Does Overall Equipment Effectiveness (OEE) Improve Manufacturing Processes?

“How does OEE systematically improve your manufacturing processes?” -- That was the question I recently posed to Ross Kennedy, author of a recently published book entitled Understanding, Measuring, and Improving Overall Equipment Effectiveness: How to Use OEE to Drive Significant Process Improvement. Ross is recognized as Australasia’s leading authority on total productive maintenance (TPM) and continuous improvement, and he had some key insights. Here is his complete answer:

OEE or Overall Equipment Effectiveness was created during the development of the Toyota Production System to help understand all the losses that could affect equipment performance so as to reduce lead times and improve quality, rather than relying on the traditional approach of measuring just equipment downtime. I first came across the concept in 1989 in a Productivity Press book titled TPM Development Program. It outlined that equipment could only be effective if it was Available when required, running at the ideal or theoretical speed or Rate (very best in ideal situation), and producing good Quality output first time. Hence OEE = Availability% x Rate% x Quality%.

Originally OEE involved the Six Big Losses (equipment failure, sets and adjustments, idling and minor stops, reduced speed, process defects, reduced yield) , however in more recent times this has been expanded to seven losses with the inclusion of planned downtime when the operating crew are at work.

OEE is often referred to as the measure that allows you to expose and capture the "hidden factory" within your plant. Often sites will identify opportunities worth 20% to 50% more capacity from their production lines or processes with little or no capital expenditure simply by fully understanding and doing something about all the losses that stop their equipment from being effective. I have certainly witnessed this in manufacturing, mining, and process industries during the past 20 years of applying this learning in a structured discipline way.

I have found when studied in detail, OEE losses can be attributed to three key areas:

• Technical issues such as design weaknesses or poor maintenance practices.
• People Development issues such as poorly trained operators or maintainers who lack an understand of prevention at source for equipment.
• Management issues such as inappropriate organization structures, rostering, recruitment, daily management policies, planned maintenance and planned break times.

Once identified and actioned, the improvement results can be very significant.

One mine site in Indonesia reported at an international conference in Asia how over two years they saved over US$135million by focusing OEE improvement on their run-of-mine. At Australia’s largest privately owned brewery, OEE was used to increase the capacity of their main production line by more than 15% each year to defer the need to increase to a two-shift operation for three years while still meeting the growth of their business which was reported in the local media as 17.5% average yearly growth from 1993 to 2012.

Unfortunately at many sites, OEE has become the most misused and abused indicator of equipment performance with some sites changing the definitions to make it appear better as they are required to submit it to corporate for comparison between other sites.

At one large multi-national food manufacturing site I visited they were boasting about their high OEE performance, however when I delved into the way they were measuring OEE, I realised that they had removed Planned Downtime and Set-up or Changeover Downtime and had an Ideal speed set at the standard average speed used for setting budgets and doing costing (typically 20% lower than true ideal or theoretical speed). In effect, they were hiding many opportunities for improvement so that they could report a good performance figure to corporate management. In other words, they had a culture of always trying to look good rather than seeking out opportunities for continuous improvement.

OEE should be seen and used as a "driver" for improvement, not as a performance measure to be compared or benchmarked between equipment and sites. As a "driver" for improvement, the definition for OEE should have a 100% correlation to the good output produced from your line or plant. In other words, if OEE increases by 10% then you should be making 10% more good output or making the same amount of good output within 10% less time, hence the need for the OEE definition to include all the seven losses. 

What are you thoughts on Ross Kennedy's perspective on the use of OEE for process performance improvements? Do you use OEE as a key performance indicator of manufacturing productivity?