Overall Equipment Effectiveness (OEE)

OEE is calculated by multiplying three percentages: OEE = Availability × Performance × Quality. Availability measures the proportion of scheduled time that the equipment is actually running. It accounts for downtime losses from equipment failures, changeovers, material shortages, and other unplanned stops. Availability = Run Time / Planned Production Time. Performance measures whether the equipment is running at its maximum designed speed. Slow cycles, minor stops, and idling reduce performance. Performance = (Ideal Cycle Time × Total Count) / Run Time. Quality measures the proportion of produced units that meet specifications without rework. Quality = Good Count / Total Count. For example, if Availability is 90%, Performance is 95%, and Quality is 99%, then OEE = 0.90 × 0.95 × 0.99 = 84.6%. This multiplicative relationship means that even small losses in each category compound to create a significant overall impact — which is precisely why OEE is so powerful for revealing hidden factory losses.

OEE was designed to address what Total Productive Maintenance (TPM) practitioners call the 'Six Big Losses' — the most common causes of equipment-based productivity loss in manufacturing. Breakdowns (unplanned equipment failures) reduce Availability. Setup and adjustments (changeovers, warmup time) also reduce Availability. Small stops (jams, misfeeds, sensor blocks lasting under 5 minutes) reduce Performance. Reduced speed (running below the machine's design capacity) reduces Performance. Startup rejects (defects produced during warmup or changeover) reduce Quality. Production rejects (defects during stable production) reduce Quality. By categorizing every minute of lost production into one of these six buckets, OEE analysis reveals exactly where to focus improvement efforts for maximum impact. A factory with 70% OEE often discovers that a single loss category — frequently setup time or small stops — accounts for half the gap, making the improvement roadmap surprisingly clear.

Production scheduling directly influences OEE through several mechanisms. First, intelligent scheduling reduces changeover frequency and duration by grouping similar products together (campaign scheduling), improving Availability. Second, balanced scheduling that aligns production pace with takt time prevents the stop-start patterns that cause small stops and reduced speed, improving Performance. Third, scheduling maintenance windows during planned downtime — rather than waiting for breakdowns — maximizes Availability. Tools like LinePlanner help production planners visualize equipment utilization across shifts and lines, making it easy to spot scheduling patterns that contribute to OEE losses. For example, if the schedule shows frequent changeovers on a bottleneck machine, the planner can resequence orders to batch similar setups. Real-time schedule adherence tracking highlights when a line is falling behind its planned pace, enabling supervisors to intervene before small delays cascade into missed delivery commitments.