What is OEE and how is it calculated?

OEE, Overall Equipment Effectiveness, is one of the most widely used key performance indicators in the manufacturing industry. A single figure between 0 and 100% is meant to summarize how well a machine, a line, or an entire factory is utilizing its potential. However, many use this metric without really knowing what it measures, how it is calculated, or what a good value is in practice.

This guide covers OEE from the ground up. We explain what the metric consists of, how to calculate it step-by-step, what is hidden behind the figure, and why the "world-class standard of 85%" is a myth that leads production managers astray. Once you have read this article, we recommend reading the second part on why OEE is not enough as a standalone KPI, where we explain how the metric should be used to actually drive improvement.

What is OEE?

OEE stands for Overall Equipment Effectiveness. The metric originated from Total Productive Maintenance (TPM) during the 1980s and has since become the standard for measuring how effectively production equipment is utilized.

The metric answers a simple question: Out of the time the equipment could potentially produce, how much does it actually produce at the right speed and with the right quality?

OEE consists of three components that we multiply together:

OEE = Availability × Performance × Quality

Availability measures the proportion of planned production time that the machine actually ran. Stops, both planned and unplanned, reduce availability.

Performance measures how fast the machine ran. Speed losses, micro-stops, and idling drag down performance.

Quality measures the percentage of produced units that met quality standards. Scrap and rework lower quality.

Because we multiply the three parts instead of adding them, a small deficiency in each area can result in a large total loss. Three component values of 90% yield an OEE of 73%, not 90%. This is one of the most important insights in the entire OEE model: the losses compound each other.

Does OEE have another name in Swedish?

In Swedish, OEE is called TAK, and it is the exact same metric. TAK stands for Tillgänglighet (Availability), Anläggningsutbyte (Performance), and Kvalitetsutbyte (Quality). In English, the terms are Availability, Performance, and Quality.

• Availability is Tillgänglighet.

• Performance is Anläggningsutbyte.

• Quality is Kvalitetsutbyte.

This means you calculate TAK in the same way as OEE. TAK is directly comparable to OEE.

How do you calculate OEE?

The basic formula looks like this:

Availability = run time ÷ planned production time
Performance = (actual production × ideal cycle time) ÷ run time
Quality = good units ÷ total units produced

Here is a calculation example: A line is scheduled to run for 8 hours (480 minutes). Due to downtime, it ran for 408 minutes. This gives an availability of 85%. During the run time, it produced 800 units. The ideal cycle time is 0.5 minutes per unit, which corresponds to 816 possible units. The performance rate is 98%. Out of the 800 units, 780 were approved. The quality rate is 97.5%.

85% availability × 98% performance × 97.5% quality yields an OEE of 81%.

That is the calculation. The difficulty does not lie in the mathematics. The challenge is measuring the right things, defining "planned production time" consistently, and managing changeovers, micro-stops, planned maintenance, and speed losses in a way that provides comparable figures over time. That is where most OEE projects are won or lost, not in the formula.

What is hidden behind the figure: 6 big losses

An OEE figure is a summary. To make it useful, we need to know what is dragging it down. TPM (Total Productive Maintenance) identifies six big losses that correspond to the three components of OEE.

Availability losses:

1. Breakdowns and unplanned stops

2. Setup and adjustments

Performance or speed losses:
3. Idling and minor stops
4. Reduced speed

Quality losses:
5. Startup losses
6. Defects and rework during normal production

Micro-stops are included in the idling and minor stops category within the six big losses and normally affect the performance component of OEE. They can be tracked separately in the analysis to highlight recurring issues, but they do not constitute a seventh category in the model. Micro-stops are brief interruptions of seconds or just a single minute. A bottle getting stuck, a sensor triggering an alarm, a sheet of paper feeding crookedly. Individually, they are insignificant. Collectively, they can account for a major portion of performance losses. They are difficult to capture without automated data collection, as they are too short and too frequent to be registered manually.

Understanding these losses is the difference between an OEE figure that is merely reported and one that can be acted upon. Without a link to the underlying losses, OEE becomes just a reporting figure. With a link, it becomes a tool for prioritizing where improvement efforts will have the greatest impact.

Is 85% OEE really world-class?

Many articles claim that 85% is "world-class" and that factories should aim for this. However, 85% functions more as an abstract reference point that rarely aligns with reality. In practice, the average OEE value in the industry is significantly lower, around 50% to 60% in Northern Europe. This level is confirmed by research from Chalmers University on productivity in the manufacturing industry (Gopalakrishnan, Subramaniyan, and Skoogh, 2022) and is also found in previously published OEE research (Ljungberg 1998; Ingemansson 2004). It also aligns with Good Solutions' own customer data from the 300+ factories measuring in the platform, looking at those factories that start measuring before improvement work has begun.

