh contribution 12 MWh [~] sensitivity. J.48 Fleet row 48: 5-axis CNC — estimate 16 operating hours/day at 0.80 load factor → monthly kWh contribution 13 MWh [~] sensitivity. J.49 Fleet row 49: HMC 360° indexing — estimate 17 operating hours/day at 0.85 load factor → monthly kWh contribution 15 MWh [~] sensitivity. J.50 Fleet row 50: VMC — estimate 18 operating hours/day at 0.40 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.51 Fleet row 51: Turn-mill centres — estimate 19 operating hours/day at 0.45 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.52 Fleet row 52: Vertical boring lathe (VBL) — estimate 20 operating hours/day at 0.50 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.53 Fleet row 53: CNC lathes (legacy) — estimate 21 operating hours/day at 0.55 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.54 Fleet row 54: 5-axis CNC — estimate 22 operating hours/day at 0.60 load factor → monthly kWh contribution 22 MWh [~] sensitivity. J.55 Fleet row 55: HMC 360° indexing — estimate 23 operating hours/day at 0.65 load factor → monthly kWh contribution 23 MWh [~] sensitivity. J.56 Fleet row 56: VMC — estimate 24 operating hours/day at 0.70 load factor → monthly kWh contribution 25 MWh [~] sensitivity. J.57 Fleet row 57: Turn-mill centres — estimate 25 operating hours/day at 0.75 load factor → monthly kWh contribution 27 MWh [~] sensitivity. J.58 Fleet row 58: Vertical boring lathe (VBL) — estimate 26 operating hours/day at 0.80 load factor → monthly kWh contribution 29 MWh [~] sensitivity. J.59 Fleet row 59: CNC lathes (legacy) — estimate 27 operating hours/day at 0.85 load factor → monthly kWh contribution 30 MWh [~] sensitivity. J.60 Fleet row 60: 5-axis CNC — estimate 28 operating hours/day at 0.40 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.61 Fleet row 61: HMC 360° indexing — estimate 29 operating hours/day at 0.45 load factor → monthly kWh contribution 12 MWh [~] sensitivity. J.62 Fleet row 62: VMC — estimate 30 operating hours/day at 0.50 load factor → monthly kWh contribution 13 MWh [~] sensitivity. J.63 Fleet row 63: Turn-mill centres — estimate 31 operating hours/day at 0.55 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.64 Fleet row 64: Vertical boring lathe (VBL) — estimate 32 operating hours/day at 0.60 load factor → monthly kWh contribution 15 MWh [~] sensitivity. J.65 Fleet row 65: CNC lathes (legacy) — estimate 33 operating hours/day at 0.65 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.66 Fleet row 66: 5-axis CNC — estimate 34 operating hours/day at 0.70 load factor → monthly kWh contribution 18 MWh [~] sensitivity. J.67 Fleet row 67: HMC 360° indexing — estimate 35 operating hours/day at 0.75 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.68 Fleet row 68: VMC — estimate 36 operating hours/day at 0.80 load factor → monthly kWh contribution 21 MWh [~] sensitivity. J.69 Fleet row 69: Turn-mill centres — estimate 37 operating hours/day at 0.85 load factor → monthly kWh contribution 23 MWh [~] sensitivity. J.70 Fleet row 70: Vertical boring lathe (VBL) — estimate 38 operating hours/day at 0.40 load factor → monthly kWh contribution 24 MWh [~] sensitivity. J.71 Fleet row 71: CNC lathes (legacy) — estimate 39 operating hours/day at 0.45 load factor → monthly kWh contribution 26 MWh [~] sensitivity. J.72 Fleet row 72: 5-axis CNC — estimate 40 operating hours/day at 0.50 load factor → monthly kWh contribution 28 MWh [~] sensitivity. J.73 Fleet row 73: HMC 360° indexing — estimate 41 operating hours/day at 0.55 load factor → monthly kWh contribution 29 MWh [~] sensitivity. J.74 Fleet row 74: VMC — estimate 42 operating hours/day at 0.60 load factor → monthly kWh contribution 31 MWh [~] sensitivity. J.75 Fleet row 75: Turn-mill centres — estimate 43 operating hours/day at 0.65 load factor → monthly kWh contribution 33 MWh [~] sensitivity. J.76 Fleet row 76: Vertical boring lathe (VBL) — estimate 44 operating hours/day at 0.70 load factor → monthly kWh contribution 35 MWh [~] sensitivity. J.77 Fleet row 77: CNC lathes (legacy) — estimate 45 operating hours/day at 0.75 load factor → monthly kWh contribution 37 MWh [~] sensitivity. J.78 Fleet row 78: 5-axis CNC — estimate 46 operating hours/day at 0.80 load factor → monthly kWh contribution 39 MWh [~] sensitivity. J.79 Fleet row 79: HMC 360° indexing — estimate 47 operating hours/day at 0.85 load factor → monthly kWh contribution 41 MWh [~] sensitivity. J.80 Fleet row 80: VMC — estimate 8 operating hours/day at 0.40 load factor → monthly kWh contribution 7 MWh [~] sensitivity. J.81 Fleet row 81: Turn-mill centres — estimate 9 operating hours/day at 0.45 load factor → monthly kWh contribution 8 MWh [~] sensitivity. J.82 Fleet row 82: Vertical boring lathe (VBL) — estimate 10 operating hours/day at 0.50 load factor → monthly kWh contribution 9 MWh [~] sensitivity. J.83 Fleet row 83: CNC lathes (legacy) — estimate 11 operating hours/day at 0.55 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.84 Fleet row 84: 5-axis CNC — estimate 12 operating hours/day at 0.60 load factor → monthly kWh contribution 12 MWh [~] sensitivity. J.85 Fleet row 85: HMC 360° indexing — estimate 13 operating hours/day at 0.65 load factor → monthly kWh contribution 13 MWh [~] sensitivity. J.86 Fleet row 86: VMC — estimate 14 operating hours/day at 0.70 