PlantOS™ Case Study · Vedanta Group
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• Metals & Mining
• Vedanta Group
• Data as of Jan 2026
PLANT RELIABILITY.
Equipment Faults + Process Anomalies
Vedanta Group — a leading global producer of zinc, aluminium, copper, iron ore, oil & gas, power, and steel — didn’t just digitize its plants. It closed the loop: from raw sensor signal to prescribed action to user-validated production outcome. And in five years, it scaled from 350 sensors at a single Jharsuguda pilot to enterprise-wide prescriptive reliability across 77 plant sites worldwide. Here’s what closing the loop at Vedanta scale looks like.
Read the Full Transformation
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PlantOS™ Prescriptive AI.
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3 outcomes in 1 prescription — zero guesswork.
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0
Hrs Downtime
Eliminated User-validated. Across 77 plants.
0
Prescriptions
Acted Upon At 83.64% user-validation rate
0
%
Prediction Accuracy Across 489 areas,
9,055 critical equipment
$
0
k
USD Production
Savings At HZL mines & smelters. Validated.
All figures validated by Vedanta Group’s Reliability & Operations teams via PlantOS™ Prescription Engine
What’s inside
FROM NOISE
TO OUTCOMES.
Mechanical Faults
Vibration, wear &
bearing degradation
Physics + AI models detect gearbox bearing defects, pinion-to-girth gear misalignment, and structural looseness across Ball Mills, Potline Belt Conveyors, and Vibrating Screens before they cascade into unplanned downtime — protecting throughput across mining, smelting, and metals operations.
Electrical Faults
Motor overheating &
drive anomalies
Temperature and vibration trend analysis at fan DE and NDE bearings surfaces inadequate lubrication conditions and load imbalances before they trip critical Potline ID Fans, FRP fans, and Rodding line drives.
Process Induced Faults
Parameter drift &
production deviation
Continuous 24×7 condition monitoring — combining advanced MEMS and piezoelectric sensing — across Ball Mill circuits, Cast House equipment, and Conveyor Belts & Rollers detects process shifts before they impact yield or energy efficiency, and before they reach the next stage.
01
489 areas. 9,055 critical equipment. One Single Source of Truth.
How Vedanta scaled from 350 sensors at VAL Jharsuguda in 2021 to 26,341 monitoring locations across 77 plant sites worldwide — unifying Vedanta Aluminium, Hindustan Zinc, and Sesa Goa operations across Potlines, Ball Mills, Vibrating Screens, Rodding lines, and Cast Houses into a single contextualized source of truth.
02
Physics + AI: precision that predictions can’t match
PlantOS™ doesn’t flag anomalies. It traces root cause — across mechanical, electrical, and process domains — with 99.98% accuracy. Advanced MEMS and piezoelectric sensing combined with domain experts who review and validate every prescription — precision that built confidence across Vedanta’s reliability leadership.
03
Diagnostic → Recommendation → Action
1,554 prescriptions acted upon at an 83.64% user-validation rate. Digital workflows and remote diagnostics reduced manual inspections in hazardous areas and accelerated work order execution — not dashboards, not alerts. Work orders that close.
04
Outcomes the plant’s own operators signed off on
5,039 hours of unplanned downtime eliminated. 5,206 hrs MTBF achieved over the last 12 months. >$700K USD in production savings at HZL across mines & smelters. Higher availability across Potlines and Ball Mills. All figures validated by Vedanta’s own Reliability & Operations teams.
Prediction
≠
Outcomes.
Most AI deployments stop at the alert. They predict. They visualize. They dashboard. But prediction without a closed loop is just a more expensive alarm bell.
Vedanta’s deployment with PlantOS™ proves the gap isn’t in the model — it’s in the mile between insight and action. The 99% Trust Loop™ is what bridges it. And at Vedanta scale — 77 plants, 9,055 critical equipment, 26,341 monitoring locations across the global portfolio — the results don’t just compound. They scale from local initiative to group strategy.
The 99% Trust Loop™ — how outcomes are guaranteed
1.
Contextualize equipment + process
489 areas, 9,055 critical equipment, 77 plants — One Prescriptive AI platform.
2.
Detect with physics-based precision
Mechanical, electrical, and process anomalies — not noise. 99.98% accuracy. Just 3 missed faults across 26,341 monitoring locations.
3.
Prescribe exact corrective action
1,554 prescriptions. 83.64% user-validation rate. Diagnostic → Recommendation → Action.
4.
Validate outcomes. Close the loop.
Engineers validate results in PlantOS™ Digital Reporting.
Reliability
Availability
Energy Efficiency
3 Guaranteed Outcomes. 0 Guesswork.
Since partnering with Infinite Uptime, we’ve seen a significant boost in plant availability and reliability. The ability to detect issues early has not only helped us avoid costly downtime but also built confidence in our operations. With these results, we’re now moving into phase two — nearly doubling our sensor coverage to monitor the entire plant.
Mr. Gaurang Kamat
Head Engineering, Sesa Goa, Vedanta Group, India
Full Transformation Story
GET THE COMPLETE PICTURE.
The numbers above are the headline. The full story reveals the real challenges Vedanta faced — FY21–22 breakdowns in Potlines and Ball Mills at flagship sites like VAL Jharsuguda, high maintenance costs, safety risks from intensive man–machine interaction in hazardous areas — and exactly how PlantOS™ flipped the script, scaling from 350 sensors at one plant to 26,341 monitoring locations across 77 sites and transforming reliability from a local initiative into group strategy.
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Real PlantOS™ Diagnostic Reports from live Vedanta deployments — HZL Ball Mill R4, Potline FRP ID Fans
✔
Equipment-level fault detection across mechanical, electrical & process domains
✔
The 99% Trust Loop™ framework — step by step
✔
User-validated outcome data, confirmed by Vedanta’s Reliability & Operations team.
Download the Full Transformation Story
Infinite Uptime · 946 plants · 26 countries · Production Outcomes. Delivered.
Thank you for your interest in
PlantOS™ Prescriptive AI.
Enter your official work email to unlock specs delivering
3 outcomes in 1 prescription — zero guesswork.
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