Managing a facility requires knowledge of two worlds: there’s the tangible, real world of noisy machinery and messy repairs to keep things running smoothly. There’s another world going on behind the scenes, however, one of numbers, spreadsheets, and careful calculations that serve as the foundation for any effective operation.
Overall equipment effectiveness (OEE) is perhaps the most famous formula in facilities management. Developed in the 1960s to evaluate the effectiveness of manufacturing operations, OEE is a metric designed to measure the improvement potential of a production process with one simple number.
Understanding the Three Metrics of Overall Equipment Effectiveness
How does OEE work? Essentially, it breaks the performance of a manufacturing unit into three separate but measurable components: Availability, Performance, and Quality.
Availability represents the percentage of scheduled time that the operation is available to operate. Essentially, it’s a pure measurement of uptime that’s not effected by the aforementioned other components. To calculate availability for OEE purposes, simply divide your actual operating time by the time you had planned to operate.
For example, a given plant is scheduled to run for an eight hour shift with a thirty minute break, or 450 minutes. Thanks to an hour of unscheduled downtime, the actual runtime winds up being 390 minutes. This results in an 86.6% availability rating.
Performance, also known as “productivity” or “process rate,” quantifies the speed at which a facility runs as a percentage of its designed speed. Essentially, it will measure how much waste you are generating by not running your operation at optimal speed.
The formula is more complex than availability: in order to calculate performance, you multiply the number of parts produced by the ideal cycle time, or standard rate to produce parts, and divide the product by the total operating time.
If the standard rate of a part being produced is 1.5 minutes per unit and your facility produces 242 total units during the shift, this results in a production time of 363 minutes. Divide that by the running time of our previous availability example and the result is a 93% productivity rate.
The final metric, Quality, is rather simple in comparison. Simply subtract the number of defective units from the number of units produced and divide the result by units produced. If a shift produces 242 units, 21 of which are defective, the quality result will be 91.3%.
Putting It All Together and What the Metrics Mean
Now that we have our three metrics, to determine our overall OEE we simply multiply the three together, giving us a rating of 73.6%. So how does that help your facility? It boils down to analysis.
Our availability is at 86.6%, so we know that 14.6% of our potential production was lost through unplanned downtime. With this insight, we can closely scrutinize our numbers and practices to find opportunities for improvement. Maybe we can speed up the setup of a particular machine, or schedule more planned downtime for preventive maintenance.
Either way, OEE provides an illustrative datapoint that gives you an idea about what’s hurting your production and offers an objective goal to aim towards. It allows you to identify threats and opportunities and, eventually, make more effective decisions.
OEE for All
In the past, OEE was more or less exclusive to large-scale operations and huge corporations, thanks to the expense and complexity involved in collecting all the requisite data. In recent years, as the tools available to small and mid-sized businesses became less costly , OEE has become more affordable for facilities of all sizes.
While a good CMMS program would allow integration to OEE software, most if not all CMMS programs are not designed to store all of the values required for OEE calculations, nor run the equations. However, a good CMMS program should absolutely contain several tools that positively impact reliability and machine uptime, which will of course positively impact OEE. Those tools include:
- Planning and scheduling
- PM scheduling and auto-generation of work orders
- Detailed analysis of parts-related downtime
- Failure analysis
- Predictive and Condition-based tasks – possibly auto-generated from meter / PLC data
- PLC / SCADA system integration, and auto-generated work orders
- A field to capture at least some of the OEE data, by machine
Take advantage of your CMMS program to positively impact your OEE results.