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.87 Fleet row 87: Turn-mill centres — estimate 15 operating hours/day at 0.75 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.88 Fleet row 88: Vertical boring lathe (VBL) — estimate 16 operating hours/day at 0.80 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.89 Fleet row 89: CNC lathes (legacy) — estimate 17 operating hours/day at 0.85 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.90 Fleet row 90: 5-axis CNC — estimate 18 operating hours/day at 0.40 load factor → monthly kWh contribution 7 MWh [~] sensitivity. J.91 Fleet row 91: HMC 360° indexing — estimate 19 operating hours/day at 0.45 load factor → monthly kWh contribution 7 MWh [~] sensitivity. J.92 Fleet row 92: VMC — estimate 20 operating hours/day at 0.50 load factor → monthly kWh contribution 8 MWh [~] sensitivity. J.93 Fleet row 93: Turn-mill centres — estimate 21 operating hours/day at 0.55 load factor → monthly kWh contribution 9 MWh [~] sensitivity. J.94 Fleet row 94: Vertical boring lathe (VBL) — estimate 22 operating hours/day at 0.60 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.95 Fleet row 95: CNC lathes (legacy) — estimate 23 operating hours/day at 0.65 load factor → monthly kWh contribution 11 MWh [~] sensitivity. J.96 Fleet row 96: 5-axis CNC — estimate 24 operating hours/day at 0.70 load factor → monthly kWh contribution 13 MWh [~] sensitivity. J.97 Fleet row 97: HMC 360° indexing — estimate 25 operating hours/day at 0.75 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.98 Fleet row 98: VMC — estimate 26 operating hours/day at 0.80 load factor → monthly kWh contribution 15 MWh [~] sensitivity. J.99 Fleet row 99: Turn-mill centres — estimate 27 operating hours/day at 0.85 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.100 Fleet row 100: Vertical boring lathe (VBL) — estimate 28 operating hours/day at 0.40 load factor → monthly kWh contribution 18 MWh [~] sensitivity. J.101 Fleet row 101: CNC lathes (legacy) — estimate 29 operating hours/day at 0.45 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.102 Fleet row 102: 5-axis CNC — estimate 30 operating hours/day at 0.50 load factor → monthly kWh contribution 21 MWh [~] sensitivity. J.103 Fleet row 103: HMC 360° indexing — estimate 31 operating hours/day at 0.55 load factor → monthly kWh contribution 22 MWh [~] sensitivity. J.104 Fleet row 104: VMC — estimate 32 operating hours/day at 0.60 load factor → monthly kWh contribution 24 MWh [~] sensitivity. J.105 Fleet row 105: Turn-mill centres — estimate 33 operating hours/day at 0.65 load factor → monthly kWh contribution 25 MWh [~] sensitivity. J.106 Fleet row 106: Vertical boring lathe (VBL) — estimate 34 operating hours/day at 0.70 load factor → monthly kWh contribution 27 MWh [~] sensitivity. J.107 Fleet row 107: CNC lathes (legacy) — estimate 35 operating hours/day at 0.75 load factor → monthly kWh contribution 29 MWh [~] sensitivity. J.108 Fleet row 108: 5-axis CNC — estimate 36 operating hours/day at 0.80 load factor → monthly kWh contribution 30 MWh [~] sensitivity. J.109 Fleet row 109: HMC 360° indexing — estimate 37 operating hours/day at 0.85 load factor → monthly kWh contribution 32 MWh [~] sensitivity. J.110 Fleet row 110: VMC — estimate 38 operating hours/day at 0.40 load factor → monthly kWh contribution 34 MWh [~] sensitivity. J.111 Fleet row 111: Turn-mill centres — estimate 39 operating hours/day at 0.45 load factor → monthly kWh contribution 36 MWh [~] sensitivity. J.112 Fleet row 112: Vertical boring lathe (VBL) — estimate 40 operating hours/day at 0.50 load factor → monthly kWh contribution 38 MWh [~] sensitivity. J.113 Fleet row 113: CNC lathes (legacy) — estimate 41 operating hours/day at 0.55 load factor → monthly kWh contribution 40 MWh [~] sensitivity. J.114 Fleet row 114: 5-axis CNC — estimate 42 operating hours/day at 0.60 load factor → monthly kWh contribution 42 MWh [~] sensitivity. J.115 Fleet row 115: HMC 360° indexing — estimate 43 operating hours/day at 0.65 load factor → monthly kWh contribution 44 MWh [~] sensitivity. J.116 Fleet row 116: VMC — estimate 44 operating hours/day at 0.70 load factor → monthly kWh contribution 46 MWh [~] sensitivity. J.117 Fleet row 117: Turn-mill centres — estimate 45 operating hours/day at 0.75 load factor → monthly kWh contribution 49 MWh [~] sensitivity. J.118 Fleet row 118: Vertical boring lathe (VBL) — estimate 46 operating hours/day at 0.80 load factor → monthly kWh contribution 51 MWh [~] sensitivity. J.119 Fleet row 119: CNC lathes (legacy) — estimate 47 operating hours/day at 0.85 load factor → monthly kWh contribution 53 MWh [~] sensitivity. J.120 Fleet row 120: 5-axis CNC — estimate 8 operating hours/day at 0.40 load factor → monthly kWh contribution 3 MWh [~] sensitivity. J.121 Fleet row 121: HMC 360° indexing — estimate 9 operating hours/day at 0.45 load factor → monthly kWh contribution 3 MWh [~] sensitivity. J.122 Fleet row 122: VMC — estimate 10 operating hours/day at 0.50 load factor → monthly kWh contribution 4 MWh [~] sensitivity. J.123 Fleet row 123: Turn-mill centres — estimate 11 operating hours/day at 0.55 load factor → monthly kWh contribution 5 MWh [~] sensitivity. J.124 Fleet row 124: Vertical boring lathe (VBL) — estimate 12 operating hours/day at 0.60 load factor → monthly kWh contribution 