OEE = Availability × Performance × Quality, with all three factors calculated automatically from equipment signals and reported production data — no human inflation. Multi-dimensional drill-down makes it crystal clear "exactly where OEE is held back," while downtime-cause classification drives continuous improvement.
From data capture and factor calculation to drill-down analysis and improvement tracking
(Planned time − Downtime) / Planned time, calculated automatically on the principle that planned stops are not deducted while unplanned stops are.
(Actual output × Standard cycle time) / Running time, reflecting speed losses, tallied automatically from equipment signals.
Good output / Total output, automatically aggregated from reported-production and inspection data, including units that pass after rework.
Drill down across 5 dimensions — shift / line / equipment / team / product — to see at a glance which line or machine is dragging OEE down.
Six categories — planned stop / fault / changeover / material shortage / waiting for staff / waiting for quality — are auto-classified, with top causes driving improvement.
Set OEE targets by equipment category / team, view attained / unattained trend charts, and track the effectiveness of improvement activities.
Shift OEE live (every 2h)
OEE used to be calculated via monthly Excel summaries with hand-entered, easily inflated data. SBK MES calculates all three factors automatically from raw data: equipment signals determine downtime, cycle-time data computes performance, and reported-production plus inspection data computes the quality rate.
A plant-level OEE of 65% is just an aggregate — it doesn't reveal which line or machine is lagging. The system supports 5-tier drill-down from plant → workshop → line → equipment → shift, making the problem node obvious.
Downtime by category (min)
The leverage point for OEE improvement lies in downtime causes. The system classifies downtime to the SEMI E10 standard, with top causes driving action: long changeover times → SMED project; frequent faults → strengthen TPM; recurring shortages → supply-chain optimization.
OEMs require key equipment OEE ≥ 85%; an improvement plan must be submitted whenever a month falls short.
When the main cause of low OEE is long changeover time, an SMED project cuts changeover from 30 minutes to 10.
Low performance was caused by mold-temperature fluctuations lengthening the cycle; after upgrading temperature control, performance rose 8%.
The main cause of low OEE was time-consuming line cleaning + validation; scheduling by "cleaning difficulty" raised OEE by 12%.
OEE data comes from equipment + reported production, and the results drive maintenance and improvement
Equipment signals automatically compute the three OEE factors
Reported data computes the quality and performance rates
Low OEE triggers optimization of maintenance plans
OEE trends feed into the consolidated analytics reports
Sign up to try automatic OEE calculation and multi-dimensional drill-down for free, or book a consultant demo