OEE Software is used to calculate and measure overall equipment effectiveness (OEE), a manufacturing metric used for driving continuous improvement by identifying why a given machine varies in performance over time. It captures the top three sources of manufacturing productivity: machinery availability, performance, and quality. Because OEE provides a consistent way to measure the effectiveness of a machine or process, it is considered a core manufacturing metric.
How is OEE Calculated?
What makes OEE a robust performance measure is that it factors in three variables to provide production teams with additional insights during different manufacturing circumstances. This powerful metric is actually simple to calculate:
OEE = Availability x Performance x Quality.
Let’s look closer at each of these factors.
Availability – The availability factor reports the percentage of scheduled time that the machine or process is available for production. This metric is used to measure uptime only. Seiichi Nakajima, the inventor of OEE, in his book Introduction to TPM: Total Productive Maintenance, designed the availability factor to exclude the effects of scheduled downtime events, performance, and quality. The analysis for defining the availability factor begins with the time a plant is available for production. From that figure, planned shutdown time needs to be subtracted, including when there’s not going to be a production run or scheduled downtime. Downtime loss should include events that stop production, such as material and labor shortages, equipment failures, and setup time. Setup time is included in the availability analysis because even though it is not possible to eliminate setup time, it is possible to reduce it. The formula is Availability = Actual Uptime / Scheduled Uptime.
Performance – The performance factor quantifies the speed that the machine or process produces parts compared to the at-spec or designed speed or standard cycle times for the machine. Seiichi Nakajima designed this metric to measure the speed that parts are produced without the influence of availability or quality. The performance metric can show a speed greater than 100%, but when used in the calculation, it must be capped at 100% to limit the effect on the percentage. The formula is: Performance = Total Parts Produced x Standard Cycle Time / Actual Uptime. In this calculation, the Total Parts Produced includes rejected parts.
Quality – In the context of OEE, the quality factor quantifies the machine or process yield of good quality parts as a percentage of all or total parts produced. Seiichi Nakajima designed this factor to be independent of availability or performance. The calculation is Quality = Good Parts / Total Parts Produced.
Benefits of OEE Software and Practical Uses
By using real-time data to calculate overall equipment effectiveness and keep it current, manufacturers can gain valuable insights into how they can continuously improve production performance. The following are four of the most common:
- Reduce production costs and waste. The combination of real-time production monitoring and OEE software enables manufacturers to continuously monitor production cycles and scrap by machine, ensure all production steps are executed, measure production times, and predict completion times. Real-time production monitoring data also helps to identify the factors that increase per-unit production costs and scrap. The resulting insights help in identifying potential areas to reduce unnecessary costs and waste as well as maximize equipment utilization.
- Improve machinery yield rates. OEE provides insights and benchmarks into how each machine and production line performs for every production job it’s assigned to work on. Seiichi Nakajima envisioned it as a metric that could catch variations in machinery performance when used to produce the same product over time. Smart manufacturing techniques developed since OEE was first created now provide the contextual intelligence needed to troubleshoot why yield rates vary. That’s why manufacturers don’t rely on OEE alone.
- Extend the useful life of machines and presses. When OEE is combined with additional metrics that use real-time production and process monitoring data, manufacturers can quickly see what jobs, materials, and tasks cause premature wear on a machine. Knowing what’s causing a machine to degradate and prematurely wear is invaluable. Using this knowledge, manufacturers can implement maintenance, repair, and overhaul (MRO) techniques to prolong the machine’s useful life, saving millions of dollars per year.
- Improve in-process and final product quality. Combining OEE with additional manufacturing metrics helps manufacturers find random versus deterministic factors that affect product consistency and quality. Keeping it in context as just one of many KPIs when troubleshooting quality problems across the shop floor—whether in-process or at the final product stage—is essential. Additionally, applying smart manufacturing techniques along can help to identify why machinery produces wide variations in availability, performance, and quality. This is a critical exercise to optimize the entire production process.
OEE scores are part of a core set of metrics and key performance indicators (KPIs) that manufacturers have on their dashboards to gain insights into machinery performance. In the purest sense, it is a metric to drive continuous improvement to the manufacturing process and identify why a given machine varies in performance over time. However, manufacturers are now using OEE software with data captured through newer technologies, such as real-time production monitoring and smart machinery, to automate trending analysis and discover new insights into how they can improve shop floor performance and manufacturing operations. Real-time data analyzed using OEE can also help predict breakdowns for each manufacturing machine or asset, expanding the original vision of the metric for 21st-century manufacturers.