Board Presentation · Cement Industry · Confidential 1 / 12
Board Presentation · Cement Industry · Confidential

What your
reports don't
show you.

A conversation about the gap between what boards see and what is actually happening inside their cement plants — and what it has been costing every month it remains invisible.

Industry witness · Present in this room
Devi Prasad Vuriti
Nearly four decades in cement, power & fertilizer industries · Now with SkyEdgeAI
Pioneered waste heat recovery in the Indian cement sector
Six Sigma Master Black Belt · Certified Energy Manager · Boiler Operation Engineer
Process Engineering, BITS Pilani · Greenfield and brownfield projects across India and international markets
Recognised for sustainability and operational excellence contributions
Note to audience
Devi Prasad Vuriti has spoken for the past five minutes — without slides — about what four decades inside this industry has shown him. What follows is the evidence that supports what he just said.
The Gap
Two views of the same plant.

Every board in this industry receives the left column. Here is what is actually in the right column.

What your board report shows
What is actually happening
MaintenanceBudget variance 12–18% over plan. Attributed to unplanned equipment failures and emergency procurement.
→
67% of those failures are the same fault repaired again. Root cause identified in sensor data. No corrective action was ever closed. The plant will pay for this repair again in 4–6 months.
EnergySpecific energy within 3–5% of benchmark. Month-on-month variation attributed to raw material quality and operating conditions.
→
Kiln seal degradation has been adding ₹5–8 crore in excess fuel annually. No alarm has ever fired. The loss appears as 'operating conditions' in the variance report.
SafetyZero lost-time injuries this quarter. Safety management system in place. Contractor inductions completed.
→
40% of process industry incidents occur during shift handover — which accounts for less than 5% of operating time. Your plant has three handovers every day. There is no structured evidence that safety-critical information was transferred.
Digital ProgrammeIoT sensors deployed, dashboards live, ₹8–15 crore invested. Digital transformation programme underway.
→
Data exists. Systems are not connected. No governed evidence trail. Your board is not receiving structured metrics on whether the programme is working. The ERP integration is still incomplete.

Sources: Oxmaint · iFactory · imubit · AFPM · CMA India · Shree Cement CIO industry panel 2024

Moment 01 · From a documented plant case
The data knew
18 days before
the failure.

The vibration signature had been deteriorating for 18 days. Bearing cage defect frequency climbing steadily. Temperature rising from 52°C to 68°C. The plant had quarterly manual inspections. Nobody saw it. The catastrophic failure halted the plant's only grinding line for 72 hours.

Day 1 — Early defect signature present. Vibration at 1.2 mm/s. Within detectable range. No inspection due.
Day 9 — Frequency doubling. Temperature trend clear at 61°C. Quarterly manual inspection not due for 6 more weeks.
Day 14 — Beyond actionable threshold. 4.8 mm/s, 68°C. No work order exists. No system has connected the signal to a decision.
Day 18 — Catastrophic failure. Emergency shutdown. 72 hours lost. Plant's only grinding line stopped.
Total event cost
₹2.8 Cr
₹55L emergency parts · ₹18L expedited freight · ₹2.1Cr production loss
Planned repair cost
₹38L
If caught on Day 1 · Planned window · Standard parts · No production loss
The data knew 18 days before the failure. The connection between the data and the decision was missing.
Moment 02 · Every shift, every plant, every day
Three times a day, the plant's performance changes with the operator.

One shift runs the kiln conservatively. The next pushes harder. Both approaches cost money. The incoming operator cannot assess — in the first few minutes — what the correct setpoint should be. So they use their instinct. Their experience level. Which varies, every shift, every day.

