Prescriptive Maintenance Solutions
for Plant
Reliability.
One Vertical AI platform.
A purpose-built AI
solution for every equipment class in your plant,
organised by industry and deployed in weeks.
PlantOS™ delivers prescriptive maintenance as three
solutions, for all equipment in a heavy
manufacturing plant. Where generic tools raise alerts, PlantOS™ issues a prescription: the specific
component at fault, the corrective action, and the outcomes to be achieved. Operators validate every
prescription, so the AI learns from real outcomes across 1000 plants.
The PlantOS™ Advantage
Plant
Reliability
The
umbrella outcome: less downtime, lower maintenance cost, and longer equipment life across every line.
Equipment-Specific
Intelligence
Each
solution is pre-trained on thousands of failure signatures for that exact equipment class, not on a
generic model.
Quantified
ROI
Every
prescription forms a closed loop, where operator validations are translated into avoided downtime
costs for documented board-level reporting.
Enterprise Agent
Orchestration
Powers
your corporate AI assistants natively, enabling management to instantly query fleet intelligence and
auto-generate executive reports.
What are the three PlantOS™ prescriptive maintenance solutions?
One platform, three solutions, sized to what each asset is worth.
Infinite Uptime’s PlantOS™ covers the full criticality spectrum, from the flagship
equipment that defines your output to the balance of plant that has never been monitored at all.
Equipment-specific AI protects the machines that can stop production. Wired and wireless coverage scales
across everything else. A single risk model underneath turns all of it into maintenance, spares and CAPEX
decisions.
Where generic tools raise alerts, PlantOS™ issues a prescription: the component at fault, the
corrective action, and the outcome to be achieved.
01 · The Active Defense
AI Shields
Equipment-specific AI for the machines that can stop production.
Each AI Shield is trained on a single class of production-critical equipment, so it
tells
a mechanical fault apart from a process upset instead of flagging both as noise. Dynamic FMEA correlates
live mechanical signals with real process conditions, which surfaces failure modes that appear only when
heat, load or chemistry change.
Shields in service
-
Steel
-
Cement
-
Tire & Rubber
-
Pulp & Paper
-
Metals & Mining
02 · The Foundation
Flex Reliability
Coverage for the rest of the plant, sized to what each asset is worth.
Not every machine justifies the same sensing. Flex Reliability lets you match the
technology to the consequence of a stoppage, from wired piezoelectric on assets that halt a line to
self-powered wireless tags on equipment that has never carried a monitoring budget. Existing third-party
sensor data is ingested as it is, so there is no rip and replace.
Three coverage tiers
- Critical Equipment Reliability
Wired piezoelectric, continuous. 150 °C surface, down to 2 RPM. - Standard Equipment Reliability
MEMS, wired or wireless. Pumps, fans, motors, gearboxes,
compressors. - Non-Critical Equipment Monitoring
Self-powered wireless InfiSense 3XT, periodic. No gateways or
cabling.
03 · The Orchestration Layer
Plant Fusion
One risk model behind every maintenance, spares and CAPEX decision.
Asset signals roll up through equipment, process, plant and fleet into one risk
foundation of failure probability, consequence and MTBF, ranked by RBI, RCM and FMEA. Open API and MCP
carry each prescription into the systems that execute the work, and every job an operator closes
returns as a label that sharpens the next decision.
Three decisions, one foundation
- MaintainA dynamic, ISO-aligned PM
programme driven by failure mode, not by calendar date. - StockRisk-aligned min and max
levels with ordering triggers, safety-critical items always human-gated. - InvestCAPEX backed by
failure-probability forecasts and remaining-life estimates.
An AI Shield for every production-critical asset
Ten Shields across five verticals, each trained on one class of equipment. Select a vertical, then open
a
Shield to see what it watches, the faults it detects and what it has protected.
Dynamic FMEA, 24×7 human-in-the-loop CoE review
Hoist motors, rope drum, end-carriage bearings and ladle transfer sequences,
preventing catastrophic failures in live zones.
Faults detected
- Hoist motor bearing failure
- Rope drum and sheave wear
- End-carriage wheel and rail wear
- Brake and gearbox degradation
Single prescription
4 hrs
of unplanned downtime avoided on the EOT ladle crane
Roughly $750K in production protected* at a global top-ten integrated steel
producer, from one call.
Explore this Shield
The roller table drive line between the finishing stand and the coiler, reading
roll, coupling and motor condition alongside the laminar cooling zone.
