OEE vs. TEEP: What’s the difference?

Breakdowns, equipment failure, outages and other shop floor disruptions can result in big losses for an organization. Production managers are tasked with ensuring that factories and other production lines are getting the most value out of their equipment and systems.

Overall equipment effectiveness (OEE) and total effective equipment performance (TEEP) are two related KPIs that are used in manufacturing and production environments to help prevent losses by measuring and improving the performance of equipment and production lines.

OEE is a metric used to measure the effectiveness and performance of manufacturing processes or any individual piece of equipment. It provides insights into how well equipment is utilized and how efficiently it operates in producing goods or delivering services.

OEE measures the equipment efficiency and effectiveness based on three factors. The OEE calculation (link resides outside of ibm.com) is simple: availability x performance x quality.

TEEP is also a metric used in manufacturing and production environments to measure the overall efficiency and effectiveness of equipment or a production line. It includes all the potential production time, including planned and unplanned downtime.

TEEP is calculated by multiplying four factors (link resides outside of ibm.com): availability x performance x quality x utilization.

The main difference between these two metrics is that while OEE measures the percentage of planned production time that is productive, TEEP measures the percentage of all time that is productive. 

It’s important when making these calculations of time to use the right terminology. Here are a few common ways to measure time within a production context:

• Unscheduled time: Time when production is not scheduled to produce anything (as opposed to “scheduled time”).
• Calendar time: The amount of time spent on a job order up to its completion.
• Total operations time: The total amount of time that a machine is available to manufacture products.
• Ideal cycle time: The theoretical fastest possible time to manufacture one unit.
• Run time: The time when the manufacturing process is scheduled for production and running.

OEE primarily focuses on the utilization of available time and identifies losses due to availability, performance and quality issues. It helps identify areas for improvement and efficiency optimization.

TEEP, on the other hand, provides a broader perspective by considering all potential production time, including planned downtime for preventive maintenance or changeovers. It aims to measure the maximum potential of the equipment or production line. 

OEE is typically used to measure the performance of a specific piece of equipment or a machine. It helps you understand how effectively equipment is being utilized during actual production time. OEE is commonly used as a benchmarking tool to track and improve equipment performance over time. It helps identify bottlenecks, areas for optimization and improvement initiatives.

TEEP is used to measure the overall performance of an entire production line or multiple pieces of equipment working together. It provides a holistic view of the effectiveness of the entire system. If you are interested in understanding the maximum potential performance of your production line, including planned downtime for maintenance, changeovers or other scheduled events, TEEP is the performance metric to use. TEEP can be helpful in production capacity planning and determining the capabilities of your equipment or production line.

1. Start with OEE analysis: Begin by calculating the OEE for individual machines or equipment within your production line. OEE analysis helps pinpoint the causes of losses and inefficiencies at the equipment level. A digital asset management platform can provide real-time data to help with this calculation.
2. Identify bottlenecks: Use OEE data to identify bottlenecks or areas where equipment performance is suboptimal. Look for machines with lower OEE scores and investigate the underlying issues. This can help you prioritize improvement efforts and target specific machines or processes that have the most significant impact on overall performance.
3. Evaluate TEEP for the entire line: Once you have assessed the OEE for individual machines, calculate the TEEP for your entire production line. TEEP takes into account all potential operating time—including planned and unplanned downtime—providing a broader perspective on the overall performance of the line.
4. Compare OEE and TEEP: Compare the OEE and TEEP data to gain insights into the gap between actual performance and the maximum potential performance of the production line. Identify the factors contributing to the difference between the two metrics, such as scheduled maintenance, changeovers or other planned downtime. This comparison can help you understand the overall efficiency and effectiveness of the production line.
5. Address common issues: Analyze common issues identified through OEE and TEEP analysis and devise strategies to address them. This may involve improving machine reliability, procuring new equipment, integrating continuous improvement methodologies, reducing setup or changeover times, enhancing product quality or optimizing maintenance management. Implementing targeted improvement initiatives can help bridge the performance gap and maximize the overall equipment performance.
6. Track progress over time: Continuously monitor and track both OEE and TEEP metrics over time to assess the effectiveness of your improvement efforts. Regularly evaluating these metrics allows you to measure the impact of implemented changes and identify new areas for optimization.

By combining OEE and TEEP, you can conduct a comprehensive analysis of current equipment performance at both the individual-machine and production-line levels. This integrated approach provides a deeper understanding of performance factors, helps prioritize improvement efforts, and maximizes the overall effectiveness and efficiency of your manufacturing operations, allowing production managers to achieve higher throughput and maximum uptime.

IBM Maximo is enterprise asset management software that delivers a predictive solution for the maximization of equipment effectiveness. Maximo is a single, integrated cloud-based platform that uses AI, IoT and analytics to optimize performance, extend the lifecycle of assets and reduce the costs of outages. 

Take a tour to see how Maximo can achieve OEE improvement while reducing the operations costs of overtime, material waste, spare parts and emergency maintenance.