How are the six big losses grouped in OEE?
The six big losses in OEE are grouped into three pairs, each corresponding to one of the three OEE factors: availability losses (breakdowns and setup/adjustment), performance losses (idling/minor stops and reduced speed), and quality losses (startup rejects and production rejects). This structure means every loss directly reduces one measurable component of Overall Equipment Effectiveness.
OEE is calculated by multiplying availability, performance, and quality. A score of 100% would mean equipment runs whenever it is scheduled, at full speed, producing only good parts. In practice, world-class manufacturing benchmarks sit around 85%, and most facilities fall below that. The six big losses explain the gap.
- Availability losses: Unplanned breakdowns and planned stops for setup or adjustment
- Performance losses: Idling, minor stops, and running below rated speed
- Quality losses: Defective output during startup and during steady-state production
Grouping losses this way forces teams to look beyond obvious failures. A machine that never breaks down can still deliver poor OEE if it runs slowly or produces scrap. The three-pair structure ensures all sources of lost output are visible and measurable.
What causes equipment breakdowns and unplanned downtime?
Equipment breakdowns in OEE are caused by the sudden failure of a component or system that stops production entirely. Common root causes include mechanical wear, misalignment of rotating components, lubrication failures, electrical faults, and deferred or inadequate maintenance. Breakdowns are the most visible OEE loss because they produce an immediate, measurable stop in output.
In rotating equipment specifically, misalignment is one of the most persistent contributors to unplanned downtime. When a motor shaft and driven equipment are not perfectly aligned, forces are transmitted into bearings, seals, and couplings with every revolution. Over time, this accelerates wear and eventually causes component failure. The problem is compounded by dynamic misalignment, where thermal expansion during operation shifts components out of alignment even when they were correctly set at installation.
Other significant drivers of unplanned downtime include:
- Vibration transmitted through rigid mechanical couplings, which overloads downstream components
- Lubrication failures in couplings and bearings, particularly in harsh or remote environments
- Maintenance-induced failures, where reassembly errors after a planned intervention cause a secondary breakdown
- Deferred maintenance that allows minor degradation to escalate into a full failure
- Electrical faults in drive systems, including aging components in variable frequency drives
Reducing breakdown losses requires both reactive improvements (faster detection and repair) and structural changes that remove failure mechanisms from the drivetrain. Eliminating wear points, reducing the number of scheduled interventions, and designing out misalignment sensitivity all reduce the frequency and severity of breakdowns over the asset's lifecycle.
What is setup and adjustment loss in OEE?
Setup and adjustment loss in OEE is the time lost when equipment is stopped or running below capacity during changeovers, tooling changes, product transitions, or recalibration after maintenance. Unlike breakdowns, this loss is planned but still reduces availability. It is counted from the moment production stops to the moment the equipment produces its first conforming output at full speed.
This distinction matters because setup loss is often accepted as unavoidable. In practice, a significant portion of setup time consists of adjustments made after the initial restart, including fine-tuning speeds, correcting alignment, waiting for temperatures to stabilize, or clearing early defects. These adjustment periods can be as long as the setup itself.
In maintenance-intensive environments, setup and adjustment loss also appears after unplanned repairs. When a coupling is replaced or a shaft is realigned, the time spent on precision alignment, re-checking after thermal growth, and verifying that the system is running correctly all count against availability. Reducing the complexity of post-maintenance setup directly improves OEE availability scores.
Strategies for reducing setup and adjustment loss include standardizing changeover procedures, reducing the number of adjustments required after maintenance, and selecting equipment and components that are less sensitive to installation precision. The goal is to shrink the gap between stopping production and producing conforming output at full speed.
How do idling, minor stops, and reduced speed affect OEE performance?
Idling, minor stops, and reduced speed are the two performance losses in OEE. They reduce the performance factor by causing equipment to run at less than its theoretical maximum rate. Idling and minor stops are brief, frequent interruptions where the machine pauses but does not require maintenance. Reduced speed loss occurs when equipment runs continuously but below its designed capacity.
Performance losses are often the most underreported category in OEE. Minor stops of less than five minutes are frequently not logged, yet their cumulative effect across a shift can be substantial. A machine that stops for two minutes every twenty minutes is losing roughly 10% of its available production time from minor stops alone, without a single breakdown appearing in the maintenance log.
