Overall Equipment Effectiveness (OEE): how to measure and improve equipment efficiency ​

For any organization that wants to remain competitive, improving operational efficiency is a priority. In this context, it is imperative to understand how effectively equipment is being used. This is precisely where OEE (Overall Equipment Effectiveness) comes in — a metric that measures equipment efficiency, identifies losses, and guides teams to areas of most significant impact.

In this article, the definition of OEE, its calculation process, and how it can be used on a day-to-day basis to improve operational results are discussed. Additionally, the main factors that influence this metric and the most effective strategies for its continuous improvement are also addressed.

What is OEE, and why does it matter?

In the context of operational excellence, the ability to quantify the performance of production systems is essential. OEE is a widely recognized metric that provides a structured summary of how effectively equipment is being utilized.

Understanding OEE

OEE (Overall Equipment Effectiveness) is a comprehensive indicator that measures the overall effectiveness of a piece of equipment, combining three key dimensions: availability, performance, and quality. Each of these dimensions represents a distinct category of operational losses, allowing for a comprehensive analysis of an asset’s performance.

The OEE value is expressed as a percentage. It reflects the degree of effective use of a piece of equipment compared to its maximum theoretical potential, i.e., without stoppages, speed losses, or defects. This metric is commonly used in both process and discrete manufacturing environments. While the core concept of OEE remains consistent, the calculation method may vary depending on the measurement practices adopted by each organization.

Why OEE is critical in manufacturing

In a competitive environment where efficiency is crucial, OEE serves as a vital structural indicator of equipment performance. It enables organizations to assess how effectively their production assets are being used, supporting the systematic identification of inefficiencies and guiding targeted improvement efforts.

In the manufacturing industry, OEE is particularly relevant because it allows to:

• Accurately quantify the primary sources of operational loss, categorizing them into specific types.
• Track the effectiveness of continuous improvement projects, providing an objective metric to measure the results of initiatives such as Kobetsu Kaizen and SMED.
• Support both strategic and tactical decisions in areas like production planning, maintenance management, resource allocation, and evaluating investments in new equipment or technologies.

By incorporating OEE into daily management practices, organizations gain a clear view of their production system efficiency, encouraging team alignment and fostering a culture of operational excellence. Consistent application of OEE directly supports cost reduction, productivity gains, quality improvements, and on-time delivery performance.

How to calculate OEE

Calculating OEE reveals the efficiency of equipment utilization in relation to its full potential. This metric helps break down operational losses and guides improvement actions based on tangible data.

OEE calculation formula

The OEE formula is expressed as follows:

OEE = Availability × Performance × Quality

Each factor represents a specific dimension of operational efficiency:

• Availability measures the percentage of time that the equipment was actually running compared to the time planned for production.
• Performance evaluates whether the equipment is operating at its ideal speed by comparing actual output to theoretical output.
• Quality indicates the proportion of good units produced compared to the total output.

All components are expressed as percentages, and the final result reflects the overall equipment efficiency.

How to calculate each of the three factors

While the general OEE formula is common in production, the specific definitions of the time metrics used in each OEE component can vary among organizations. A common variation involves how opening time is defined.

Figure 1 – Times involved in calculating OEE

Many companies define opening time as the total time allocated for production, subtracting only the time lost due to a lack of demand. In this approach, all scheduled pauses—such as lunch breaks, training sessions, preventive maintenance, or other planned downtimes—are included in the opening time. This method assumes that all such periods are potential areas for improvement and therefore should be included in the OEE calculation as efficiency opportunities.

Other organizations choose to exclude these planned downtimes from the opening time in the OEE calculation. This approach excludes those losses from the scope of continuous improvement, as they no longer directly affect the indicator.

Selecting a method should be a deliberate decision aligned with the organization’s operational management goals and its maturity in fostering a culture of improvement. Below is a detailed explanation of how each of the three OEE components—availability, performance, and quality—is calculated.

1.Availability:

Availability represents the proportion of time that the equipment was actually in operation compared to the time it was planned for production.

Available time refers to the total planned production time minus any equipment stoppages, such as breakdowns or setups.

2. Performance:

Performance measures how efficiently the equipment operated in terms of speed, comparing actual output to the ideal production assuming optimal cycle time.

Microstoppages, reduced cadence, or unstable process conditions are examples of losses that negatively affect performance.

3. Quality:

The quality factor measures the proportion of output that meets compliance standards—i.e., the number of good parts relative to total production.

