Is OEE An Effective Metric for Assessing Industrial Production?

Using the right metrics is crucial to achieving successful performance in any enterprise. Keeping those metrics simple, if possible, is ideal. Can overall equipment effectiveness (OEE) provide that kind of snapshot information to manufacturers?

When you drive a car, you rely on one metric, speed, to tell you pretty much everything you need to know. It tells you if you are operating the car in a safe manner, or if you are at risk of being pulled over for an infraction. It gives you an estimate of how long it will take you to reach your destination, and a pretty good idea if you are pushing the car in a way that will land you the repair shop before long.

Lots of other things are going on, some of which are visible on the dashboard, but most of them you will not need to monitor unless there is a problem. There will be times when you wished you had known more, which might have saved you money in repair bills, but the burden of keeping up with all that information, is often simply too high.

The same is true for plant managers. When they’ve been out of the office for a bit and want to know how things are going, they don’t want an hour-long briefing. They want a single metric, which tells them whether they can relax or begin drilling down to try to understand what went wrong.

This is more or less the rationale behind OEE. Proponents of OEE claim that unlike other manufacturing buzzwords of the past, OEE is different. Vorne Industries Inc., which designed products to help measure OEE, says the metric “truly reduces complex production problems into simple, intuitive presentation of information. It helps you systematically improve your process with easy to obtain measurements.”

The allure of OEE is that it wields the potential to squeeze more production from a given facility without necessarily prompting an investment in new equipment or added personnel.

OEE is a key performance indicator (KPI) that is defined as the non-dimensional mathematical product of availability, performance (or efficiency), and quality.

Availability is the percentage of time that a machine is operational or capable of being operated -- when it is not broken, or being serviced. Performance is the ratio of the achieved speed or throughput relative to the design throughput. And quality is the percentage of units successfully produced compared to the number of units started. So if the OEE is 100 percent, that means that everything is as good as it could be. “It measures how much stuff I made that I can sell versus how much I could have made if I did everything right,” said Todd Smith, product manager for Rockwell Software.

There are variations in how these calculations are applied. Some companies measure availability against a 24/7 standard, independent of demand. Other companies adjust the calculation to measure the availability of the equipment only during the times it is actually needed.

Likewise, performance/efficiency can be measured against a theoretical maximum, or adjusted based on the MRP specified attainment.

Quality can also be expressed in terms of either overall yield or first pass yield.

LNS Research recommends the use of the following formulas:

  • Availability = Asset Uptime / Asset Scheduled Production Time
  • Efficiency = Total amount of product produced / (Time asset was available x Theoretical maximum production rate of asset)
  • Quality = Total products achieving quality specifications first time / Total products produced

Putting them together, we get: OEE = Availability x Efficiency x Quality.

LNS recommends this formula to reflect their position that “overall equipment effectiveness should be a standardized tool that doesn't allow for individual plants or decision makers to hide sins,” said Matthew Littlefield, LNS president and principal analyst. “Instead, OEE should maximize performance through highlighting areas of focus for continuous improvement efforts. However, this goal has to be tempered by the need to ensure maximizing OEE is in alignment with overall supply chain performance.”

The metric originated in Japan in the 1960s as an offshoot of the in-line quality control movement that was sweeping that country’s export-oriented economy. It was not exactly an overnight success. But the metric has been gaining popularity in the highly competitive packaging industry. Packaging suppliers are being driven hard these days to increase productivity.

Tom Jensen, program manager, OEM business development for Lenze Americas, which manufactures packaging automation equipment, says that productivity improvements of up to 40 percent can be achieved by process improvement methodologies like Six Sigma. OEE can then be used to track the effectiveness of those initiatives. But to use OEE most effectively, they should “measure and display OEE in real time to operators, along with supporting information that enables operations staff to understand root causes of OEE availability, line performance, or quality issues,” said Mark Davidson, principal analyst at LNS Research.

Software tools for real-time monitoring of OEE are available from companies like Vorne, Aptean, OEE Impact, Predator, and Evocon.

LNS plans to gather OEE data from over 1,000 companies. It has established a web portal through which participants can submit data for OEE, on-time and complete shipments, successful new product introductions, and cost of quality. Recently, they provided a snapshot in the form of a box plot for seven industries showing their median OEE and their distribution.

Of those, medical devices scores the highest at 91percent. Aerospace and defense (A&D), and semiconductors are at the bottom of the list at 75 and 75.5 percent respectively. These two also have the largest and smallest distributions. The overall median score is 85 percent. Also evaluated were automotive, electronics, and industrial equipment. Several companies within the categories A&D, electronics, and industrial equipment scored above the 90 percent mark.

At the end of the day, OEE is an alert that shows you where you’re losing money in production. “OEE provides a way to calculate the machine’s effectiveness and identify those losses,” said Gary Lerner, director of product strategy at Systech International. “It’s not a pill you can swallow and suddenly the equipment runs better. It’s a score that tells you whether you’re winning or losing.”

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