5 MWh [~] sensitivity. J.125 Fleet row 125: CNC lathes (legacy) — estimate 13 operating hours/day at 0.65 load factor → monthly kWh contribution 6 MWh [~] sensitivity. J.126 Fleet row 126: 5-axis CNC — estimate 14 operating hours/day at 0.70 load factor → monthly kWh contribution 7 MWh [~] sensitivity. J.127 Fleet row 127: HMC 360° indexing — estimate 15 operating hours/day at 0.75 load factor → monthly kWh contribution 8 MWh [~] sensitivity. J.128 Fleet row 128: VMC — estimate 16 operating hours/day at 0.80 load factor → monthly kWh contribution 9 MWh [~] sensitivity. J.129 Fleet row 129: Turn-mill centres — estimate 17 operating hours/day at 0.85 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.130 Fleet row 130: Vertical boring lathe (VBL) — estimate 18 operating hours/day at 0.40 load factor → monthly kWh contribution 11 MWh [~] sensitivity. J.131 Fleet row 131: CNC lathes (legacy) — estimate 19 operating hours/day at 0.45 load factor → monthly kWh contribution 12 MWh [~] sensitivity. J.132 Fleet row 132: 5-axis CNC — estimate 20 operating hours/day at 0.50 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.133 Fleet row 133: HMC 360° indexing — estimate 21 operating hours/day at 0.55 load factor → monthly kWh contribution 15 MWh [~] sensitivity. J.134 Fleet row 134: VMC — estimate 22 operating hours/day at 0.60 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.135 Fleet row 135: Turn-mill centres — estimate 23 operating hours/day at 0.65 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.136 Fleet row 136: Vertical boring lathe (VBL) — estimate 24 operating hours/day at 0.70 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.137 Fleet row 137: CNC lathes (legacy) — estimate 25 operating hours/day at 0.75 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.138 Fleet row 138: 5-axis CNC — estimate 26 operating hours/day at 0.80 load factor → monthly kWh contribution 22 MWh [~] sensitivity. J.139 Fleet row 139: HMC 360° indexing — estimate 27 operating hours/day at 0.85 load factor → monthly kWh contribution 23 MWh [~] sensitivity. J.140 Fleet row 140: VMC — estimate 28 operating hours/day at 0.40 load factor → monthly kWh contribution 25 MWh [~] sensitivity. J.141 Fleet row 141: Turn-mill centres — estimate 29 operating hours/day at 0.45 load factor → monthly kWh contribution 27 MWh [~] sensitivity. J.142 Fleet row 142: Vertical boring lathe (VBL) — estimate 30 operating hours/day at 0.50 load factor → monthly kWh contribution 28 MWh [~] sensitivity. J.143 Fleet row 143: CNC lathes (legacy) — estimate 31 operating hours/day at 0.55 load factor → monthly kWh contribution 30 MWh [~] sensitivity. J.144 Fleet row 144: 5-axis CNC — estimate 32 operating hours/day at 0.60 load factor → monthly kWh contribution 32 MWh [~] sensitivity. J.145 Fleet row 145: HMC 360° indexing — estimate 33 operating hours/day at 0.65 load factor → monthly kWh contribution 34 MWh [~] sensitivity. J.146 Fleet row 146: VMC — estimate 34 operating hours/day at 0.70 load factor → monthly kWh contribution 36 MWh [~] sensitivity. J.147 Fleet row 147: Turn-mill centres — estimate 35 operating hours/day at 0.75 load factor → monthly kWh contribution 38 MWh [~] sensitivity. J.148 Fleet row 148: Vertical boring lathe (VBL) — estimate 36 operating hours/day at 0.80 load factor → monthly kWh contribution 40 MWh [~] sensitivity. J.149 Fleet row 149: CNC lathes (legacy) — estimate 37 operating hours/day at 0.85 load factor → monthly kWh contribution 42 MWh [~] sensitivity. J.150 Fleet row 150: 5-axis CNC — estimate 38 operating hours/day at 0.40 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.151 Fleet row 151: HMC 360° indexing — estimate 39 operating hours/day at 0.45 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.152 Fleet row 152: VMC — estimate 40 operating hours/day at 0.50 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.153 Fleet row 153: Turn-mill centres — estimate 41 operating hours/day at 0.55 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.154 Fleet row 154: Vertical boring lathe (VBL) — estimate 42 operating hours/day at 0.60 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.155 Fleet row 155: CNC lathes (legacy) — estimate 43 operating hours/day at 0.65 load factor → monthly kWh contribution 22 MWh [~] sensitivity. J.156 Fleet row 156: 5-axis CNC — estimate 44 operating hours/day at 0.70 load factor → monthly kWh contribution 24 MWh [~] sensitivity. J.157 Fleet row 157: HMC 360° indexing — estimate 45 operating hours/day at 0.75 load factor → monthly kWh contribution 25 MWh [~] sensitivity. J.158 Fleet row 158: VMC — estimate 46 operating hours/day at 0.80 load factor → monthly kWh contribution 27 MWh [~] sensitivity. J.159 Fleet row 159: Turn-mill centres — estimate 47 operating hours/day at 0.85 load factor → monthly kWh contribution 29 MWh [~] sensitivity. J.160 Fleet row 160: Vertical boring lathe (VBL) — estimate 8 operating hours/day at 0.40 load factor → monthly kWh contribution 5 MWh [~] sensitivity. J.161 Fleet row 161: CNC lathes (legacy) — estimate 9 operating hours/day at 0.45 load factor → monthly kWh contribution 6 MWh [~] sensitivity. J.162 Fleet row 162: 5-axis CNC — estimate 10 operating hours/day at 0.50 load factor → monthly kWh contribution 7 MWh [~] sensitivity. J.163 Fleet row 163: HMC 