Idling and minor stops
Idling and minor stops are typically caused by sensor faults, material jams, misfeeds, blockages, or operator interventions that clear quickly without a formal work order. Because each event is brief, the temptation is to treat them as insignificant. However, when tracked systematically, they often account for more lost production than major breakdowns. Vibration in rotating equipment is a common indirect cause: excessive vibration can trigger safety sensors, cause misfeeds, or displace components that require manual resetting.
Reduced speed loss
Reduced speed loss occurs when operators deliberately run equipment below its rated speed to avoid quality problems, prevent overheating, or compensate for mechanical issues such as vibration or instability. It also occurs when aging equipment cannot sustain its original throughput rate. This loss is particularly difficult to detect because the equipment appears to be running normally. Comparing actual cycle time against the designed ideal cycle time is the only reliable way to quantify it.
What are quality losses in OEE and how are they measured?
Quality losses in OEE are output that fails to meet specification, divided into two types: startup rejects produced during the warmup or adjustment phase after a stop, and production rejects generated during steady-state operation. Both types reduce the quality factor in OEE by subtracting non-conforming units from total output. Quality losses are measured as the ratio of good output to total output over a defined period.
Startup rejects are particularly relevant in processes that require time to reach stable operating conditions, such as thermal processes, extrusion, or precision machining after a tool change. Every time equipment stops and restarts, there is a window where output does not meet specification. Reducing the number of stops, or shortening the stabilization period after each stop, directly reduces startup scrap.
Production rejects during steady-state operation are typically caused by process drift, worn tooling, inconsistent material inputs, or mechanical instability. In rotating equipment, vibration is a recurring contributor: excessive vibration can affect product consistency in mixing, pumping, and conveying applications. Reducing mechanical instability in the drivetrain therefore has a measurable effect on quality as well as availability and performance.
Quality losses are measured by tracking the number of defective or reworked units as a percentage of total units produced. Both scrap and rework count against OEE quality, because rework consumes time and resources even when the part is eventually accepted. World-class OEE targets a quality rate above 99%, meaning fewer than one in a hundred units requires rework or disposal.
Which of the six big losses is hardest to eliminate?
Reduced speed loss is widely regarded as the hardest of the six big losses to eliminate, because it is the least visible and the most deeply embedded in operator behavior and process culture. Unlike breakdowns, which trigger alarms and work orders, reduced speed loss accumulates silently. Equipment appears to be running, so no intervention is triggered, yet throughput is consistently below what the machine is capable of delivering.
The difficulty is compounded by the fact that operators often reduce speed deliberately, as a rational response to quality problems, vibration, instability, or past failures. Without addressing the underlying mechanical or process issue, simply instructing operators to run at full speed produces more rejects or more breakdowns. Eliminating reduced speed loss therefore requires solving the root cause rather than overriding the symptom.
Minor stops present a similar challenge at a different scale. Because each event is brief, they are rarely investigated systematically. Over months of operation, the cumulative data reveals patterns that individual events conceal, but capturing that data requires consistent logging discipline that many facilities do not sustain.
In practice, the hardest loss to eliminate is the one that is hardest to see. Breakdowns and setup losses are measured because they are impossible to ignore. Performance losses, particularly reduced speed, persist precisely because they do not demand attention in the moment.
How Zytec Non-Contact Drives address OEE losses
Each of the six big losses in OEE has a mechanical dimension, and non-contact drive technology directly addresses several of the most persistent root causes. Zytec's non-contact drives eliminate physical contact between the motor and driven equipment, removing the wear mechanisms that drive breakdowns, reduce speed, and generate vibration-related quality problems.
- Breakdown reduction: No wear components, no lubrication requirements, and no misalignment sensitivity mean the drivetrain does not degrade between maintenance intervals. Expected service life exceeds 20 years without coupling replacement.
- Setup and adjustment loss: Installation requires no laser alignment, and there is no periodic coupling element replacement. Post-maintenance setup time is significantly reduced because the coupling does not need precision realignment after every intervention.
- Reduced speed and minor stops: Vibration reduction of up to 80% removes a common reason operators run equipment below rated speed. Fewer vibration-triggered sensor faults means fewer minor stops.
