know-how
What is OEE in manufacturing? Definition, formula, calculation, benchmarks, and optimization with CMMS, lean, and TPM
Definition and meaning of OEE in manufacturing
Overall Equipment Effectiveness (OEE) is a key metric for evaluating the productivity and efficiency of production equipment. It is used in the context of Lean Production, Kaizen, and Total Productive Maintenance (TPM) to make waste visible and identify opportunities for optimizing production processes.
OEE measures the actual output of a machine compared to its theoretical maximum. The metric helps companies make informed decisions about equipment utilization, production planning, and maintenance strategies.
How is OEE calculated?
OEE is usually expressed as a percentage. It is composed of the three factors availability, performance, and quality. Each factor helps identify and analyze waste in the production process.
Availability factor
Availability is calculated as the ratio of actual operating time to planned production time:
$$
\text{Availability} = \frac{\text{Actual Operating Time}}{\text{Planned Production Time}} \times 100\
$$
- Actual operating time is the time during which a machine is productively running, minus unplanned downtime, maintenance, and changeover activities
- Planned production time includes all periods when a machine is scheduled and ready for production.
Performance factor
The performance factor measures how close the production is to the maximum possible output. The theoretically possible number of units at optimal speed is compared with the actual output:
$$
\text{Performance} = \frac{\text{Actual Output}}{\text{Maximum Possible Output During Runtime}} \times 100\
$$
Quality factor
The quality factor indicates the percentage of defect-free products. Good parts are determined by subtracting reworked and scrap parts from total production:
$$
\text{Quality}=\frac{\text{Good Parts}}{\text{Total Parts Produced}}\times 100\
$$
Note: The calculation of the quality factor (Good Parts / Total Parts) applies primarily to discrete manufacturing, where products are counted in units. In process industries, the quality factor is typically calculated based on yield (actual vs. theoretical output) or specification compliance (batches within vs. outside tolerance limits).
Overall OEE formula
OEE is obtained by multiplying all three factors:
$$
\mathrm{OEE} = \text{Availability} \times \text{Performance} \times \text{Quality}
$$
OEE explained with a simple example
A production plant schedules a daily shift of 480 minutes. Due to changeovers and downtime, the equipment runs effectively for 390 minutes. During this time, 1,000 parts could be produced at optimal speed. In fact, 850 were manufactured, 810 of which were good parts.
The three factors are calculated as follows:
- Availability = 390 min / 480 min = 0,8125 (81,25%)
- Performance = 850 units / 1,000 units = 0,85 (85%)
- Quality = 810 good parts / 850 produced parts = 0,95 (95%)
Result:
- OEE = 0,8125 × 0,85 × 0,95 = 0,656 (65,6%)
During the planned daily shift, the equipment was productively utilized at about 66%, considering downtime, reduced speed, and quality losses
What is a good OEE value in practice?
An OEE value of 100% is theoretically achievable, but it would mean that equipment runs without any downtime, at maximum speed, and produces only defect-free parts. In reality, such a value is nearly impossible to achieve, as every production process inevitably incurs unavoidable losses, such as changeovers, minor stops, or quality deviations.
In practice, the following OEE values (benchmarks) are considered optimal:
1
- 85% OEE – Considered a desirable, achievable target in discrete manufacturing (e.g., automotive, electronics assembly) for optimized processes.
- 75% OEE – Often considered excellent performance in continuous production, such as the food and beverage industry, where frequent changeovers, cleanings, and quality checks reduce availability.
These benchmarks are highly context-dependent. Differences in plant layout, product type, degree of automation, and maintenance strategy mean that an OEE of 60% may already be very good in some industries. In contrast, much higher targets are realistic in others.
To improve OEE and reach higher performance levels, it is essential to systematically identify and reduce the causes of losses. In the next section, we examine the most common types of losses and their impact on availability, performance, and quality.
Common causes of OEE losses
OEE losses can be divided into three main categories, directly linked to the OEE factors Availability, Performance, and Quality. This classification follows the “Six Big Losses” defined in Total Productive Maintenance (TPM).
Technical downtime losses
Technical downtime losses negatively affect the availability factor.
- Equipment and machine failures: Unplanned, technically caused stoppages significantly reduce operating time. The time to restart depends heavily on the Mean Time to Repair (MTTR). The shorter the MTTR, the faster the equipment can return to production after failure.
- Changeover and setup losses: Time required to change over or set up equipment between production runs reduces available production time.
- Missing material: Material shortages, components not supplied on time, or logistics disruptions cause stoppages that shorten planned production time.
- Maintenance, inspection, cleaning: Necessary activities such as planned maintenance or cleaning create scheduled downtime, counted as availability loss in the OEE.
Organizational speed losses
Organizational speed losses negatively affect the performance factor.
- Short stops and idling: Short interruptions, e.g., minor stoppages, operator changes, or staff shortages, cause repeated production breaks and reduce effective output.