This indicator measures the impact of losses resulting from defects and rework. It thus reflects the efficiency of the operation in delivering compliant products within the defined quality standards.

Practical example of calculating OEE

Below is a practical example of calculating OEE. Let’s consider a production shift lasting 8 hours (480 minutes), with a 30-minute pause due to lack of demand. The planned production time—or opening time—is therefore 450 minutes.

Availability calculation:

During the shift, the following downtimes were recorded:

• Setup: 60 minutes
• Breakdowns: 15 + 20 minutes = 35 minutes
• End-of-shift: 10 minutes

The total time lost due to unavailability was therefore 105 minutes.

The time available for actual production is calculated as follows:

Available time = 450 – 105 = 345 minutes

Figure 2 – Opening time vs available time

Availability is calculated using the following formula:

Performance calculation:

Assuming a total output of 1,000 units and an ideal cycle time of 20 seconds per part, the ideal production time is calculated as:

Productive time = 1 000 × 20 = 20 000 seconds = 333,3 minutes

Figure 3 – Available time vs. productive time

Performance is calculated using the formula:

Quality calculation:

From the total output of 1,000 parts, 945 units were found to be compliant (i.e., free from defects). Assuming an ideal cycle time of 20 seconds per unit, the adequate time spent producing good parts is calculated as:

Effective time = 945 × 20 = 18 900 seconds = 315 minutes

Figure 4 – Productive time vs. effective time

Quality is calculated using the formula:

OEE calculation:

The OEE for the shift analyzed is obtained by multiplying the three previous factors:

OEE = Availability × Performance × Quality = 76,7% × 96,6% × 94,5% = 70%

or

This example illustrates how OEE can be used to objectively identify the most critical sources of operational loss and guide data-driven improvement action plans.

Types of losses impacting OEE

As previously discussed, the operational losses that affect OEE fall into three main categories: availability, performance, and quality. Each of these dimensions involves different types of losses that reduce equipment effectiveness and compromise overall operational performance.

Availability losses

Availability losses refer to periods when equipment is stopped during scheduled production time. These losses include:

• Unplanned downtime: breakdowns, technical failures, and unavailability of operators or materials.
• Planned downtime: setups, tool changes, cleaning, and preventive maintenance.

Other planned downtimes—such as breaks, training sessions, meetings, or annual maintenance—also count as availability losses if they are included in the opening time, depending on the methodology adopted.

Performance losses

Performance (or speed) losses occur when equipment is running but not at its ideal speed. Although time is being used, the output is lower than expected. These losses include:

• Reduced speed: operation below the rated cadence.
• Microstoppages: frequent short interruptions (e.g., part misalignment, minor adjustments).
• Empty cycles: cycles without actual production.

These losses represent the difference between actual production and theoretical production at maximum speed, affecting performance even when there is no downtime.

Quality losses

Quality losses occur when the equipment produces units that fail to meet compliance requirements, resulting in scrap, rework, or rejected items. These include:

• Startup waste (during machine warm-up or adjustment periods).
• Production defects.
• Reworked parts that require extra time without creating additional value.

These losses reduce the volume of compliant production, directly affecting the quality component of the OEE, since part of the production effort does not result in value delivered to the customer.

Strategies for improving OEE

Improving OEE on a sustained basis requires more than solving specific problems. It is essential to adopt systematic practices for measuring, analyzing, and addressing the root causes of losses. Combining continuous monitoring with structured approaches such as Kobetsu Kaizen makes it possible to turn data into specific improvement actions.

Systematic measurement and continuous monitoring

OEE improvement begins with systematic measurement and daily monitoring of performance indicators. Only with consistent, visible, and shared data can a culture of accountability, loss focus, and proactive correction take hold. To support this, the following key elements should be implemented:

• Team boards with visual indicators: Every team should have a physical or digital board located in the work area that displays key operational performance indicators, including OEE and its three components. These boards should be updated regularly, include clear targets, use visual coding (e.g., color signals or traffic lights), and provide space for recording anomalies and action plans.
• Frequent, standardized meetings: Indicator review should take place during structured daily meetings. These sessions allow teams to analyze data, identify causes, and define corrective actions. When needed, they also serve as a trigger to initiate improvement workshops. This routine strengthens accountability, promotes direct engagement with performance, and prevents the accumulation of unresolved losses.

This practice enables teams to identify opportunities for improvement, make data-driven decisions, foster collaboration, and take ownership of continually enhancing operational performance.