Experienced operator
710 kcal/kg
Specific heat · Optimal range · Stable burning zone
Less experienced operator
780 kcal/kg
Specific heat · Conservative margins · Higher fuel consumption
The performance gap · Per year · 5,500 TPD line
₹4.8 Cr
Annual fuel cost difference between optimal and conservative kiln operation. Documented post-AI deployment. No new equipment. Same kiln. Different information quality.
3× daily · Every plant · Everywhere — This happens at every shift change. And 40% of process industry incidents occur in the 5% of operating time called shift handover (AFPM). Your existing APC system optimises the kiln while the experienced operator is in the chair. What happens when they leave and the next operator sits down? That is the gap no existing AI deployment in cement currently closes.

Source: imubit cement AI deployment documentation · AFPM process safety data · Infinity for Cement Equipment kiln control theory

Moment 03 · The question every board will be asked
"Where is the evidence
that this was managed?"

A pressure safety valve had been removed and replaced with a blind flange. The information existed — it was in a logbook. The shift changed. The incoming team was not told. The question the regulator asked after the incident was simple. The answer required four days of manual reconstruction across three systems that did not communicate with each other.

The investigation question · Directed at the board, not just the plant
"What did your AI system recommend? When was the advisory generated? Who reviewed it? What was the operator's decision? Where is the record?"
Most cement plants cannot answer this question from a governed record. Reconstruction after an incident is not the same as proof. Regulators and courts know the difference. If your plant already uses AI for process control or predictive maintenance, this question is more specific — and the governance gap in most existing deployments means the answer does not exist.
Board-level personal exposure · India context
Companies Act 2013 Section 166 — director duty of care; personal liability for material misstatement in sustainability reports
Factories Act — prosecution of occupier and manager for safety system failures; extended to board members in multiple precedents
IFC Performance Standard 2 — for DFI-financed operations: labour and working conditions governance is a lender covenant obligation
MeitY AI Governance Guidelines (January 2025) — accountability and human oversight requirements for AI systems in industrial use
The Cost of the Status Quo · Right Now
₹68.5L
Left your plant today. And yesterday. And every day.

₹25 crore in annual recoverable losses is ₹68.5 lakh per day. ₹2.85 lakh per hour. The board meeting running right now is 90 minutes. ₹4.27 lakh left the plant while you sat here. This is not a future risk. It is a present loss, accumulating continuously.

Where the ₹25 crore comes from
OEE gap — 70% vs 85% industry benchmark₹18–22 Cr
Repeat failures — same fault repaired again₹5–15 Cr
Kiln seal false air — undetected fuel waste₹5–10 Cr
Shutdown overruns — scope found at cooldown₹3–15 Cr
Peak demand tariff — avoidable with load management₹4–16 Cr
If your company has already deployed IoT sensors and dashboards, some of this gap is being partially measured. But measured and recovered are not the same thing. The gap between what your sensors see and what your board recovers is where ₹68.5 lakh per day lives.
In forty years I have never walked into a plant and not found this gap. The question is always the same: does the board know it is there?
The Competitive Cliff
Your competitors
are not waiting.

87% of cement producers globally are prioritising digital initiatives. The plants that moved first are now compounding a cost advantage that grows every quarter. In a commodity market where ₹50–100 per tonne is the entire margin, a permanent cost advantage from full-plant AI deployment is not a competitive nuance — it is an existential gap.

Heidelberg Materials · Mokra plant · Documented first month
4.1% fuel cost reduction · 2% carbon reduction · 33% reduction in C3S variance. ABB + Carbon Re AI integration with existing APC. One month of operation.
Conch Group + Huawei · 2025
Industry's first AI large model for cement — Yungong. 1% coal reduction in kiln combustion optimisation. Awarded by UNIDO as Global Digital Economy solution 2025.
Holcim · Global deployment
AI deployed across 45 plants, scaling to 100. Predictive maintenance, energy optimisation, digital twin integration. Double-digit maintenance disruption reductions at multiple sites.
What this means in Indian cement
A plant at 85% OEE can produce the same volume at 12–15% lower cost per tonne — or 12–15% more volume at the same cost. Either outcome permanently changes the competitive position. Every quarter of delay is a quarter of recoverable losses that compound for the competitor who moved and do not compound for the plant that waited.