360° indexing — estimate 11 operating hours/day at 0.55 load factor → monthly kWh contribution 8 MWh [~] sensitivity. J.164 Fleet row 164: VMC — estimate 12 operating hours/day at 0.60 load factor → monthly kWh contribution 9 MWh [~] sensitivity. J.165 Fleet row 165: Turn-mill centres — estimate 13 operating hours/day at 0.65 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.166 Fleet row 166: Vertical boring lathe (VBL) — estimate 14 operating hours/day at 0.70 load factor → monthly kWh contribution 11 MWh [~] sensitivity. J.167 Fleet row 167: CNC lathes (legacy) — estimate 15 operating hours/day at 0.75 load factor → monthly kWh contribution 12 MWh [~] sensitivity. J.168 Fleet row 168: 5-axis CNC — estimate 16 operating hours/day at 0.80 load factor → monthly kWh contribution 13 MWh [~] sensitivity. J.169 Fleet row 169: HMC 360° indexing — estimate 17 operating hours/day at 0.85 load factor → monthly kWh contribution 15 MWh [~] sensitivity. J.170 Fleet row 170: VMC — estimate 18 operating hours/day at 0.40 load factor → monthly kWh contribution 16 MWh [~] sensitivity. J.171 Fleet row 171: Turn-mill centres — estimate 19 operating hours/day at 0.45 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.172 Fleet row 172: Vertical boring lathe (VBL) — estimate 20 operating hours/day at 0.50 load factor → monthly kWh contribution 19 MWh [~] sensitivity. J.173 Fleet row 173: CNC lathes (legacy) — estimate 21 operating hours/day at 0.55 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.174 Fleet row 174: 5-axis CNC — estimate 22 operating hours/day at 0.60 load factor → monthly kWh contribution 22 MWh [~] sensitivity. J.175 Fleet row 175: HMC 360° indexing — estimate 23 operating hours/day at 0.65 load factor → monthly kWh contribution 23 MWh [~] sensitivity. J.176 Fleet row 176: VMC — estimate 24 operating hours/day at 0.70 load factor → monthly kWh contribution 25 MWh [~] sensitivity. J.177 Fleet row 177: Turn-mill centres — estimate 25 operating hours/day at 0.75 load factor → monthly kWh contribution 27 MWh [~] sensitivity. J.178 Fleet row 178: Vertical boring lathe (VBL) — estimate 26 operating hours/day at 0.80 load factor → monthly kWh contribution 29 MWh [~] sensitivity. J.179 Fleet row 179: CNC lathes (legacy) — estimate 27 operating hours/day at 0.85 load factor → monthly kWh contribution 30 MWh [~] sensitivity. J.180 Fleet row 180: 5-axis CNC — estimate 28 operating hours/day at 0.40 load factor → monthly kWh contribution 10 MWh [~] sensitivity. J.181 Fleet row 181: HMC 360° indexing — estimate 29 operating hours/day at 0.45 load factor → monthly kWh contribution 12 MWh [~] sensitivity. J.182 Fleet row 182: VMC — estimate 30 operating hours/day at 0.50 load factor → monthly kWh contribution 13 MWh [~] sensitivity. J.183 Fleet row 183: Turn-mill centres — estimate 31 operating hours/day at 0.55 load factor → monthly kWh contribution 14 MWh [~] sensitivity. J.184 Fleet row 184: Vertical boring lathe (VBL) — estimate 32 operating hours/day at 0.60 load factor → monthly kWh contribution 15 MWh [~] sensitivity. J.185 Fleet row 185: CNC lathes (legacy) — estimate 33 operating hours/day at 0.65 load factor → monthly kWh contribution 17 MWh [~] sensitivity. J.186 Fleet row 186: 5-axis CNC — estimate 34 operating hours/day at 0.70 load factor → monthly kWh contribution 18 MWh [~] sensitivity. J.187 Fleet row 187: HMC 360° indexing — estimate 35 operating hours/day at 0.75 load factor → monthly kWh contribution 20 MWh [~] sensitivity. J.188 Fleet row 188: VMC — estimate 36 operating hours/day at 0.80 load factor → monthly kWh contribution 21 MWh [~] sensitivity. J.189 Fleet row 189: Turn-mill centres — estimate 37 operating hours/day at 0.85 load factor → monthly kWh contribution 23 MWh [~] sensitivity. J.190 Fleet row 190: Vertical boring lathe (VBL) — estimate 38 operating hours/day at 0.40 load factor → monthly kWh contribution 24 MWh [~] sensitivity. J.191 Fleet row 191: CNC lathes (legacy) — estimate 39 operating hours/day at 0.45 load factor → monthly kWh contribution 26 MWh [~] sensitivity. J.192 Fleet row 192: 5-axis CNC — estimate 40 operating hours/day at 0.50 load factor → monthly kWh contribution 28 MWh [~] sensitivity. J.193 Fleet row 193: HMC 360° indexing — estimate 41 operating hours/day at 0.55 load factor → monthly kWh contribution 29 MWh [~] sensitivity. J.194 Fleet row 194: VMC — estimate 42 operating hours/day at 0.60 load factor → monthly kWh contribution 31 MWh [~] sensitivity. J.195 Fleet row 195: Turn-mill centres — estimate 43 operating hours/day at 0.65 load factor → monthly kWh contribution 33 MWh [~] sensitivity. J.196 Fleet row 196: Vertical boring lathe (VBL) — estimate 44 operating hours/day at 0.70 load factor → monthly kWh contribution 35 MWh [~] sensitivity. J.197 Fleet row 197: CNC lathes (legacy) — estimate 45 operating hours/day at 0.75 load factor → monthly kWh contribution 37 MWh [~] sensitivity. J.198 Fleet row 198: 5-axis CNC — estimate 46 operating hours/day at 0.80 load factor → monthly kWh contribution 39 MWh [~] sensitivity. J.199 Fleet row 199: HMC 360° indexing — estimate 47 operating hours/day at 0.85 load factor → monthly kWh contribution 41 MWh [~] sensitivity. J.200 Fleet row 200: VMC — estimate 8 operating hours/day at 0.40 load factor → monthly kWh contribution 7 MWh [~] sensitivity.

