PlantOS™ Case Study · MRF
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Tire Manufacturing · MRF · Data as of Jan 2026
PLANT RELIABILITY.
Equipment Faults + Process Anomalies
MRF Tyres — India’s largest tire manufacturer — didn’t just monitor its operations across high-throughput production lines. It closed the loop: from raw sensor signal to prescribed action to user-validated production outcome. Here’s what a 99% Trust Loop looks like across 16 plants, 85 areas, and 562 critical assets.
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 Unplanned. User-validated.
0
Prescriptions
Acted Upon 95.73% implementation rate
0
%
Prediction Accuracy Across 85 areas, 562 critical assets
0
Hrs MTBFMean Time Between Failure,
last 12 months
All figures validated by MRF’s engineering & operations teams via PlantOS™ Prescription Engine
What’s inside
FROM NOISE
TO OUTCOMES.
Mechanical Faults
Vibration, bearing defects
& coupling wear
Physics + AI models detect ball spin bearing defects, coupling looseness, and gearbox lubrication failure across Banbury Mixers, Roller Head Calender Extruder gearboxes, and 36″ Calender drives before they cascade into unplanned downtime.
Electrical Faults
Motor overheating
& cooling failures
Temperature trend analysis at motor DE and NDE bearings surfaces cooling system inadequacies, lubrication failures, and sudden temperature spikes before they trip extruder motors and calender drives across high-throughput tire production lines.
Process Induced Faults
Load anomalies &
process variation
Continuous monitoring across Banbury Mixers, Hold and Feed Mills, Duplex–Triplex Extruders, Inner Liner Calendering, 4 Roll Calenders, and Tyre Building systems detects load and process deviations before they cost tons of production at scale.
01
6,145 monitoring locations. 85 areas. One Single Source of Truth.
How MRF unified 16 plants — 562 critical assets across mixing, milling, extrusion, calendering, and tyre building — into a single contextualized source of truth. From 40 sensors at Arakkonam to 6,000+ across 16 plants in 18 months — a 14X expansion.
Physics + AI: precision that predictions can’t match
PlantOS™ doesn’t flag anomalies. It traces root cause — across mechanical, electrical, and process domains — with 99.81% prediction accuracy and only 3 missed faults.
Diagnostic → Recommendation → Action
374 prescriptions acted upon. 95.73% implementation rate. Real Diagnostic Reports with specific corrective steps — not dashboards, not alerts. Work orders that close.
Outcomes the plant’s own operators signed off on
1,833 hours of unplanned downtime recovered. 2,091-hour MTBF achieved across critical tire assets. 10% capacity increase contributed through reliability gains — with zero capex. All figures from MRF’s own Maintenance & 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.
MRF’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.
The 99% Trust Loop™ — how outcomes are guaranteed
1.
Contextualize equipment + process
85 areas, 562 critical assets, 6,145 monitoring locations, 16 plants — One Prescriptive AI platform
2.
Detect with physics-based precision
Mechanical, electrical, and process anomalies — not noise
3.
Prescribe exact corrective action
374 prescriptions. Diagnostic → Recommendation → Action
4.
Validate outcomes. Close the loop.
Engineers validate results in PlantOS™ Digital Reporting
Reliability
Throughput
Process Quality
3 Guaranteed Outcomes. 0 Guesswork.
40 → 6,000+ sensors.
1 plant → 16 plants. 18 months.
What started as a 40-sensor pilot on a single 4 Roll Calender at Arakkonam in May 2024 became a 14X enterprise-wide deployment by end-2025 — covering 85 areas and 562 critical assets across India’s largest tire manufacturing footprint.
Full Transformation Story
GET THE COMPLETE PICTURE.
The numbers above are the headline. The full story reveals the real challenges MRF faced — persistent machine breakdowns, lack of real-time visibility on critical assets like 4 Roll Calenders, and the reliability demands of India’s largest tire manufacturing footprint — and exactly how PlantOS™ flipped the script, delivering user-validated outcomes from Arakkonam to enterprise scale.
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Real PlantOS™ Diagnostic Reports from live MRF deployments (Roller Head Calender Extruder, 36″ Calender, 4R
50 Banbury Mixer, QTX 200MM Extruder)
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Equipment-level fault detection across mechanical, electrical & process domains
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The 99% Trust Loop™ framework — step by step
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The 14X scale-up story — from 40 sensors to 6,000+ across 16 plants in 18 months
✔
User-validated outcome data, confirmed by MRF’s own maintenance team
Download the Full Transformation Story
Infinite Uptime · 881 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.
[contact-form-7 id=”3d9579b” title=”landing page of MRF Tyres pdf downlaod”]
Infinite Uptime × MRF Tyres A PlantOS™ Transformation Story · Production Outcomes. Delivered.