A power plant's turbine hall can run at full load all shift and still lose ten percent of its output to nobody in particular — a slow ramp after a trip, a boiler soot-blow that ran long, a coal feeder that choked for six minutes nobody logged. Operations leaders usually find out about these losses in the monthly generation report, weeks after the megawatt-hours were already gone. iFactory's OEE and availability dashboard closes that gap by scoring every unit continuously against availability, performance, and quality, and turning shift-level losses into a single number your team can act on before the next shift starts. You can see it running against your own unit data by booking a demo whenever your team is ready.
Your Plant Reports 92% Availability. Your Actual OEE Says Something Very Different
iFactory scores every generating unit continuously across availability, performance, and quality losses, replacing the monthly generation report with a live number your shift supervisors can act on immediately.
Why "We Were Available 92% of the Time" Still Leaves Megawatts on the Table
Availability alone tells operations leaders almost nothing about what actually left the busbar. A unit can be technically available and still underperform badly against its rated output because of derates, slow ramps, and part-load running that never trips an alarm. The figures below show how much generation capacity typically disappears between the availability number in the monthly report and the true output-based OEE score.
Six Loss Categories iFactory Tracks on Every Unit, Every Shift
The classic six big losses framework was built for discrete manufacturing, but the same structure maps cleanly onto a generating unit once you replace cycle time with megawatt output. Select each category below to see how iFactory isolates it from routine operating noise.
Unplanned trips from boiler tube leaks, turbine vibration events, or protection system actuations are the largest single availability loss at most thermal stations. iFactory correlates trip timestamps against sensor trends in the preceding hours so the root cause is visible before the incident report is even filed.
Scheduled maintenance windows routinely run long once a borescope inspection turns up unexpected wear. The dashboard tracks outage milestones against the original plan in real time, flagging schedule slip as soon as it starts rather than at the closeout meeting.
Every start consumes hours of ramp time at reduced or zero output while metal temperatures equalize, and a slower-than-optimal ramp curve quietly compounds across a cycling unit's annual run hours. iFactory benchmarks each start against the unit's own best historical ramp rate.
Ambient temperature limits, fuel constraints, and equipment derates keep a unit running below rated capacity for extended stretches without ever generating an alarm. The dashboard quantifies the megawatt-hour gap between actual and rated output for every derate event.
Fouled condensers, worn turbine seals, and drifting combustion tuning erode heat rate gradually enough that no single reading looks abnormal. iFactory trends heat rate against a corrected baseline so degradation is visible months before the next performance test.
Steam temperature or pressure excursions outside turbine design limits force load reductions to protect equipment, a quality-equivalent loss that rarely gets tracked with the same rigor as an outage. The dashboard logs every excursion against its output impact automatically.
Every Percentage Point Between Availability and True OEE Is Revenue Your Plant Already Generated On Paper
iFactory turns your DCS and historian data into a continuously scored OEE number for every unit, broken down into the exact loss category driving it. Book a demo and see your own unit's real OEE calculated live.
From DCS Tags to a Shift-Level OEE Number in Four Stages
Operations teams do not need a new control system to get a live OEE score. iFactory reads the historian and DCS tags you already have and layers a scoring engine on top, so the number reflects what happened this shift rather than what a report says happened last month.
Rated Capacity and Baseline Modeling
Each unit's rated output, ambient correction curves, and design heat rate are loaded so every subsequent measurement has a correct reference point rather than a flat historical average.
Continuous Tag Ingestion
Historian and DCS tags for load, steam conditions, fuel flow, and auxiliary consumption stream into iFactory at one-minute resolution, with automatic handling for sensor dropouts.
Loss Classification
Every deviation from the corrected baseline is classified into one of the six loss categories and quantified in megawatt-hours, with the responsible system or event tagged automatically.
Shift and Unit Scoring
Availability, performance, and quality scores roll up into a single OEE figure at the shift, daily, and monthly level, visible to operators, shift supervisors, and plant leadership at the same time.
What Changes When OEE Moves From a Monthly Report to a Live Dashboard
The table below compares how operations teams typically track performance today against what a continuously scored OEE dashboard changes at the shift level.
| Capability | Monthly Generation Report | iFactory Live OEE Dashboard |
|---|---|---|
| Reporting Frequency | Once a month, after data reconciliation | Continuous, updated every shift |
| Loss Attribution | Broad outage categories only | Six loss categories with root cause |
| Detection Lag on Drift | Weeks to a full billing cycle | Hours to a few days |
| Visibility for Shift Supervisors | None during the shift itself | Real-time score and loss breakdown |
| Benchmark Basis | Prior year averages | Ambient-corrected rated baseline |
Getting From Historian Access to a Live OEE Score
Most power generation sites can see their first live OEE score within the first few weeks of onboarding, since the dashboard is built on data that already exists in the plant historian.
Historian Connection
iFactory connects to your existing historian and DCS tag structure without requiring new field instrumentation for most units.
Baseline Calibration
Rated capacity, ambient correction, and design heat rate curves are calibrated against each unit's commissioning and test data.
Loss Model Validation
Operations and reliability engineers review the first month of loss classifications alongside the dashboard to confirm accuracy against known events.
Shift-Level Rollout
Shift supervisors and control room operators get direct dashboard access, replacing the monthly report as the primary performance reference.
Questions Operations Leaders Ask Before Adopting a Live OEE Dashboard
The Megawatts Your Report Doesn't Show Are Still Sitting on Your Historian
Every derate, slow ramp, and heat rate drift that never makes it into the monthly report is already recorded somewhere in your historian tags, waiting for a scoring model that knows how to read it. The gap between a 92% availability figure and a 78% true OEE score is not a measurement error; it is real generation capacity that left the plant unaccounted for.
iFactory's OEE and availability dashboard reads the data your plant already produces and turns it into a shift-level score your operations team can act on the same day a loss appears, rather than a month later. Book a demo to see your own units scored against their true output potential.
Stop Reporting Availability. Start Scoring Output.
iFactory continuously calculates true OEE for every generating unit and shows your team exactly which loss category is costing megawatts right now. Book a demo and see the score calculated live from your own historian data.