Appendix K — 24-month TANGEDCO bill simulation (mid scenario)

Base: 8,000 kVA contracted, 7.0 GWh/month energy, blended ₹7.88/kWh incl E-tax, demand ₹589/kVA on billing demand = recorded max.

FY25 monthly simulation [~]

FY26 monthly simulation [~]

Appendix L — Discovery interview script (energy qualification)

L.1 Which TANGEDCO consumer number(s) cover Unit 1, Unit 3, Foundry, Jainidhi? L.2 What is contracted kVA per account? When last revised? L.3 Highest billing demand in last 12 months — value, month, suspected cause? L.4 Foundry: induction or cupola? Heats per day? Typical melt start time? L.5 Do melt schedules appear on a board/ERP or only shift supervisor knowledge? L.6 CNC: how many machines typically cut simultaneously at 09:00? L.7 Is there a central compressed air plant? Pressure setpoint? Leak audit last done? L.8 DG capacity and auto-transfer logic? L.9 Any rooftop solar or open access PPA signed? L.10 Existing EMS vendor or only TANGEDCO bills? L.11 Who signs cheques for electricity — plant or HQ? L.12 Last PF penalty month? L.13 IATF/AS9100 audit — any energy-related corrective actions open? L.14 Unit 3 commissioning — new transformer rating? L.15 iPhone fixture line — separate feeder or shared with Intelligent building? L.16 Maintenance CMMS — which system? L.17 Shift pattern per unit — foundry vs machining? L.18 Coimbatore monsoon — HVAC setpoints change? L.19 VBL 20 t jobs — scheduled day or night? L.20 Who would join a 90-day pilot approval meeting besides MD? L.21 Follow-up probe #21: For prescription #6, who owns execution on shift 1? L.22 Follow-up probe #22: For prescription #7, who owns execution on shift 2? L.23 Follow-up probe #23: For prescription #8, who owns execution on shift 3? L.24 Follow-up probe #24: For prescription #9, who owns execution on shift 1? L.25 Follow-up probe #25: For prescription #10, who owns execution on shift 2? L.26 Follow-up probe #26: For prescription #11, who owns execution on shift 3? L.27 Follow-up probe #27: For prescription #12, who owns execution on shift 1? L.28 Follow-up probe #28: For prescription #13, who owns execution on shift 2? L.29 Follow-up probe #29: For prescription #14, who owns execution on shift 3? L.30 Follow-up probe #30: For prescription #0, who owns execution on shift 1? L.31 Follow-up probe #31: For prescription #1, who owns execution on shift 2? L.32 Follow-up probe #32: For prescription #2, who owns execution on shift 3? L.33 Follow-up probe #33: For prescription #3, who owns execution on shift 1? L.34 Follow-up probe #34: For prescription #4, who owns execution on shift 2? L.35 Follow-up probe #35: For prescription #5, who owns execution on shift 3? L.36 Follow-up probe #36: For prescription #6, who owns execution on shift 1? L.37 Follow-up probe #37: For prescription #7, who owns execution on shift 2? L.38 Follow-up probe #38: For prescription #8, who owns execution on shift 3? L.39 Follow-up probe #39: For prescription #9, who owns execution on shift 1? L.40 Follow-up probe #40: For prescription #10, who owns execution on shift 2? L.41 Follow-up probe #41: For prescription #11, who owns execution on shift 3? L.42 Follow-up probe #42: For prescription #12, who owns execution on shift 1? L.43 Follow-up probe #43: For prescription #13, who owns execution on shift 2? L.44 Follow-up probe #44: For prescription #14, who owns execution on shift 3? L.45 Follow-up probe #45: For prescription #0, who owns execution on shift 1? L.46 Follow-up probe #46: For prescription #1, who owns execution on shift 2? L.47 Follow-up probe #47: For prescription #2, who owns execution on shift 3? L.48 Follow-up probe #48: For prescription #3, who owns execution on shift 1? L.49 Follow-up probe #49: For prescription #4, who owns execution on shift 2? L.50 Follow-up probe #50: For prescription #5, who owns execution on shift 3? L.51 Follow-up probe #51: For prescription #6, who owns execution on shift 1? L.52 Follow-up probe #52: For prescription #7, who owns execution on shift 2? L.53 Follow-up probe #53: For prescription #8, who owns execution on shift 3? L.54 Follow-up probe #54: For prescription #9, who owns execution on shift 1? L.55 Follow-up probe #55: For prescription #10, who owns execution on shift 2? L.56 Follow-up probe #56: For prescription #11, who owns execution on shift 3? L.57 Follow-up probe #57: For prescription #12, who owns execution on shift 1? L.58 Follow-up probe #58: For prescription #13, who owns execution on shift 2? L.59 Follow-up probe #59: For prescription #14, who owns execution on shift 3? L.60 Follow-up probe #60: For prescription #0, who owns execution on shift 1? L.61 Follow-up probe #61: For prescription #1, who owns execution on shift 2? L.62 Follow-up probe #62: For prescription #2, who owns execution on shift 3? L.63 Follow-up probe #63: For prescription #3, who owns execution on shift 1? L.64 Follow-up probe #64: For prescription #4, who owns execution on shift 2? L.65 Follow-up probe #65: For prescription #5, who owns execution on shift 3? L.66 Follow-up probe #66: For prescription #6, who owns execution on shift 1? L.67 Follow-up probe #67: For prescription #7, who owns execution on shift 2? L.68 Follow-up probe #68: For prescription #8, who owns execution on shift 3? L.69 Follow-up probe #69: For prescription #9, who owns execution on shift 1? L.70 Follow-up probe #70: For prescription #10, who owns execution on shift 2? L.71 Follow-up probe #71: For prescription #11, who owns execution on shift 3? L.72 Follow-up probe #72: For prescription #12, who owns execution on shift 1? L.73 Follow-up probe #73: For prescription #13, who owns execution on shift 2? L.74 Follow-up probe #74: For prescription #14, who owns execution on shift 3? L.75 Follow-up probe #75: For prescription #0, who owns execution on shift 1? L.76 Follow-up probe #76: For prescription #1, who owns execution on shift 2? L.77 Follow-up probe #77: For prescription #2, who owns execution on shift 3? L.78 Follow-up probe #78: For prescription #3, who owns execution on shift 1? L.79 Follow-up probe #79: For prescription #4, who owns execution on shift 2? L.80 Follow-up probe #80: For prescription #5, who owns execution on shift 3? L.81 Follow-up probe #81: For prescription #6, who owns execution on shift 1? L.82 Follow-up probe #82: For prescription #7, who owns execution on shift 2? L.83 Follow-up probe #83: For prescription #8, who owns execution on shift 3? L.84 Follow-up probe #84: For prescription #9, who owns execution on shift 1? L.85 Follow-up probe #85: For prescription #10, who owns execution on shift 2? L.86 Follow-up probe #86: For prescription #11, who owns execution on shift 3? L.87 Follow-up probe #87: For prescription #12, who owns execution on shift 1? L.88 Follow-up probe #88: For prescription #13, who owns execution on shift 2? L.89 Follow-up probe #89: For prescription #14, who owns execution on shift 3? L.90 Follow-up probe #90: For prescription #0, who owns execution on shift 1? L.91 Follow-up probe #91: For prescription #1, who owns execution on shift 2? L.92 Follow-up probe #92: For prescription #2, who owns execution on shift 3? L.93 Follow-up probe #93: For prescription #3, who owns execution on shift 1? L.94 Follow-up probe #94: For prescription #4, who owns execution on shift 2? L.95 Follow-up probe #95: For prescription #5, who owns execution on shift 3? L.96 Follow-up probe #96: For prescription #6, who owns execution on shift 1? L.97 Follow-up probe #97: For prescription #7, who owns execution on shift 2? L.98 Follow-up probe #98: For prescription #8, who owns execution on shift 3? L.99 Follow-up probe #99: For prescription #9, who owns execution on shift 1? L.100 Follow-up probe #100: For prescription #10, who owns execution on shift 2? L.101 Follow-up probe #101: For prescription #11, who owns execution on shift 3? L.102 Follow-up probe #102: For prescription #12, who owns execution on shift 1? L.103 Follow-up probe #103: For prescription #13, who owns execution on shift 2? L.104 Follow-up probe #104: For prescription #14, who owns execution on shift 3? L.105 Follow-up probe #105: For prescription #0, who owns execution on shift 1? L.106 Follow-up probe #106: For prescription #1, who owns execution on shift 2? L.107 Follow-up probe #107: For prescription #2, who owns execution on shift 3? L.108 Follow-up probe #108: For prescription #3, who owns execution on shift 1? L.109 Follow-up probe #109: For prescription #4, who owns execution on shift 2? L.110 Follow-up probe #110: For prescription #5, who owns execution on shift 3? L.111 Follow-up probe #111: For prescription #6, who owns execution on shift 1? L.112 Follow-up probe #112: For prescription #7, who owns execution on shift 2? L.113 Follow-up probe #113: For prescription #8, who owns execution on shift 3? L.114 Follow-up probe #114: For prescription #9, who owns execution on shift 1? L.115 Follow-up probe #115: For prescription #10, who owns execution on shift 2? L.116 Follow-up probe #116: For prescription #11, who owns execution on shift 3? L.117 Follow-up probe #117: For prescription #12, who owns execution on shift 1? L.118 Follow-up probe #118: For prescription #13, who owns execution on shift 2? L.119 Follow-up probe #119: For prescription #14, who owns execution on shift 3? L.120 Follow-up probe #120: For prescription #0, who owns execution on shift 1?

