Key takeaways
Short answer: Availability loss and performance loss are two of the three loss categories in OEE, and they capture fundamentally different problems. Availability loss is production time lost because the equipment was stopped — downtime from breakdowns and changeovers. Performance loss is production lost because the equipment ran slower than its ideal rate while it was running — slow running and minor stops. One is about time stopped; the other is about speed while running. A machine can be up a lot (low availability loss) yet still produce slowly (high performance loss), so both must be tracked. For the time buckets behind them, see planned production time vs operating time.
Availability loss is the production time lost because the equipment was stopped when it should have been running — the downtime within your planned production time. It is the gap between the time you scheduled to produce (planned production time) and the time the equipment actually ran (operating time). Availability loss comes from two of the six big losses: breakdowns (unplanned failures that stop the machine) and setup and adjustment (changeovers and setups that take the machine offline). The defining feature of availability loss is that the machine is not running — it is stopped, producing nothing. Availability loss is the most visible kind of loss, because a stopped machine is obvious, and it is usually the first thing improvement efforts target. It directly reduces the availability factor of OEE, and it answers the question: how much of my scheduled time did I lose to the equipment being down?
Performance loss is the production lost because the equipment ran slower than its ideal rate while it was running — the speed loss within operating time. Even when a machine is up and producing, it may not be producing at its full rated speed, and that shortfall is performance loss. It comes from two of the six big losses: reduced speed (running below the rated rate) and minor stops or idling (brief, frequent pauses that do not count as full downtime but slow the average output). The defining feature of performance loss is that the machine is running but not at full speed — it is up, just slow. This makes performance loss far less visible than availability loss: a running machine looks fine, and the loss hides in a slightly-slow cycle rather than an obvious stoppage. Performance loss directly reduces the performance factor of OEE, and it answers: while it was running, how much output did I lose to slowness?
The clean distinction is time stopped versus speed while running: availability loss is the equipment being stopped, performance loss is the equipment running below speed. They occupy different parts of the time structure — availability loss is the gap between planned production time and operating time (the machine is down), while performance loss occurs within operating time (the machine is up but slow). This is why they must be tracked separately: they are different problems with different causes and different fixes. Availability loss is attacked by reducing breakdowns and speeding changeovers; performance loss is attacked by addressing the causes of slow running and minor stops. A common error is to focus only on the visible availability loss (the obvious stoppages) while ignoring the hidden performance loss — a machine can be up most of the time, looking healthy, while quietly losing a large fraction of its potential output to running slow. Both are real, both count, and only by separating them do you see and address each.
A machine has 7 hours of planned production time. It suffers 1 hour of downtime (a breakdown), so it runs for 6 hours — that 1 hour is availability loss, and availability is 6 divided by 7, about 86%. Now look within those 6 hours of running. The machine's ideal cycle would produce 100 units an hour, so 6 hours should yield 600 units. But it actually produced 480, because it ran below rated speed and suffered minor stops — that shortfall of 120 units is performance loss, and performance is 480 divided by 600, or 80%. Two distinct losses: the 1 hour stopped (availability loss) and the slowness while running (performance loss). Note the machine was up 86% of its scheduled time yet still lost 20% of its running output to slowness — a substantial performance loss that the availability figure completely misses. Tracking only availability would have shown a reasonably healthy machine; tracking performance too reveals the hidden speed loss.
The reason to track availability loss and performance loss separately is that each is invisible to the other, and a machine can be strong on one while weak on the other. A machine with excellent availability (rarely stops) can still have poor performance (runs slow when up), and vice versa — and if you measure only one, you miss the other entirely. The worked example shows the danger: a machine up 86% of the time looks fine on availability alone, while quietly losing 20% of its output to performance loss. Conversely, a machine that stops often but runs at full speed when up has an availability problem, not a performance one. The two require different diagnoses and different fixes, so collapsing them — or tracking only the visible availability loss — leads to attacking the wrong problem or missing a large loss. OEE deliberately separates them into distinct factors precisely so that both the time-stopped and the speed-while-running losses are visible and addressable.
Availability loss and performance loss are two of the three loss categories that make up OEE (the third being quality loss). Availability loss reduces the availability factor (operating time divided by planned production time), and performance loss reduces the performance factor (actual output divided by ideal output for the running time, the cycle-time ratio). Together with quality loss they multiply into the overall OEE. The two map onto four of the six big losses — breakdowns and setup (availability), reduced speed and minor stops (performance). Separating them is the whole point of OEE's structure: it ensures both the obvious time-stopped losses and the hidden speed-while-running losses are measured and attributed, so neither is missed. A line's OEE can be dragged down by either, and only the decomposition shows which.
Fabrico measures availability loss and performance loss separately and precisely, capturing both the downtime that stops the machine and the slow running and minor stops that rob output while it runs. By decomposing OEE into its distinct factors, it surfaces the hidden performance loss that a downtime-only view misses — showing whether a line's lost output is really a time-stopped problem or a speed-while-running one, and pointing improvement at the right cause. Book a demo to see both your stopped time and your slow running, clearly separated.
Availability loss is production time lost because the equipment was stopped — breakdowns and setup. Performance loss is production lost because the equipment ran slower than its ideal rate while running — slow running and minor stops. One is time stopped; the other is speed while running.
Yes. A machine can be up most of its scheduled time (low availability loss) yet still produce well below its rated speed when running (high performance loss). This is why both must be tracked — measuring only availability would miss the hidden speed loss.
Two of the six big losses: reduced speed (the machine running below its rated rate) and minor stops or idling (brief, frequent pauses that do not count as full downtime but slow the average output). Both occur while the machine is running, so they hide in a slow cycle.
Because each is invisible to the other and needs a different fix. Availability loss is attacked by reducing breakdowns and speeding changeovers; performance loss by addressing slow running and minor stops. Collapsing them hides which problem to attack.
They are two of the three OEE loss categories. Availability loss reduces the availability factor; performance loss reduces the performance factor; together with quality loss they multiply into OEE. They map onto four of the six big losses, and separating them is the point of OEE's structure.
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