- Quality losses: Stable, vibration-free operation reduces process drift in applications such as pumps, fans, and conveyors where mechanical instability affects output consistency.
- Total cost of ownership: With energy savings of up to 50% and maintenance costs reduced dramatically, the payback period is often under two years, making the investment straightforward to justify against OEE improvement targets.
If your facility is working to reduce OEE losses and the root cause analysis points to drivetrain reliability, vibration, or maintenance frequency, contact Zytec to discuss how non-contact drive technology can be applied to your specific rotating equipment.
Frequently Asked Questions
How do I get started with measuring the six big losses if my facility has no OEE tracking system in place?
Start by manually tracking downtime events, output counts, and reject quantities for a single machine or production line over two to four weeks. Even a simple spreadsheet that records stop time, reason, duration, and units produced is enough to calculate a baseline OEE score and identify which of the six loss categories is consuming the most time. Once you have a baseline, you can prioritize where to invest in more formal data collection tools or software. Trying to instrument everything at once typically delays action; starting small with one asset builds the habit and reveals what data is actually useful.
What is a realistic OEE improvement target when starting a loss reduction program?
For facilities operating below 60% OEE, a realistic near-term target is reaching 65–70% within the first 6–12 months by addressing the most visible losses first — typically unplanned breakdowns and excessive setup times. Moving from 70% toward the world-class benchmark of 85% is a longer journey that requires tackling performance losses like reduced speed, which demand cultural and process changes in addition to technical fixes. Setting incremental targets by loss category (for example, reducing breakdown time by 20%) is more actionable than chasing a single OEE percentage point improvement.
Can a machine have high availability but still perform poorly on OEE?
Yes, and this is one of the most common misconceptions about OEE. A machine that never breaks down and has minimal setup time can still deliver a poor overall OEE score if it runs at 70% of its rated speed or produces a high proportion of defective parts. Because OEE multiplies all three factors together, a 95% availability score combined with an 80% performance score and a 90% quality score yields an OEE of only 68.4% — well below world-class. This is precisely why the six big losses framework exists: to make performance and quality losses as visible as downtime.
How should we prioritize which of the six big losses to tackle first?
Prioritize based on data, not assumptions — the loss category consuming the most production time or output is the right starting point, regardless of how visible it feels day-to-day. In most facilities, breakdowns and reduced speed losses account for the largest share of lost OEE, but this varies significantly by industry and equipment type. Run a Pareto analysis on your loss data: rank each of the six categories by total time or units lost over a 30–60 day period, and focus initial improvement efforts on the top one or two categories. Addressing the biggest loss first delivers the fastest measurable return and builds organizational confidence in the process.
What is the difference between rework and scrap in OEE quality calculations, and do both count against the quality factor?
Both rework and scrap count against the OEE quality factor, because OEE measures only units that exit the process as conforming output on the first pass. A reworked part that is eventually accepted still consumed additional time, labor, and resources, and it was not produced correctly the first time — so it is counted as a quality loss in the period it was originally made. The distinction matters for cost analysis (scrap is typically more expensive than rework), but from an OEE perspective, the goal is a quality rate that reflects true first-pass yield, not final yield after rework is factored in.
How do we convince operators to log minor stops consistently when each event feels too small to bother recording?
The most effective approach is to show operators the aggregated data after a short pilot period of consistent logging — seeing that two-minute stops add up to 45 minutes of lost production per shift makes the case more powerfully than any policy directive. Reduce the friction of logging by making it as simple as possible: a physical tally sheet at the machine, a single button press on an HMI, or a short dropdown on a tablet. Framing the data as a tool for operators to identify and fix frustrating interruptions — rather than as a performance monitoring mechanism — also significantly improves buy-in and logging discipline.
Are the six big losses applicable to non-manufacturing environments, such as logistics or food processing?
The six big losses framework applies well beyond traditional discrete manufacturing. In food processing, quality losses from startup rejects are particularly significant due to the time required for thermal and hygiene stabilization after every stop. In logistics and warehousing, conveyor and sortation systems experience all six loss types, including minor stops from jams and reduced speed from aging equipment. The categories may need to be relabeled to fit the operational language of a specific environment, but the underlying structure — availability, performance, and quality — maps onto any process where equipment output can be measured against a theoretical maximum.