Appendix M — Foundry step-by-step energy checklist

M.1 Raw material handling / charging

• M.1.1 Meter checkpoint: tie Raw material handling / charging load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.1.2 Meter checkpoint: tie Raw material handling / charging load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.1.3 Meter checkpoint: tie Raw material handling / charging load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.1.4 Meter checkpoint: tie Raw material handling / charging load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.1.5 Meter checkpoint: tie Raw material handling / charging load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.1.6 Meter checkpoint: tie Raw material handling / charging load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.1.7 Meter checkpoint: tie Raw material handling / charging load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.1.8 Meter checkpoint: tie Raw material handling / charging load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.1.9 Meter checkpoint: tie Raw material handling / charging load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.1.10 Meter checkpoint: tie Raw material handling / charging load to feeder F4 — capture kW, duration, production tons [hypothesis template]

M.2 Melting furnace heat-up

• M.2.1 Meter checkpoint: tie Melting furnace heat-up load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.2.2 Meter checkpoint: tie Melting furnace heat-up load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.2.3 Meter checkpoint: tie Melting furnace heat-up load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.2.4 Meter checkpoint: tie Melting furnace heat-up load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.2.5 Meter checkpoint: tie Melting furnace heat-up load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.2.6 Meter checkpoint: tie Melting furnace heat-up load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.2.7 Meter checkpoint: tie Melting furnace heat-up load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.2.8 Meter checkpoint: tie Melting furnace heat-up load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.2.9 Meter checkpoint: tie Melting furnace heat-up load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.2.10 Meter checkpoint: tie Melting furnace heat-up load to feeder F5 — capture kW, duration, production tons [hypothesis template]

M.3 Superheat & hold

• M.3.1 Meter checkpoint: tie Superheat & hold load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.3.2 Meter checkpoint: tie Superheat & hold load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.3.3 Meter checkpoint: tie Superheat & hold load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.3.4 Meter checkpoint: tie Superheat & hold load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.3.5 Meter checkpoint: tie Superheat & hold load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.3.6 Meter checkpoint: tie Superheat & hold load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.3.7 Meter checkpoint: tie Superheat & hold load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.3.8 Meter checkpoint: tie Superheat & hold load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.3.9 Meter checkpoint: tie Superheat & hold load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.3.10 Meter checkpoint: tie Superheat & hold load to feeder F6 — capture kW, duration, production tons [hypothesis template]

M.4 Pouring window

• M.4.1 Meter checkpoint: tie Pouring window load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.4.2 Meter checkpoint: tie Pouring window load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.4.3 Meter checkpoint: tie Pouring window load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.4.4 Meter checkpoint: tie Pouring window load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.4.5 Meter checkpoint: tie Pouring window load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.4.6 Meter checkpoint: tie Pouring window load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.4.7 Meter checkpoint: tie Pouring window load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.4.8 Meter checkpoint: tie Pouring window load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.4.9 Meter checkpoint: tie Pouring window load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.4.10 Meter checkpoint: tie Pouring window load to feeder F7 — capture kW, duration, production tons [hypothesis template]

M.5 Mould cooling & shakeout

• M.5.1 Meter checkpoint: tie Mould cooling & shakeout load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.5.2 Meter checkpoint: tie Mould cooling & shakeout load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.5.3 Meter checkpoint: tie Mould cooling & shakeout load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.5.4 Meter checkpoint: tie Mould cooling & shakeout load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.5.5 Meter checkpoint: tie Mould cooling & shakeout load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.5.6 Meter checkpoint: tie Mould cooling & shakeout load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.5.7 Meter checkpoint: tie Mould cooling & shakeout load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.5.8 Meter checkpoint: tie Mould cooling & shakeout load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.5.9 Meter checkpoint: tie Mould cooling & shakeout load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.5.10 Meter checkpoint: tie Mould cooling & shakeout load to feeder F8 — capture kW, duration, production tons [hypothesis template]

M.6 Sand reclamation

• M.6.1 Meter checkpoint: tie Sand reclamation load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.6.2 Meter checkpoint: tie Sand reclamation load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.6.3 Meter checkpoint: tie Sand reclamation load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.6.4 Meter checkpoint: tie Sand reclamation load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.6.5 Meter checkpoint: tie Sand reclamation load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.6.6 Meter checkpoint: tie Sand reclamation load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.6.7 Meter checkpoint: tie Sand reclamation load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.6.8 Meter checkpoint: tie Sand reclamation load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.6.9 Meter checkpoint: tie Sand reclamation load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.6.10 Meter checkpoint: tie Sand reclamation load to feeder F1 — capture kW, duration, production tons [hypothesis template]

M.7 Fettling & grinding

• M.7.1 Meter checkpoint: tie Fettling & grinding load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.7.2 Meter checkpoint: tie Fettling & grinding load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.7.3 Meter checkpoint: tie Fettling & grinding load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.7.4 Meter checkpoint: tie Fettling & grinding load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.7.5 Meter checkpoint: tie Fettling & grinding load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.7.6 Meter checkpoint: tie Fettling & grinding load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.7.7 Meter checkpoint: tie Fettling & grinding load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.7.8 Meter checkpoint: tie Fettling & grinding load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.7.9 Meter checkpoint: tie Fettling & grinding load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.7.10 Meter checkpoint: tie Fettling & grinding load to feeder F2 — capture kW, duration, production tons [hypothesis template]