This means two things. First, most factories have huge potential for improvement without needing new equipment or new investments. The difference between 55% and 65% OEE corresponds to 18% more production from the same machine park. Second, the chase for 85% often becomes counterproductive. Production managers inflate the figure by discounting time that "doesn't count," such as changeovers, planned maintenance, and planned stops. The result is a figure that looks good but does not reflect real efficiency.

The question "What is a good OEE value?" has no universal answer. It depends on the industry, production type, how the metric is defined internally, and what you are comparing it against. A more useful approach is to compare the factory with itself over time and focus on the direction of trend, rather than an absolute figure taken from a textbook.

Different ways to measure OEE

There are four common levels for how OEE data is collected, from simple to more advanced.

Manual collection. Operators register stops and production by hand, often on paper or in spreadsheets. It is easy to start with, but the data is often incomplete and difficult to trust over time. Micro-stops are rarely captured.

Semi-automated collection. The machine reports production and stops automatically, while the operator complements this with reasons for downtime. This is often the most valuable level, as it combines reliable machine data with the operator's knowledge of why the stops occur.

Automated collection from the machine's control system. Data is retrieved directly from the PLC or similar. It provides high precision in times and quantities but cannot independently determine the cause of a stop.

Integrated collection with ERP, MES, and maintenance systems. OEE data is linked to orders, items, scheduling, and maintenance. This provides a more complete picture but requires integrations to work and data quality to be high at every stage.

Most factories that succeed with OEE often use a combination: automated collection of times and quantities, complemented by the operator's categorization of causes. This ensures both precision and understanding.

What a good OEE system does, beyond calculating

An OEE system that only shows a number rarely helps a factory move forward. A system worth the investment highlights losses in real-time, while the stop is ongoing, so the right person can take action immediately. It supports the operators' work by making it easy to classify stops and register scrap. It enables deep loss analysis, so OEE can be broken down by line, article, shift, cause, and time. And it integrates with other operations, so OEE data, quality data, maintenance data, and energy data can be viewed together.

It is these characteristics, not the length of the feature list, that determine whether a system creates value in daily operations. Simply put, it allows you to make better decisions faster and move from finding losses in production to implementing the right improvements and securing results over time.

How Good Solutions works with OEE

The platform from Good Solutions is built on the principle that OEE should move from reporting to action. Measurement is the means, improvement is the goal. The platform combines machine connectivity, operator tools, dashboards, timelines, reports, quality management, maintenance, andon, energy, and operational implementation into one cohesive tool. Today, the platform supports over 300+ factories, from individual production lines to global corporations.

Machine connection is done via common standards like OPC UA or through a proprietary IoT solution, such as RS IoT 4G from Good Solutions, which collects operating data from various sources. For example, RS IoT 4G can analyze machine vibrations, current consumption, other digital signals, or a standard 24 V connection. It works on both new and old machines and requires neither a local network nor IT support to get started. The data is sent directly to Good Solutions' cloud service via the industrial 4G network. This allows even older equipment to provide reliable OEE data, which is a prerequisite for improvement work to encompass the entire factory.

Sibbhultsverken was able to improve OEE by 19.4% in 12 months. At Barilla Wasa, net production increased by 15% while CO₂ consumption decreased by 28%.

These types of results are not built by OEE measurement in itself, but by the systematic improvement work that the platform makes simple to execute.

Read more about how others have increased their factory productivity

FAQ

What is a good OEE value?
It depends on the industry, production type, and how the metric is defined internally. The industry average in Northern Europe lies between 50 and 60%. The most important thing is not the figure in absolute terms, but the direction over time and what the loss analysis shows. Comparing OEE against the factory's own history usually yields more value than comparing against external benchmarks.

Is 85% OEE really world-class?
It is a widespread belief but in practice an abstract reference point. Few factories reach 85%, and those that report it have often defined away a large portion of the time. A more useful goal is to focus on the losses the factory actually experiences and improve OEE incrementally based on actual figures.

How do you calculate OEE for a shift?
Availability = run time in the shift ÷ planned production time for the shift. Performance = (actual production × ideal cycle time) ÷ run time. Quality = good units ÷ total units produced. The three are multiplied. The central aspect is that definitions are consistent over time. Otherwise, it is impossible to compare figures between shifts.

What are the 6 big losses?
They are breakdowns, setups/adjustments, idling and minor stops, reduced speed, defects in normal production, and startup defects. The first two reduce availability, the middle two affect performance, and the last two impact quality. Micro-stops are included in the idling and minor stops category within the six big losses and normally affect the performance component of OEE. They can be tracked separately in the analysis to highlight recurring issues, but do not constitute a seventh category in the model.

Do we need a separate OEE system, or is our ERP enough?
ERP systems are built for business processes, meaning orders, inventory, finance, and planning. They rarely have real-time data, machine connectivity, or the operator tools required for meaningful OEE work. A dedicated OEE system is used alongside the ERP and integrated with it. The common division is that the ERP keeps track of what is produced and the OEE system keeps track of how it is produced.