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In this article, we are going to talk about the elements needed to calculate OEE, then how you can capture and present them in Maximo (or the new MAS Manage).

 

What are the elements of OEE?

There are classically three elements of OEE:

  • Availability
  • Productivity
  • Quality

Given that each of these has a value between 0 and 100%, then OEE = A x P x Q. A relative value where the closer to 100% (or 1) the more effective your equipment is for your purposes.

These elements are just a starting point for understanding. There are many different approaches people use to come up with their take on, “effectiveness.” The context of the equipment you are responsible for might necessitate the need for a more nuanced approach.

Another approach is to use OEE at a higher level, considering the entire production operation. Here you bring in each department involved in production and their individual efficiency. Operations, Maintenance, and Engineering would be those typical elements. This method brings you Overall Production Efficiency.

For a specific and asset-focused example, in the TRM Advanced Asset Management (AAM) product, we calculate the Availability, Reliability, and Maintainability of defined Assets to arrive at the effectiveness value. Same idea: Asset Effectiveness Index (AEI) = A x R x M.

Availability is the easy one. Simply, out of some period of time, what percentage of that time is the piece of equipment available to perform its function? Consider those fixed periods where the equipment is scheduled to be down and not expected to be available. Then add the always changing periods of unplanned maintenance that should be kept to a minimum. Recall that you can establish calendars or operational and maintenance time in tools such as Maximo (or Manage) that can be a foundation for this calculation. Let’s say that overall, a piece of equipment is available 90% (0.9) of the time.

Productivity is a little tricky in that it can mean so many different things across industries. How do you measure the productivity of a piece of equipment? It comes down to the speed (or lack thereof) of the equipment to produce whatever it is producing. In the case of our AAM product, we chose to use a Reliability calculation to be a proxy for Productivity. Given a Mean Time Between Failure (MTBF) calculation, we can then arrive at a Reliability value. Let’s say the equipment is 98% (0.98) productive (or reliable)

Quality too is subject to your situation. If the equipment has an impact on the quality of what is being produced, you will need to find a calculation method that suits you. Simply the calculation could be the ratio between good parts produced and the total parts produced. In AAM we used the Maintainability of the equipment for this OEE element. By knowing how maintainable (or not) a piece of equipment is, we can estimate the hassle factor a breakdown introduces to our daily life. Let’s say this piece of equipment has a Quality level of 99% (0.99) for our example today.

 

Let’s calculate OEE…

OEE = 0.90 x 0.98 x 0.99 = 0.87

So, what does that tell us? By itself nothing really. Is 87% effective a good or bad result? Maybe that’s pretty good. Maybe it is terrible. The point is that we have a result that is based on real data. But we need the effectiveness of other pieces of equipment to compare it with. If you are calculating in the same manner across equipment, you will end up with a ranked list of “bad actors” where the worst performing OEE equipment is at the top

OEE results generally run with the number of components that can fail.  If you have a complex system vs a simple system, the OEE for the simpler system can be as good as 96% while the more complex one may only reach 90% with the same maintenance practices.  There is more risk with higher complexity, that’s why it is good to simplify a production line whenever possible.

Maybe you end up with a long list of OEE results per equipment, and you find that the top 10 are down into the 80s, while the rest are 90+ values. Now you have a list of bad actors to focus on and begin to research why they might be struggling.

Let’s stop here a moment. Go out in the field or to the production floor with your list and ask the folks intimate with the equipment if the results match their experience. Are the top 10 bad actors on your list also the same ones that drive the operators or maintenance team crazy? Here’s hoping for at least a few matches. Given their input, now your list has credibility.

 

Where to begin?

Decide two things first: 1) You are going to research and develop an approach to OEE that suits your situation, and 2) how you are going to calculate each of the different elements. Once those are settled, now you can specify the data you need to collect to support your calculations. If you have a system such as Maximo or another EAM/CMMS tool, there are already data fields for capture. But you should be prepared to have other fields added and to train your field staff when and where to enter the data.

Be sure you document the details of your approach. People will question your results and sources of data, so you need to have good references to rely upon for your responses.

 

Automate!

As we did for our AAM offering, make the entry of the supporting data fields easy for your field staff, and make the continual calculations automated. By automating the calculations, you do not spend time extracting data into spreadsheets and forming reports regularly. Rather, you can gather decision-makers and use the presentations of OEE directly from the software tool. Wherever you can eliminate the need to extract data and create reports will have significant time savings for your organization.

 

Make use of your new tool!

Given data coming into the system from the field and calculations being performed on a near-real-time basis, you will be well-armed with lists of OEE estimations to act upon. Don’t get all wrapped up about what the actual values are… it does not matter that one piece of equipment is at .98 and another is .97. Rather, focus on the list of the top 10 worst performers and begin to investigate why. It may take a few cycles or months to get enough data for the results to reflect reality. You may also find “motion,” in the list where a particular piece of equipment appears bad, but then looks good a few weeks later.

When you do take action to remedy the OEE for a piece of equipment, be sure to track the results. Don’t just assume your efforts “fix,” the problem. Again, it may take time for you to see the results, but if you track what you did and when, you can easily see the impact in the OEE results… eventually.

 

Finally…

Simple data capture, simple calculations, and simple presentations of OEE add up to a powerful tool to help you visualize the health and effectiveness of your equipment. You will never reach 100% or even in the high-90s, but you have a guide to continuous improvement using tools that have been there the whole time.

We would be glad to show you our Advanced Asset Management product and how this powerful EAM can maximize your ability to calculate OEE and visualize the health of your equipment.

 

Article by John Q. Todd, Sr. Business Consultant at TRM. Reach out to us at AskTRM@trmnet.com if you have any questions or would like to discuss deploying MAS 8 or Maximo AAM for condition based maintenance / monitoring.

 

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