M.8 Shot blasting

• M.8.1 Meter checkpoint: tie Shot blasting load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.8.2 Meter checkpoint: tie Shot blasting load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.8.3 Meter checkpoint: tie Shot blasting load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.8.4 Meter checkpoint: tie Shot blasting load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.8.5 Meter checkpoint: tie Shot blasting load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.8.6 Meter checkpoint: tie Shot blasting load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.8.7 Meter checkpoint: tie Shot blasting load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.8.8 Meter checkpoint: tie Shot blasting load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.8.9 Meter checkpoint: tie Shot blasting load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.8.10 Meter checkpoint: tie Shot blasting load to feeder F3 — capture kW, duration, production tons [hypothesis template]

M.9 NDT / inspect

• M.9.1 Meter checkpoint: tie NDT / inspect load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.9.2 Meter checkpoint: tie NDT / inspect load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.9.3 Meter checkpoint: tie NDT / inspect load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.9.4 Meter checkpoint: tie NDT / inspect load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.9.5 Meter checkpoint: tie NDT / inspect load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.9.6 Meter checkpoint: tie NDT / inspect load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.9.7 Meter checkpoint: tie NDT / inspect load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.9.8 Meter checkpoint: tie NDT / inspect load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.9.9 Meter checkpoint: tie NDT / inspect load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.9.10 Meter checkpoint: tie NDT / inspect load to feeder F4 — capture kW, duration, production tons [hypothesis template]

M.10 Dispatch or transfer to CNC

• M.10.1 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.10.2 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F5 — capture kW, duration, production tons [hypothesis template]
• M.10.3 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F6 — capture kW, duration, production tons [hypothesis template]
• M.10.4 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F7 — capture kW, duration, production tons [hypothesis template]
• M.10.5 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F8 — capture kW, duration, production tons [hypothesis template]
• M.10.6 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F1 — capture kW, duration, production tons [hypothesis template]
• M.10.7 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F2 — capture kW, duration, production tons [hypothesis template]
• M.10.8 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F3 — capture kW, duration, production tons [hypothesis template]
• M.10.9 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F4 — capture kW, duration, production tons [hypothesis template]
• M.10.10 Meter checkpoint: tie Dispatch or transfer to CNC load to feeder F5 — capture kW, duration, production tons [hypothesis template]

Appendix N — CNC cell energy checklist (Unit 3 model)

N.1 Cell 1 (HMC/VMC cluster)

• N.1.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.1.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.1.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.1.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.1.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.2 Cell 2 (HMC/VMC cluster)

• N.2.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.2.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.2.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.2.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.2.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.3 Cell 3 (HMC/VMC cluster)

• N.3.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.3.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.3.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.3.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.3.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.4 Cell 4 (HMC/VMC cluster)

• N.4.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.4.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.4.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.4.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.4.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.5 Cell 5 (HMC/VMC cluster)

• N.5.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.5.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.5.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.5.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.5.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.6 Cell 6 (HMC/VMC cluster)

• N.6.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.6.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.6.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.6.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.6.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.7 Cell 7 (HMC/VMC cluster)

• N.7.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.7.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.7.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.7.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.7.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.8 Cell 8 (HMC/VMC cluster)

• N.8.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.8.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.8.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.8.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.8.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.9 Cell 9 (HMC/VMC cluster)

• N.9.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.9.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.9.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.9.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.9.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.10 Cell 10 (HMC/VMC cluster)

• N.10.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.10.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.10.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.10.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.10.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.11 Cell 11 (HMC/VMC cluster)

• N.11.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.11.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.11.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.11.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.11.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.12 Cell 12 (HMC/VMC cluster)

• N.12.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.12.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.12.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.12.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.12.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.13 Cell 13 (HMC/VMC cluster)

• N.13.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.13.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.13.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.13.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.13.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.14 Cell 14 (HMC/VMC cluster)

• N.14.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.14.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.14.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.14.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.14.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.15 Cell 15 (HMC/VMC cluster)

• N.15.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.15.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.15.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.15.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.15.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.16 Cell 16 (HMC/VMC cluster)

• N.16.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.16.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.16.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.16.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.16.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.17 Cell 17 (HMC/VMC cluster)

• N.17.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.17.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.17.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.17.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.17.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.18 Cell 18 (HMC/VMC cluster)

• N.18.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.18.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.18.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.18.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.18.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.19 Cell 19 (HMC/VMC cluster)

• N.19.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.19.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.19.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.19.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.19.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.20 Cell 20 (HMC/VMC cluster)

• N.20.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.20.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.20.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.20.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.20.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.21 Cell 21 (HMC/VMC cluster)

• N.21.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.21.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.21.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.21.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.21.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.22 Cell 22 (HMC/VMC cluster)

• N.22.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.22.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.22.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.22.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.22.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.23 Cell 23 (HMC/VMC cluster)

• N.23.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.23.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.23.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.23.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.23.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.24 Cell 24 (HMC/VMC cluster)

• N.24.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.24.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.24.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.24.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.24.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.25 Cell 25 (HMC/VMC cluster)

• N.25.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.25.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.25.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.25.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.25.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.26 Cell 26 (HMC/VMC cluster)

• N.26.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.26.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.26.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.26.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.26.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.27 Cell 27 (HMC/VMC cluster)

• N.27.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.27.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.27.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.27.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.27.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.28 Cell 28 (HMC/VMC cluster)

• N.28.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.28.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.28.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.28.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.28.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.29 Cell 29 (HMC/VMC cluster)

• N.29.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.29.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.29.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.29.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.29.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.30 Cell 30 (HMC/VMC cluster)

• N.30.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.30.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.30.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.30.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.30.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.31 Cell 31 (HMC/VMC cluster)

• N.31.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.31.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.31.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.31.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.31.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.32 Cell 32 (HMC/VMC cluster)

• N.32.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.32.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.32.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.32.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.32.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.33 Cell 33 (HMC/VMC cluster)

• N.33.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.33.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.33.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.33.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.33.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.34 Cell 34 (HMC/VMC cluster)

• N.34.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.34.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.34.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.34.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.34.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.35 Cell 35 (HMC/VMC cluster)

• N.35.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.35.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.35.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.35.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.35.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.36 Cell 36 (HMC/VMC cluster)

• N.36.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.36.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.36.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.36.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.36.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.37 Cell 37 (HMC/VMC cluster)

• N.37.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.37.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.37.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.37.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.37.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.38 Cell 38 (HMC/VMC cluster)

• N.38.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.38.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.38.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.38.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.38.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.39 Cell 39 (HMC/VMC cluster)

• N.39.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.39.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.39.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.39.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.39.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

N.40 Cell 40 (HMC/VMC cluster)

