PLANT RELIABILITY.
Equipment Faults + Process Anomalies
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PlantOS™ Prescriptive AI.
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3 outcomes in 1 prescription — zero guesswork.
Eliminated
1,407 critical equipment
82 plants. India.
FROM NOISE
TO OUTCOMES.
Mechanical Faults
Vibration, wear
& bearing degradation
Physics + AI models detect bearing defects at fan DE and NDE locations, ball mill anomalies, and conveyor motor degradation across Pellet Plants, Blast Furnace Dedusting & Blower Fans, and Condenser Water Pumps before they cascade into unplanned downtime.
Electrical Faults
Motor overheating
& drive anomalies
Temperature and vibration trend analysis at motor DE and NDE bearings surfaces inadequate lubrication conditions, base bolt looseness, and load imbalances before they trip Blast Furnace ID Fans or Steam Exhaust Fans across the Steel Melting Shop.
Process Induced Faults
Parameter drift
& production deviation
Continuous 24×7 condition monitoring — capturing data every 2–7 seconds via wired sensing — across Continuous Casting, Hot Strip Mill, and Cold Rolling Mill detects process shifts before they impact yield, and before they reach the next stage.
208 areas. 1,407 critical equipment. One Single Source of Truth.
How Tata Steel scaled from 300 wired sensors at Meramandali in 2021 to 5,721 monitoring locations across 82 plants — unifying Blast Furnaces, Pellet Plants, Steel Melting Shops, and Hot Strip & Cold Rolling Mills into a single contextualized source of truth.
Contextualization layerPhysics + AI: precision that predictions can't match
PlantOS™ doesn't flag anomalies. It traces root cause — across mechanical, electrical, and process domains — with 99.44% accuracy. Continuous wired sensing captures data every 2–7 seconds, against every 6–7 hours for battery-operated devices — the precision that built trust across production and reliability leadership.
Intelligence layerDiagnostic → Recommendation → Action
2,408 prescriptions executed at a 91.48% implementation rate. 3,567 breakdowns avoided. Digital work orders and automated AI-powered insights improved execution speed, reduced manual effort, and strengthened reliability-driven decision-making — not dashboards, not alerts. Work orders that close.
Prescriptive engineOutcomes the plant's own operators signed off on
17,811 hours of unplanned downtime eliminated. 7,386 hrs MTBF achieved over the last 12 months. 3,567 breakdowns avoided. A digital reliability culture strengthened across 82 plants. All figures validated by Tata Steel's own Reliability & Operations teams.
Validated outcomesPrediction
≠
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.
Tata Steel’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 Tata scale — 82 plants, 1,407 critical equipment, 5,721 monitoring locations — the results don’t just compound. They scale.
We avoided close to three-to-four months of outage by detecting component wear early and replacing it in just three days. This first instance showed our team the power of equipment communicating directly, sparking the creation of our success story.
Mr. Amit Khanna
Vice President Business Excellence, Tata Steel
GET THE COMPLETE PICTURE.
Real PlantOS™ Diagnostic Reports from live Tata Steel deployments — Caster Steam Exhaust Fans, Blast Furnace 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 Tata Steel's Reliability & Operations team.
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.