Faults detected
- Roll and bearing degradation across the table
- Coupling and drive motor faults
- Roll surface wear and scale build-up
- Gearbox and drive-line misalignment
Built for the section of the mill you cannot afford to stop
- Sealed wired sensing to 120 °C, no batteries
- RPM-gated capture inside the stable band
- Zero PLC dependency
- Early detection through cross-correlation
Cumulative
58 hrs
of ROT roll uptime protected
At one of the world’s most valuable steel producers, 2022 to 2026.
Mill stands, work rolls and backup rolls, catching bearing faults, roll surface
defects and chock misalignment before they cause strip breaks or quality rejects.
Faults detected
- Work roll and backup roll bearing faults
- Chock alignment drift
- Gearbox and spindle vibration
- Lubrication system anomalies
Prevented outcome
Caught at the chock, not at the coiler.
The component is identified before misalignment becomes a strip break and a
grade downgrade.
Rolling mill stands across steel and metals.
Turbo-blowers and axial compressors feeding blast furnaces, tracking surge
margins, bearing health, blade condition and inter-cooler performance.
Faults detected
- Impeller and blade wear
- Bearing degradation
- Surge and stall events
- Inter-cooler fouling and seal leaks
Single prescription
12 hrs
of unplanned blast furnace downtime avoided
Roughly $2.0M in production protected* at one of the world’s most valuable
steel producers, from one call.
Bearing temperatures, tyre and roller wear, shell deformation and combustion
anomalies across the kiln line, with two to three weeks of actionable lead time.
Faults detected
- Bearing degradation and overheating
- Tyre and roller misalignment
- Shell ovality and hot spots
- Burner and combustion drift
Cumulative
45 hrs
of kiln uptime protected
At the world’s third largest cement producer, April to May 2026.
End-to-end VRM health covering grinding pressure, vibration signatures, separator
performance and gearbox condition.
Faults detected
- Gearbox mesh and lubrication faults
- Roller and table wear
- Fan imbalance and bearing failure
- Separator drive anomalies
Single prescription
48 hrs
of VRM downtime avoided after early gear wear was caught in the gearbox
At one of the world’s largest cement producers.
Rotor health, gearbox condition, ram and door seals, and batch-to-batch process
consistency, protecting compound quality.
Faults detected
- Rotor imbalance and bearing wear
- Gearbox helical and bevel faults
- Ram cylinder seal degradation
- Motor harmonics and thermal drift
Single prescription
22 hrs
of unplanned Banbury mixer downtime avoided
Roughly $650K in production protected* at a top-five Indian tyre
manufacturer, from a single gearbox call.
Rubber extrusion lines, tracking screw and barrel wear, die pressure consistency,
drive faults and temperature uniformity.
Faults detected
- Screw and barrel wear profiles
- Drive motor and gearbox faults
- Die pressure and temperature anomalies
- Feed roll bearing degradation
Cumulative
98 hrs
of extruder uptime protected
At a leading Indian tyre manufacturer, 2024 to 2026.
Paper machine dryer sections, covering cylinder and felt roll bearings, drive
train integrity, thermal stress and roll surface condition.
Faults detected
- Cylinder and felt roll bearing failure
- Drive shaft shear and connecting gear damage
- Roll shell wear and thermal fatigue
- Cylinder imbalance and oil contamination
Cumulative
235 hrs
of dryer uptime protected
Across pulp and paper customers, 2022 to 2026.
Bearing and drive condition, structural and weld integrity, vibration dynamics and
screen surface wear.
Faults detected
- Bearing failure and shaft shear
- Structural integrity and weld cracks
- Side plate failure and thermal fatigue
- Weight unbalance, resonance and screen tear
Single prescription
30 hrs
of unplanned downtime avoided
Roughly $450K in production protected* at one of Asia’s leading mining
enterprises, from a single exciter-bearing call.
*Production protected is calculated on the customer’s own stated hourly value of output for
the affected line.
No blind spots, no orphan assets.
Deep domain AI on the equipment that defines your output, flexible coverage across everything that supports
it, and one risk model that turns all of it into decisions your board can read.
Compounding Intelligence
Why does the outcome gap widen instead of closing?
Zero Guesswork. Compounding Intelligence. Starts Day 1.
Infinite Uptime retraining across
1000
plants
Horizontal platforms static local
models drift over time
The
Structural Cause
Compounding intelligence
through the 99% Trust Loop
PlantOS™ – the Prescriptive
Al
that learns continually across the entire installed base. Operator
validation turns every correction into shared intelligence, so each asset
teaches every other.
Horizontal platforms rely on static local models that drift over time. Because
PlantOS™ retrains across 1000 plants, drift is caught before it compounds, and
accuracy improves the longer the
system runs.
How long does it take to
deploy PlantOS™ Prescriptive AI?