- Speed losses: Operation below optimal cycle time, e.g., for process safety, wear, insufficient lubrication, or to avoid disruptions, reduces actual output.
Defect losses
Defect losses negatively affect the quality factor.
- Process defects: Deviations from the target process cause scrap, rework, or reduced product quality.
- Ramp-up losses: Reduced output when ramping up production or after changeovers until the process is running smoothly leads to increased scrap or lower production output.
These loss types occur in almost all production environments. Their impact depends on plant layout, processes, and organization. Targeted analysis of these losses enables effective OEE improvement measures.
In practice, methods from Lean and TPM are primarily used, such as changeover time optimization (Single Minute Exchange of Die, SMED), workplace organization and quality management (5S and TQM), as well as autonomous and preventive maintenance. Reducing the Mean Time to Repair (MTTR) plays a key role and can be supported by modern maintenance software (Computerized Maintenance Management Systems, CMMS)
.
Methods to improve OEE
Improving OEE requires a systematic approach that addresses the causes of availability, performance, and quality losses. While Lean and TPM methods create the organizational and technical foundation, the use of digital maintenance systems plays a central role today.
Lean and TPM methodology
Changeover time optimization (SMED): Structured changeover processes reduce machine downtime, directly increasing availability. For example, separating internal and external setup steps: tasks previously performed during machine downtime, including tool preparation, material change, calibration, etc., are moved to running time wherever possible. In practice, this can be achieved with standardized tool carts, quick-clamping devices, or pre-defined material kits.
Workplace organization (5S) and Quality Management (TQM): The 5S method (Sort, Set in order, Shine, Standardize, Sustain) organizes workplaces so that tools, materials, and information are always clearly assigned and easily accessible. Example: Tools arranged in fixed holders at the workstation reduce search time and minimize operator errors.
TQM integration: In Total Quality Management (TQM), quality checks are integrated into the process. Example: Inspection stations directly on the production line detect deviations early, reducing scrap and rework.
Autonomous and preventive maintenance: In TPM, operators carry out basic maintenance and inspection tasks themselves. Example: Daily visual inspections, lubrication, or machine cleaning prevent small disruptions and extend component life.
Preventive maintenance includes scheduled servicing based on fixed intervals or operating cycles. Example: Replacing wear parts at defined cycles prevents unplanned downtime. Both approaches aim to increase availability, reduce MTTR, and avoid follow-up costs from failures.
Use of maintenance software (CMMS)
Maintenance software (Computerized Maintenance Management Systems, CMMS) is a key lever to improve OEE because it directly affects the three influencing factors: availability, performance, and quality. Properly integrated into technical and organizational processes, it reduces downtime, shortens response times, and helps avoid unplanned failures.
Typical CMMS functions and their direct contribution to OEE
- Failure reporting and processing: Failures can be reported directly at the machine via QR codes or mobile apps. They are automatically logged, prioritized based on equipment criticality, and assigned to maintenance personnel. This reduces the Mean Time to Acknowledge (MTTA) and improves the Mean Time to Repair (MTTR).
- Preventive maintenance: Maintenance teams can schedule tasks based on defined time intervals. Regular inspections prevent unplanned failures and stabilize equipment availability.
- Condition-based maintenance (Condition Monitoring): In combination with IoT sensors, CMMS continuously monitors critical machine parameters. Deviations from normal operation automatically trigger maintenance or failure tickets, allowing early intervention. This reduces failure risks and shortens downtime.
- Knowledge management and autonomous maintenance: Digital instructions, checklists, and inspection reports support production operators in independently carrying out smaller maintenance tasks. This speeds up fault resolution without requiring immediate technician involvement. CMMS also supports 5S and TQM processes.
- Mobile maintenance: CMMS apps give technicians mobile access to machine histories. Integrated collaboration functions involve internal experts or external machine suppliers directly in the process as needed. This saves in-plant travel time, reduces queries, and accelerates recommissioning.
- Providing solution knowledge with AI: AI-powered features expand the CMMS, helping analyze fault patterns and suggest appropriate solutions. This speeds up diagnosis and repair, positively impacting MTTR.
In the “Industrial Maintenance Report” conducted by Plant Engineering (2021), 203 maintenance professionals responded to maintenance strategies and the benefits of using tools. 60% of the participants stated that the use of a CMMS improves productivity and has a positive effect on OEE.2 In addition, 75% reported benefits for cost-effectiveness, and around half also cited improvements in overall efficiency and safety.
Economic and organizational benefits of OEE optimization
Combining traditional TPM methods with powerful maintenance software enables companies to systematically increase value-adding operating time. CMMS software reduces OEE losses by standardizing maintenance processes and accelerating response to failures. Production operators can be actively involved in troubleshooting, further shortening downtime.
Higher OEE not only boosts productivity but also lowers unit costs, as either more can be produced in the same time or the same output can be achieved in less time. In addition, it ensures order schedule reliability through stable and more predictable production flows.