The OEE Deficit: Why It Can't Deliver The Results You Require

The OEE Deficit
Why it can't deliver the results you require
January 2008The OEE Deficit:Why it can't deliver the results you require
Executive Summary
For complex manufacturing environments, OEE (Overall Equipment Effectiveness) falls short when it comes to delivering improvements in productivity. That's because OEE tools were originally developed to measure the performance of stand-alone equipment or the total output of a particular line. But current manufacturing processes incorporate complex value streams with multiple processing steps. So OEE measures can obscure the main goal - to make improvements which will lead to greater productivity and more production off the end of the line. To succeed, today's enterprises need more.
This paper describes an evolution in thinking: The most efficient way to increase productivity is to focus on product flow through the process.
Conventional thinking suggests that all processes in the value stream must run at their highest level to realize peak productivity. However, if the objective is to improve end-of-line output and overall performance, a new approach should be considered. Concentrating instead on the flow of product through the value stream enables the identification of chronic disruptors. And, to take this thinking even further, precisely measuring how each process maintains (or disrupts) throughput, plus applying the Theory of Constraints, allows improvement efforts to be directed toward the constraints that are most inhibiting the process.
The result is a more tangible and powerful strategy for continuous improvement. With a focus on throughput capability, plant operators use fewer resources to fix productivity issues because they know exactly where to find the chronic constraints and what improvements are required. And management gets objective information, enabling informed decisions that will positively impact the bottom line.

The OEE Deficit  © Activplant CorporationWhat's Wrong with OEE?
Actually, nothing. That is, if you're looking for an accepted standard of measurement to determine whether standalone machinery is operating at its maximum capacity. OEE (Overall Equipment Effectiveness) is an excellent reporting methodology.
However, in today's complex manufacturing environments, OEE doesn't go far enough. OEE can measure how well a process is doing at achieving its desired target of quality products. However, OEE cannot tell you which step in the process is constricting the output of the line and why.
And once the data is collected, what is a manager to do with it? After determining whether OEE is high or low, whether it has improved or deteriorated, what next? Typically, manufacturers turn to the collected data in an attempt to get further information at the process or station level. This results in an escalation of the amount of data and statistics about machine performance. You may have a measurement of hundreds of processes. But what is actually needed is an understanding of the data. To improve manufacturing productivity and profits, you need more.
To succeed today, plant management must go beyond data collection. It is imperative to understand the meanings behind the data so that better business decisions can be made for the enterprise. Moreover, management decisions will be enhanced if the most relevant data is identified. And finally, management must be able to assign accountability and pinpoint the specific areas for improvement that will generate the largest and most immediate returns.
The Conventional Perspective
Traditionally, plant management has been conditioned to use OEE reporting to measure downtime. If production targets are not being met, downtime has been the logical issue to address. And most of the time, equipment downtime is thought to be the likely culprit. And so the convention has been that if management strives to eliminate all equipment downtime, overall gains in output will be achieved and plant performance will improve.
The OEE Deficit  © Activplant CorporationHowever, there are many reasons beyond low OEE for reduced equipment performance. Part shortages, excessive changeover times, delays in part loading and process delays for quality adjustments can all be ... [download for more]