Sources: Carbon Re / ABB Heidelberg case Oct 2024 · Huawei Conch MWC Barcelona Mar 2025 · iFactory AI industry data 2025

What Changes · Your world, specifically
Not what SkyEdgeAI does.
What your board meeting looks like after.
For the CFO — Maintenance Accountability
Before
Maintenance budget variance 18% over plan, approved for four years. No attribution. You do not know whether the variance is six recurring faults or sixty random ones. Neither does your maintenance manager — not in a form they can prove.
↓ SkyEdgeAI ↓
After
Your variance report shows ₹3.2 crore of the over-spend is six repeat failure modes — 47 repairs in 18 months. Root causes named. Corrective actions tracked. Regulator answered in 60 seconds.
For the Independent Director — Safety Governance
Before
Zero LTI this quarter. Safety report approved. Three weeks later, a contractor is injured. The investigation asks what safety governance was in place. The answer is a policy document and a training register.
↓ SkyEdgeAI ↓
After
Every confined space entry, every hot work permit, every contractor credential in a governed, timestamped, blockchain-anchored record. The investigation asks. The answer is produced in 60 seconds. The policy document is now evidence, not assertion.
For the AI-Aware Board Member — Digital Programme Accountability
Before
₹8–15 crore invested in digital transformation. Programme approved. IoT tags deployed. Dashboards live. No board-level metrics on performance. Suspected to be drifting. ERP integration incomplete. The board is not receiving structured reports on whether the investment is working.
↓ SkyEdgeAI ↓
After
AI programme performance visible to the board monthly — advisory generation rate, operator acceptance rate, value recovered per plant per month. The programme cannot drift without the board seeing it drift. Your existing sensors and APC are now governed and connected, not fragmented and dark.
For the Chairman — Competitive Position
Before
Plant running at industry-average OEE. Competitors investing in AI. Board receives no comparative performance data. Unable to answer: are we ahead or behind?
↓ SkyEdgeAI ↓
After
Plant at 85% OEE. ₹50–100 per tonne cost advantage over the competitor still at 70%. Defensible position in a margin-thin commodity market. The gap between you and the laggard compounds every quarter in your favour.
The Early Advisory Value Stack
How the platform pays for itself.
Twice. From day one.

Two independent value streams. Both begin from existing data. Neither requires new sensors.

Stack 1 — Equipment failure advisory
1
Signal detected 18 days before failure
Vibration and temperature trend cross-correlated. Advisory generated. Planned work order raised.
Day 1
2
Parts ordered at standard cost
Not 3.2× emergency premium. Scheduled window. Technician arrives with correct tools and spec.
–68%
3
No production loss
Repair in planned window. Line continues. Emergency shutdown eliminated.
₹2.1Cr saved
4
Total: ₹38L instead of ₹2.8 crore
7.4× return on the advisory for this single event. At 12–18 predictable events per plant per year:
7.4×
Platform cost recovered in 60–90 days from equipment advisory alone.
Stack 2 — Shift handover advisory · This value stream does not exist in any existing cement AI deployment
1
AI-generated briefing fires at every shift change
Active advisories, equipment trends, permit status, kiln parameters — compiled in 90 seconds.
3× daily
2
Incoming operator runs at expert performance from minute one
Not after 2 hours of finding their footing. The 710 kcal/kg window, not the 780 kcal/kg default.
70 kcal/kg
3
₹4.8 crore annual energy gap begins closing from day one
No new hardware. No new sensors. No process change. Immediate return from existing DCS data.
₹4.8 Cr/yr
Your existing APC, CMMS, and IoT deployment does not address shift handover. This is the specific gap that SkyEdgeAI closes above every existing deployment.
Why This Will Not Drift
"We have tried things
like this before."

In forty years, improvement initiatives have drifted. Not because the technology failed. Because the people who owned them left, production pressure reasserted, or the board stopped asking about them. Every improvement initiative in this industry has the same vulnerability: it depends on someone staying focused on it.

