It is usually calculated by considering the three factors – performance, quality, and availability:
OEE (%) = Performance (%) × Quality (%) × Availability (%)
• Availability (No Stop Time)
It takes into account of unplanned stops in production, such as machine breakdowns; and planned stops such as scheduled maintenance, cleaning, and quality inspections.
• Performance (As Fast as Possible)
This applies when production doesn’t run at its full capacity either due to slow cycle or small stops such as poorly maintained or worn out machine, environmental factors, or operator issues such as misfeed, skill-level, or availability.
• Quality (Only Good Parts)
Quality takes into account defects as well as the reduced yield that occurs as a result of defective products. A 100% on quality score means there are no defect.
One of the common culprit for ineffective OEE measurement is due to the wrong threshold level set by the managers that has little to do with real productivity in manufacturing operation, hence assessing obtained result wrongly. By measuring the right level of OEE, manufacturers can gain insights on how to systematically identify and eliminate on losses, improve on machine performance and productivity, hence able to achieve goals like cost reduction, quality improvement, capacity and efficiency optimization that allows for more stable and reliable production output.
When measuring OEE standards at your manufacturing plant, focus your assessment first on the equipment that brings an impact on your manufacturing upstream and downstream. When you can improve the performance of it, you will not only be able to smooth out the production process and produce better product quality, but also significantly reduce downtimes and repair costs.
There are different measurement standards for different production equipment & industry. It is important for manufacturers to know which matters the most to the customer values so KPIs can be established to optimize on the equipment’s OEE. Depending on the value your business is delivering to customers, performance (speed) may be the main consideration whilst quality comes next as you produce commodity products in bulk where small defects don’t matter.
Following the trend of smart manufacturing, the Industrial Internet of Things (IIoT) are gradually adopted by many manufacturing companies as they are proven to be effective against downtimes and unplanned machine breakdowns by capturing real time information about machine condition through smart sensors that allows preventive and predictive maintenance to be carried out.
The planned and unplanned machine idle time are taken into consideration in OEE measurement as they affect factory’s productivity in big and small ways. With the real-time data fed by IIoT sensors, predictive maintenance can be performed by anticipating on machine condition through data analysis on machine performance to optimize on planned downtime and equipment lifespan. With more effective machine maintenance, OEE can be improved to achieving continuous improvement on productivity.
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