Dresden, (PresseBox) - It is often said in business and life alike, 'Time is money', for a manufacturing plant - this statement is of great importance. Today we will look at a performance metric called OEE-Overall Equipment Effectiveness, which pegs plant/equipment performance against time, i.e. it compares the actual productivity against planned productivity. We will also explore the application of OEE in a manufacturing plant and the benefits of using an MES application in the implementation. But first, let's understand what OEE is and how it is calculated.

In a very simple way, OEE is a metric which measures the percentage of production time which is actually productive and it is expressed in percentage. A score of 100% OEE is considered a perfect production, which signifies that the plant is manufacturing only good parts, as fast as it can be, with zero down time. However, for practical purposes, an OEE of 85% is considered a world class level production. Lower percentages of OEE such as 60% or 40% are not uncommon, but such values indicate a significant room for process improvement.

What this metric basically does is comparing the Fully Productive Time of a plant/equipment to the Planned Production Time, where the latter is the difference of the total time available for production and planned shutdowns. OEE is critically important for any manufacturing plant because it allows the management to know the actual performance of the plant against the planned performance in terms of Down Time Loss, Speed Loss and Quality Loss. The OEE calculations help management take fact-based decisions to improve productivity and perform quality vs. speed trade-offs.

Now let's see how OEE is calculated as this will help us to better understand the losses mentioned above. OEE is calculated as the product of Availability, Performance and Quality.

Availability is basically the ratio of Operating Time (Planned Production Time - Down Time) to Planned Production Time; it takes into account the Down Time Loss.

Performance is the ratio of Net Operating Time to Operating Time; here it's worthwhile to mention that Net Operating Time is the product of Ideal Cycle Time & Total Pieces. The Ideal Cycle Time is a theoretical time which represents the fastest possible time to produce a single product unit. Performance accounts for Speed Loss, which occurs when the plant/equipment is operating at lower than ideal speed.

Quality is calculated as the ratio of Fully Productive Time to Net Operating Time, it accounts for Quality Loss, which is products/parts that do not meet the quality standards, and this also includes parts which require rework. Practically Quality is calculated as the ratio of Good or Acceptable Pieces to Total Pieces Produced.

So the final formula becomes: OEE= Availability X Performance X Quality or (Good Pieces X Ideal Cycle Time)/Planned Production Time.

Having understood how to calculate the OEE, let's consider its implementation in a manufacturing plant; say a plant which manufactures engine parts for a motor vehicle company. Such a plant would have various assembly lines with specialized equipment for various parts being manufactured. Typically, OEE is calculated for the bottleneck of a particular line, but it can be calculated for every single piece of equipment and can also be calculated for an entire plant with all its components, including equipment and human resources. Calculating OEE manually is possible and can be done for a new establishment as approximate values of down-time, speed and quality loss, may be acceptable, considering that the plant is relatively low on the experience curve. But for a well-established plant, accuracy of data collection and precise measurements of down time, cycle time and quality are imperative to improve performance.

This is where the Manufacturing Execution Systems (MES) makes its grand entrance; the MES is an IT application which has the capability to extract process data from the production line with 100% accuracy in real time. The MES is capable of calculating the exact down times to the very last second, exact quality loss data and overall speed of production. This helps exact calculation of OEE and helps management take better and well informed decisions pertaining to process capability, process performance, shift scheduling, employee/operator performance and process improvement. Due to the automated nature of data collection a lot of time and effort is saved in collecting and reporting data, this automatically leads to better performance. Also due to automation, it is possible to drill down to the exact cause of a performance related problem, as the data collected is granular in nature. MES applications allow process owners to use OEE to their advantage by providing structured reports, Pareto charts and shield them from the complexity of the application's design.

MES can also be used to provide a corporate overview of performance of not just one plant, but all the plants of the organization. For a plant similar to the one mentioned above the MES application would be greatly beneficial for implementing OEE, as it would be able to provide data specific not only to equipment and production lines but also based on various product classes, for each batch produced, in each shift and under each operator.

The possibilities of improvement are enhanced when MES is used for OEE implementation as it has the power to support the implementation of a higher improvement endeavor like Lean Manufacturing or TQM. The application can provide data pertaining to all resources and help analyze the problem areas in a more comprehensive and precise manner. So if your plant is currently at a 45-55% OEE level and you are employing manual means to calculate OEE, it's time to consider an MES to support its calculation, monitoring and all subsequent process improvement actions.

This and other blog entries can be found here.

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