Documented results · Not projections
5,000 TPD plant — 45% downtime reduction. ₹15 crore Year 1 saving documented.
Reactive maintenance premiums — ₹2.4 crore → ₹65 lakh in year one. 73% reduction.
OEE improvement — 8–12 percentage points in first year for plants with real-time monitoring.
Heidelberg Materials Mokra — 4.1% fuel cost reduction, 2% carbon reduction. First month of operation.
GuardianLedger™ — The permanence mechanism
Every advisory logged. Every operator decision recorded. Every outcome tracked. The improvement creates a record that cannot quietly disappear — because the moment SkyEdgeAI stops generating advisories, the silence is itself a signal visible to the board.
For boards with existing AI deployments: The 25,000 IoT tags are generating data. GuardianLedger is the governed record that makes that data accountable to the board — not just visible on a dashboard that nobody is responsible for maintaining.
Where other platforms stop at capability, SkyEdgeAI adds continuous assurance — the governed evidence record that proves the platform is working, every day, to every stakeholder who asks.
The Valuation Impact
What this does to what the company is worth.
₹150–200 Cr
Enterprise value addition · At 6–8× EBITDA multiple

₹25 crore annual EBITDA improvement, at a 6× multiple, adds ₹150 crore to enterprise value. At 8×, ₹200 crore. The investment required to generate this improvement is a fraction of these figures. The improvement is visible in audited results within 12–18 months of deployment.

For the Institutional Investor
The operational gap between 70% and 85% OEE is a recoverable EBITDA gap. A plant closing this gap is a different asset on the day it closes it than it was the day before. The valuation multiple applies to sustained operational improvement, not to one-time gains.
For the Chairman
A plant running at 85% OEE with a governed, continuous AI platform is a demonstrably more valuable asset than one at 70% OEE with fragmented digital deployments. This is not an improvement programme. It is a permanent revaluation of the asset.
For boards with existing digital investments
Your existing digital transformation investment has already contributed to this valuation trajectory. SkyEdgeAI completes the architecture that existing deployments have partially built — connecting the fragmented systems, governing the ungoverned advisories, and making the improvement visible to the board rather than only to the dashboard.

EBITDA multiple range sourced from Indian cement sector analyst reports 2024–2025 · Valuation improvement modelled on documented deployment outcomes

The Next Step
See your own plant's
numbers. In 30 days.

Everything shown today came from documented plant cases. Not from your plant. Not from your historian. Not from your sensor data. Your historian has been recording everything that has happened in this plant for years. Every bearing temperature trend. Every kiln thermal deviation. Every shift handover gap. Every repeat failure pattern. The data for every loss described today already exists in your systems.

30 days · For the Board & CFO
Plant Loss Audit — Your numbers, from your data
Top 5 documented operational losses in rupees. Sensor evidence for each. Sourced from your own historian and CMMS records. Not industry averages — your plant's specific gap, named and quantified. This document belongs to you regardless of what you decide next.
60 days
For the Operations Director
Operational Gap Map
Asset by asset, shift by shift. The recurring failure modes and shift-to-shift performance variation specific to your plant. Where the ₹68.5 lakh per day is actually coming from, asset by asset.
30 days
For boards with existing AI deployments
Current Deployment Assessment
Mapping your existing IoT, APC, and predictive maintenance deployment against the full platform architecture. Showing exactly where your coverage ends, what the uncovered gap costs annually, and what the governance exposure is in your current system today.
90 days
For DFI Lenders & Investors
Governance Gap Assessment
Structured against IFC Performance Standards, SEBI ESG requirements, MeitY AI Governance Guidelines, and CBAM evidence obligations. What exists, what is missing, what the liability exposure is today.
If it confirms what you have seen today, the conversation about what to do next will answer itself. If your plants are the exception — if the gap does not exist — you will know that, and we will have earned the right to be honest with you about it.
info@skyedge.ai · skyedge.ai · All conversations have no cost and no commitment beyond your time.