Most of my readers probably heard about the machine effectiveness measure of OEE, short for Overall Equipment Effectiveness. It is a composite measurement of the effectiveness of a piece of equipment, composed of three elements, i.e., availability, performance and quality. And I regularly see this indicator on the shop floor, posted near or on multiple machines. But when I try to engage a shop floor discussion on its actual use in improving operations, I am often disappointed. A blog post on four reasons why I dislike OEE for shop floor control and improvement.
1. OEE Hampers Learning and Improvement
As already mentioned, Overall Equipment Effectiveness or OEE is not one measure, it is a composite measure. It is based upon three underlying measures, i.e., availability, performance and quality. Availability measures the ratio of operating time and planned opening time. It focuses on planned and unplanned losses like changeovers (planned) and breakdowns (unplanned). Performance focuses on speed losses and short stops and is the ratio between actual and theoretical output during the operating time. Quality, finally, is the ratio between good output and the actual output signifying losses related to rejects for instance.
Now when we show a composite figure based upon three other figures, clearly, it is very hard to understand what the actual voice of the process (VOP) is. What is a poor OEE telling us? I don’t know. You always must dig deeper. So, it means you always must track the individual values related to availability, performance and quality anyway. If not, OEE doesn’t teach us anything. Due to its composite nature, a stable OEE also does not imply a stable process. One effect can cancel out another. So, it doesn’t help us learn and improve.
2. OEE Scares Employees Away
I am a big fan of shop floor control by the team members themselves. How well a process is running should be answerable by the team itself. Not by some office analyst that needs to be called down to the shop floor to explain. I already blogged about this in my “Report In Syndrome” post here (http://dumontis.com/2015/03/daily-huddle-report-in-syndrome/).
But as OEE is a composite measure, and even its components subject to many rules on what event and time to allocate to which category in the OEE definition, associates are often put off by the complexity and unclear allocations typically part of the OEE measurement system.
Associates subsequently get lost, book events in wrong categories and, more generally, don’t really understand the figure in the end. They disconnect from it. Most of them have lost interest and don’t bother to review it anymore and consequently also don’t pay attention anymore to how to book time in the first place. At that moment, OEE has become “a thing management has asked us to do”. And it has lost its purpose, if it ever had one.
3. OEE Is A Local Measure
As already mentioned, the fact that you can show a “good” OEE figure as such, does not necessarily mean anything to the overall objectives of the value stream. It could be, but it isn’t necessarily so. We should never forget OEE is a local measure; a measure of a single piece of equipment. And yes, I understand you can even aggregate OEE across machines, departments, sites, … How wonderful, but what are you learning from it?
A high OEE in the end only means that you got more output from the machine in the reporting period. But whether it was output that was actually needed and in the right mix? OEE doesn’t tell you anything about how the result actually contributed to better flow, improved reliability, shorter lead times and lower costs. It is a local measure, not directly connected to your company objectives. Don’t forget this.
4. “World-Class OEE” Is A Fallacy
Sometimes I stumble upon companies that set OEE targets of around 80-85 percent, stating that these are world-class OEE levels. To achieve the set targets, sites and teams regularly try and game the system. They favor running larger batches and overproduction, thereby reducing changeover and startup losses, positively impacting the quality and availability components of the OEE indicator. Or they speed up the machine and book possible rejects as product awaiting decision, another version of the product (e.g., the spare part or private label version) or even, by definition, as good product until final inspection (maybe days later) finds possible defects. OEE figures therefore should always be taken with a few grains of salt.
As often is the case, the moment you set an objective or a benchmark for a certain indicator such as the OEE, the indicator will fail to fulfill its initial purpose, i.e., serve as an instrument to understand the process and to enable its improvement.
This also impacts the use of OEE as a popular benchmark figure across machines and locations. OEE data should always be approached with the greatest suspicion. Furthermore, as I also argued in an earlier post here (http://dumontis.com/2016/07/muri-mura-kingman/) on the continued relevancy of Kingman’s formula, the level of utilization of a piece of equipment should be in line with the level of variation it experiences. If not, your lead time and inventories will be higher than what you have asked for. But hey, “great OEE you got there on your location… But what was it we were trying to achieve overall?”
Break-Down the OEE Measure
My advice therefore is to break up the composite OEE measure into its individual components. Shop floor measures, like those that relate to the operations on a machine, should be easy to collect, represent and interpret; by the team members on the shop floor. Focus therefore should be on the individual loss categories (the “waste”) that we try to eliminate. We all want less breakdowns and unplanned downtime, we all want to reduce stops and rejects. So, measure those losses, show them and act upon them!
And don’t get yourself lost in the traditional utilization and benchmark game. As Goldratt already mentioned, there is a clear distinction between “activitation” (traditional “utilization”) and real “utilization” (based upon the Latin word “utile”, meaning useful, beneficial and profitable).