How to measure the performance level of your factory?
The tricks of the trade
One of the most widespread KPIs (Key Performance Indicators) in production entities (whether SMEs or large enterprises) is the OEE (Overall Equipment Effectiveness) which measures the efficiency of production resources within a factory. It’s essentially an index made up of percentage points that sums up three very important concepts from the point of view of manufacturing production: the availability, efficiency and quality rate of an installation.
Although this KPI is applied within almost all production structures, different facets are often generated via technical calculation.
These different approaches, specifically adapted to each structure, often cause limits or misunderstandings, especially when conducting comparisons or benchmarking. This is why we believe it’s important to stick as closely as possible to the so-called “Academic Model”. This was born in 1975 from a treatise on “Total Productive Maintenance” (by Seiichi Nakajima): over the years, this theory has of course undergone a number of developments and changes in order to ensure that diagnoses are as accurate as possible.
The OEE identifies 6 macro-causes of “non-productivity”. Each of the “Big Losses” belongs to one of three categories:
1- Faults (downtime loss, DL)
2- Production rates (speed loss, SL)
3- Quality (quality loss, QL)
The OEE measurement consists of three steps:
OEE = Availability*Performance*Quality
Where:
- Availability= measures downtime losses
- Performance= measures speed losses
- Quality= measures quality losses
Let’s now take into consideration the individual factors involved in the OEE by simplifying the calculation concepts.
– Availability: percentage of actual running time compared to available time; the main downtime losses are: breakdowns, set-up and equipment
– Performance: percentage of parts produced compared to the theoretical capacity: when the installation is in operation, this corresponds to the actual speed compared to the nominal or registration plate speed; the main related “speed losses” are: speed reduction and micro-stops
– Quality: percentage of compliant parts in comparison to the total number of parts produced. The main “quality losses” are: rejects, rework and yield losses upon start-up.
The OEE, being a product of percentages, is a non-dimensional number that represents the numerical effectiveness of production resources. To date, the World-Class OEE is set at 85% (https://www.oee.com/world-class-oee.html) as a best-practice goal worldwide: from the very start, this figure has been based on analyses conducted on Japanese companies (Best-in-Class in the application of OEE) and on the practical experience of Seiichi Nakajima. Yet it’s important and essential to understand that you should not only focus on reaching this target but also assess your capability to improve your OEE.
So how can you improve it?
The OEE model, characterised by the three elements mentioned above, and being the basis of production management and monitoring policies, must draw on valid and precise data. The best solution for data collection and analysis? Having an MES system (Manufacturing Execution System, an information system for the management and control of production processes). MES software, in addition to automatic monitoring of production data, allows for there to be “real-time” processing of the results obtained, which then allows you to automatically convert them into KPIs of interest such as OEE. Furthermore, thanks to all the data collection and analysis, MES is therefore the basis on which all the predictive techniques, that help to prevent errors, are based: this has an impact on Big Losses by optimizing production.