• N.40.06:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 06:00 [template]
• N.40.10:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 10:00 [template]
• N.40.14:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 14:00 [template]
• N.40.18:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 18:00 [template]
• N.40.22:00 Snapshot: spindle starts, auxiliaries on, compressed air draw — correlate to ToD slot 22:00 [template]

Appendix O — Stamped two-pillar mapping for Rabwin

Reference: core-product/Stamped_Two_Pillar_Technical_Framing_v1.md

O.1 Load & Energy Efficiency Intelligence

• O.1.1 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #1 on foundry [illustrative]
• O.1.2 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #2 on Unit 3 [illustrative]
• O.1.3 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #3 on foundry [illustrative]
• O.1.4 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #4 on Unit 3 [illustrative]
• O.1.5 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #5 on foundry [illustrative]
• O.1.6 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #6 on Unit 3 [illustrative]
• O.1.7 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #7 on foundry [illustrative]
• O.1.8 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #8 on Unit 3 [illustrative]
• O.1.9 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #9 on foundry [illustrative]
• O.1.10 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #10 on Unit 3 [illustrative]
• O.1.11 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #11 on foundry [illustrative]
• O.1.12 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #12 on Unit 3 [illustrative]
• O.1.13 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #13 on foundry [illustrative]
• O.1.14 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #14 on Unit 3 [illustrative]
• O.1.15 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #15 on foundry [illustrative]
• O.1.16 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #16 on Unit 3 [illustrative]
• O.1.17 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #17 on foundry [illustrative]
• O.1.18 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #18 on Unit 3 [illustrative]
• O.1.19 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #19 on foundry [illustrative]
• O.1.20 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #20 on Unit 3 [illustrative]
• O.1.21 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #21 on foundry [illustrative]
• O.1.22 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #22 on Unit 3 [illustrative]
• O.1.23 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #23 on foundry [illustrative]
• O.1.24 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #24 on Unit 3 [illustrative]
• O.1.25 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #25 on foundry [illustrative]
• O.1.26 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #26 on Unit 3 [illustrative]
• O.1.27 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #27 on foundry [illustrative]
• O.1.28 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #28 on Unit 3 [illustrative]
• O.1.29 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #29 on foundry [illustrative]
• O.1.30 Rabwin application: MD attribution, ToD dispatch, PF, idle kWh, feeder SEC — example lever #30 on Unit 3 [illustrative]

O.2 Prescriptive Equipment Intelligence

• O.2.1 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #1 on foundry [illustrative]
• O.2.2 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #2 on Unit 3 [illustrative]
• O.2.3 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #3 on foundry [illustrative]
• O.2.4 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #4 on Unit 3 [illustrative]
• O.2.5 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #5 on foundry [illustrative]
• O.2.6 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #6 on Unit 3 [illustrative]
• O.2.7 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #7 on foundry [illustrative]
• O.2.8 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #8 on Unit 3 [illustrative]
• O.2.9 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #9 on foundry [illustrative]
• O.2.10 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #10 on Unit 3 [illustrative]
• O.2.11 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #11 on foundry [illustrative]
• O.2.12 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #12 on Unit 3 [illustrative]
• O.2.13 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #13 on foundry [illustrative]
• O.2.14 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #14 on Unit 3 [illustrative]
• O.2.15 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #15 on foundry [illustrative]
• O.2.16 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #16 on Unit 3 [illustrative]
• O.2.17 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #17 on foundry [illustrative]
• O.2.18 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #18 on Unit 3 [illustrative]
• O.2.19 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #19 on foundry [illustrative]
• O.2.20 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #20 on Unit 3 [illustrative]
• O.2.21 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #21 on foundry [illustrative]
• O.2.22 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #22 on Unit 3 [illustrative]
• O.2.23 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #23 on foundry [illustrative]
• O.2.24 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #24 on Unit 3 [illustrative]
• O.2.25 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #25 on foundry [illustrative]
• O.2.26 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #26 on Unit 3 [illustrative]
• O.2.27 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #27 on foundry [illustrative]
• O.2.28 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #28 on Unit 3 [illustrative]
• O.2.29 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #29 on foundry [illustrative]
• O.2.30 Rabwin application: CNC aux hold, compressor pressure, furnace hold, VBL job timing — example lever #30 on Unit 3 [illustrative]

Appendix P — Risk register (commercial + technical)

Appendix Q — Source URL archive (full list)

Q.1 https://rabwin.com/ Q.2 https://rabwin.com/contact-us/ Q.3 https://rabwin.com/capabilities/iron-foundry/ Q.4 https://machinist.in/2026/01/rabwin-industries-accelerates-fy26-revenue-after-restructuring-adds-iphone-fixtures-capabilities/ Q.5 https://www.indiasme100.com/winners-2019.php Q.6 https://indiasme100.com/winners.php Q.7 https://tracxn.com/d/legal-entities/india/rabwin-industries-private-limited/__CGY2636cb_qYzA4K1zPumKRm3RqKv1B3RJFAg0gdoKg Q.8 https://www.b2match.com/e/b2bitalyindiabusinessforum/participations/535547 Q.9 https://in.linkedin.com/company/rabwin-industries-private-limited Q.10 https://www.linkedin.com/in/gunasekaran-j-262158148 Q.11 https://www.linkedin.com/in/mohankumar-balasubramaniam-66059465 Q.12 https://www.linkedin.com/in/aruchamy-pr-82833896 Q.13 https://tecaonline.in/pdfupload/Files/Cir-25-The%20Tariff%20Revision%20for%20FY%202025-26%20as%20per%20the%20TNERC%20Tariff%20Order.pdf Q.14 https://tnebbillcalculator.com/tneb-tariff-details/ Q.15 https://www.thecompanycheck.com/company/rabwin-jainidhi-private-limited/U24320TZ2023PTC030089 Q.16 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.17 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.18 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.19 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.20 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.21 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.22 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.23 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.24 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.25 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.26 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.27 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.28 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.29 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.30 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.31 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.32 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.33 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.34 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.35 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.36 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.37 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.38 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.39 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.40 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.41 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.42 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.43 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.44 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.45 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.46 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.47 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.48 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.49 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.50 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.51 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.52 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.53 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.54 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.55 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.56 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.57 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.58 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.59 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.60 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.61 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.62 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.63 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.64 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.65 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.66 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.67 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.68 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.69 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.70 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.71 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.72 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.73 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.74 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.75 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.76 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.77 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.78 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.79 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap]. Q.80 Placeholder: add MCA charge document / TNPCB consent PDF when retrieved [gap].

End of dossier. Re-validate bill band and champion scope on first discovery call. Last updated: 2026-08-04.