I debated using the title “Why I hate OEE” but I thought that was a little extreme, albeit catchy. And I wouldn’t go so far as to say that I hate OEE. Rather, I view initiatives solely focused on calculating the metric like investing in an expensive rear view mirror. You need one, don’t get me wrong. But the metric and the data required to calculate it will only tell you where you’ve been. If implemented properly, you will know when you have had a problem, but it won’t change your behavior, your business processes or support your continuous improvement efforts - all of which can serve to increase your return on invested capital.
My friend Matt Littlefield at LNS Research (formerly an analyst at Aberdeen) wrote a good summary of OEE (Part 1, Part 2) in his blog. If you are looking for some good foundational information on OEE it’s well worth a read. He advocates measuring OEE, rightly so. From a comparative perspective it’s helpful (between equipment, within a plant, between plants and potentially between companies). What’s not written, and Matt will be quick to point out, it’s the action you take based on OEE related events that provides ROI.
Therein lies the rub, the devil is in the “events” and the “events” are what provide ROI. Take the availability component of OEE for example – the ratio of asset uptime to asset scheduled production time. What’s more important to you, knowing that you are using 85% of scheduled production time or knowing when an asset transitioned into an unproductive state (the event)? Would you rather have a detailed account of the 85% of available time you used, or of the 15% that’s being wasted? More importantly, what are you doing about it? What actions are you taking when an asset transitions from a productive to unproductive state? Taking action on exception events differentiates a manufacturer from its peers and provides returns that exceed peer performance – the mark of an exceptional manufacturer.
We advocate a unified approach to modeling asset states and state transitions, with sufficient detail to support continuous improvement initiatives. The same holds for the quality component of OEE – have a unified approach with regards to quality events (yield loss). There’s a special emphasis here at Savigent on events, state transitions and quality events, because we want our customers to realize high ROIs on their implementations. Knowing when events occur allows our customers to implement workflows that guide the actions they take every time an asset transitions from a productive to unproductive state, or a yield loss event occurs. Since events are monitored in real time and responses are implemented as workflows there’s guaranteed execution with 100% process compliance. Our customers know when bad things happen, and they know they are responding to them as they have defined each and every time.
Of course, when you take this approach you’ll have all the data you need to calculate OEE. But you will also capture a tremendous amount of information about the events that are causing inefficiency – their frequency of occurrence, duration, impact and any related data you need to support continuous improvement efforts.