Kobetsu Kaizen: structured problem solving

Kobetsu Kaizen is a widely used methodology in Kaizen workshops for improving OEE. Based on a 9-step process, it guides teams from challenge definition through to the consolidation of improvements, supporting a complete improvement cycle. The nine steps of Kobetsu Kaizen are:

1. Define the challenge.
2. Verify the current state using data.
3. Set the target state using SMART goals.
4. Investigate root causes.
5. Design solutions targeting the identified causes.
6. Test the solutions.
7. Implement the actions by defining the responsible parties and setting deadlines.
8. Confirm results and standardize the new practices.
9. Consolidate and pursue continuous improvement.

This approach ensures that solutions are both practical and sustainable, while also promoting direct engagement from frontline teams in identifying and eliminating losses using real data.

Depending on the type of loss identified, other methodologies may also be applied, such as:

• SMED, when reducing setup times is necessary.
• Quality management tools and Six Sigma, in cases of losses related to defects, rejections, or rework.
• Other TPM (Total Productive Maintenance) methods, such as autonomous maintenance or predictive maintenance, for frequent stoppages or equipment reliability issues.

Kobetsu Kaizen serves as a key tool for structuring improvement initiatives that focus on root causes, delivering measurable, direct impact on OEE.

Technologies and tools supporting OEE

The digitalization of industrial processes has significantly enhanced organizations’ ability to measure, analyze, and improve OEE. Supportive technologies enable the automation of data collection, enhance measurement reliability, and facilitate real-time decision-making.

Key tools and technologies that support OEE include:

• MES (Manufacturing Execution Systems): These systems automate the collection of production data and integrate with both equipment and ERP systems to generate real-time indicators such as availability, performance, and quality.
• Sensors and IoT (Internet of Things): These devices collect data directly from machines (e.g., stoppages, speed, temperature), enabling continuous and precise monitoring of equipment status.
• Visual dashboards and digital boards: These tools help teams easily visualize OEE indicators and any deviations, allowing quick response to anomalies.
• Advanced analytics and artificial intelligence solutions: These technologies help identify patterns of loss, predict failures, and support predictive maintenance decisions, directly improving availability and performance.
• OEE software: These platforms integrate many of the above functionalities, offering a centralized solution for real-time monitoring and optimization of equipment efficiency.

Technology adoption should align with operational goals and the organization’s level of digital maturity, ensuring that collected data is transformed into actionable insights and sustained performance improvements.

Conclusion: OEE as a driver of industrial competitiveness

In an increasingly competitive industrial landscape, systematically measuring and improving OEE can act as a catalyst for operational transformation. More than identifying losses, OEE creates process transparency, encourages critical thinking among teams, and aligns the entire organization around delivering tangible value. Its effectiveness lies in the simplicity of the formula, combined with disciplined execution: measuring accurately, analyzing methodically, and acting on the real causes of deviation.

When combined with technologies such as IoT sensors, analytics platforms, and decision-support systems, OEE evolves from a reactive metric to a predictive tool that guides both operational and strategic decisions.

The real potential of OEE lies in embedding it into daily management—displayed on team boards, reviewed in meetings, incorporated into decisions, and reflected in improved process efficiency.

Do you still have questions about OEE?

TEEP vs. OEE: What are the differences and similarities?

OEE (Overall Equipment Effectiveness) and TEEP (Total Effective Equipment Performance) are both metrics that measure equipment effectiveness, but they differ in scope. Each is based on the same three core factors—availability, performance, and quality—and both serve as key tools for identifying operational losses and guiding improvement efforts. The key difference lies in the time frame used.

OEE measures effectiveness during scheduled production time. It evaluates performance only within the periods when equipment is planned to operate, excluding non-production time (such as weekends, holidays, or unscheduled shifts). TEEP, on the other hand, uses total available time as its reference—24 hours a day, 7 days a week—regardless of production scheduling. Thus, TEEP enables understanding of the maximum potential use of a piece of equipment, including opportunities to increase the load or optimize planning.

What is a good benchmark for OEE?

There is no universal benchmark for OEE, as it depends on several factors, including the industry, type of production process, level of automation, operational maturity, and the method used to calculate the metric. As a general guideline, an OEE above 85% is considered excellent. However, this reference should be used cautiously.

What matters most is using OEE as a tool to identify and continuously eliminate real losses. Each organization should define its own targets based on its operational context and track progress over time.