The Path to Reliability Outcomes Your Operators Trust – in 90 Days
No rip-and-replace works with your
existing systems.
First prescription in 2
weeks. Scale with confidence.
Week 1-2
Solution Deployment
-
100% equipment coverage Day
1 -
Rotating + static equipment +
process context -
Baseline assessment
complete
Week 3-4
First Prescription
-
Operator validation
workshop - Digital signoff trained
- First fault prescribed
Month 2
Scale & Optimize
-
Additional equipment
lines -
Process efficiency
modules -
KPI baseline
established
Month 3
Plant-Wide
- Board-ready ROI report
- Expansion planning
- 99% Trust Loop complete
Ready to see your first
prescription?
Book a discovery call. We’ll model your specific
equipment risk and ROI before you commit.
Frequently Asked Questions
01
What is prescriptive maintenance and how is it different from predictive maintenance?
What is prescriptive maintenance and how is it different from predictive maintenance?
Predictive maintenance forecasts that a machine is likely to fail and roughly when. Prescriptive maintenance goes further: it identifies the specific component at fault mapping both mechanical and process-induced faults, prescribes the corrective action, and highlights the guaranteed outcomes. PlantOS™ then captures whether the fix worked, so its recommendations improve with every validated outcome.
02
What is Dynamic FMEA in prescriptive maintenance?
What is Dynamic FMEA in prescriptive maintenance?
Dynamic FMEA is the method behind AI Shields. A traditional Failure Modes and Effects Analysis is a static document, written once and quickly outdated. Dynamic FMEA continuously correlates live mechanical signals with real process conditions, so it detects failure modes that appear only when heat, load or chemistry change. That is how PlantOS™ identifies faults such as thermal fatigue and cyclone jamming that generic vibration monitoring cannot see.
03
Does Infinite Uptime’s solution require replacing existing equipment?
Does Infinite Uptime’s solution require replacing existing equipment?
No. PlantOS™ requires no rip-and-replace. Sensors are retrofitted onto your existing equipment and PlantOS™ works alongside the systems you already run. Most plants receive their first prescription within two weeks of installation.
04
What equipment does the AI Shield Prescriptive Maintenance Solution support?
What equipment does the AI Shield Prescriptive Maintenance Solution support?
AI Shields are built for flagship heavy industrial equipment, specifically kilns, mills, cranes, furnaces, dryers, etc. Each Shield is trained on the failure signatures of that exact equipment class and detects both mechanical and process-induced faults including thermal fatigue, material build-up, cyclone jamming, oil contamination, gear-mesh backlash, and more.
05
Which PlantOS™ solution is right for my equipment?
Which PlantOS™ solution is right for my equipment?
It depends on asset criticality and operational scope. AI Shields protect flagship, production-critical machinery – such as kilns, rolling mills, and cranes – by correlating live mechanical signals with process parameters to detect complex, condition-specific failure modes. Flex Reliability delivers standardized wired and wireless coverage across the rest of your plant’s rotating assets. Underpinning both is Plant Fusion, which aggregates asset intelligence into a unified risk model, translating line-level prescriptions into plant- and fleet-wide maintenance, spares, and CAPEX decisions. Together, they span the complete criticality spectrum without requiring a patchwork of standalone tools.
Latest Insights
Condition-Based Maintenance vs. Prescriptive Maintenance: Key Differences Explained
As industrial operations become more complex and cost pressures increase, maintenance strategies are evolving beyond reactive and time-based approaches. Two commonly discussed modern strategies are Condition-Based Maintenance (CBM) and Prescriptive Maintenance. While both aim to reduce failures and improve reliability, they differ significantly in how decisions are made and how effectively downtime is prevented.
Prescriptive vs predictive maintenance refers to two different industrial maintenance strategies. Predictive maintenance uses condition monitoring and predictive analytics to estimate when equipment is likely to fail, while prescriptive maintenance goes further by recommending what actions to take, when to take them, and why to prevent failure. Prescriptive maintenance uses prescriptive AI, operational context, and outcome feedback loops, such as Infinite Uptime’s 99% Trust Loop, to ensure recommendations are trusted, acted upon, and continuously validated, resulting in higher reliability, reduced unplanned downtime, and measurable ROI.
Prescriptive Maintenance + Energy Efficiency: A Practical Path to Stable Industrial Operations
In the United States, unplanned downtime costs manufacturers over $1 trillion annually, while energy accounts for 20–40% of operating costs in energy-intensive plants such as steel, cement, chemicals, and food processing. Industry studies show that unplanned downtime alone can erode 5–20% of annual production capacity, even before maintenance costs are considered.