Overall Equipment Effectiveness – a jargon-buster
14 June 2011
Last month, we briefly touched upon the subject of Overall Equipment Effectiveness and introduced an entry-level system to help you get to grips with this production metric. This month, we invite Uwe Kueppers to describe the technique in more detail and explain the jargon
Overall Equipment Effectiveness (OEE) is an ideal starting point for many businesses to assess how productively they are using the resources that they have at their disposal. It is by no means a perfect business metric, but in our experience it is often the first step to truly understanding and quantifying how to improve business performance and to understand, analyse and manage the information that often already exists within the system. What’s more, OEE is a simple but effective ‘proof of concept’ for companies seeking to gain the advantage that automation and improved integration and management systems can bring, in fact, OEE frequently offers the first insight into the size and nature of a company’s potential to increase profitability.
What is OEE?
Overall Equipment Effectiveness is considered to be a fundamental Key Performance Indicator (KPI) in the industrial sector and is particularly important for manufacturing. The food & beverage, pharmaceutical or any manufacturing industry that involves packaging benefit particularly from OEE improvements. In the past 12-24 months, OEE has become a key driver for starting up a goal alignment management system or a KPI metrics system. It is a key stepping-stone on the path to rich, real-time information of a high quality and accuracy that can drive ‘lean manufacturing’ or ‘6 Sigma’ optimisation. The final figure for OEE is made from a simple calculation of: Availability x Performance x Quality
Availability is the proportion of scheduled time that the equipment is operational. For an accurate reading of this figure it is important that the equipment is monitored electronically so that every unplanned downtime is measured, rather than the more common measurement of ‘anything more than two or three seconds’ when manual monitoring.
Performance is the speed at which the machinery is operating against its optimal speed. For example, actual performance for a particular line could be 100 strikes per minute, whereas the machine may have the capacity to run efficiently at 200 strikes per minute. In this case a performance rate of 50% would be recorded.
Quality is the amount of good units produced as a percentage of the total units started. For example, a company that runs at 85% Availability, 90% Performance and 95% Quality, would have an OEE of 72.7%
Once a company has an accurate figure for Availability, Performance and Quality it can start to assess different approaches to improving the efficiency of the line, or process in question. Having a benchmark OEE figure is very important so that improvements to any part of the process can be assessed in terms of how effective they are. Moreover, in a larger manufacturing unit where the same process may be repeated elsewhere in the plant it can help determine ‘best practise’ and be combined with various other management tools to identify where efficiencies can be made.
Our experience at Rockwell Automation is that most companies are running between 55 and 65% OEE, which, at first glance, seems shocking. The best way to look at this though is as an opportunity, particularly while the export market is improving for UK manufacturers. ‘Best in class’ operations run at around 85% OEE, which allows most companies much room for improvement. Even those running at high standards of 75% can look to improve their OEE by up to 10%, and with just a few percent having an inevitably positive effect on the bottom line, it is easy to understand why OEE is considered such an important starting point for so many companies in today’s market.
Retrieving the data.
We find a lot of data is already available in the PLCs. Often, in an average automated environment, it is a matter of simply coming in and taking a single machine line, defining the measurement to be addressed and harvesting the information for a week or two to prove the concept. This can be set up very quickly, in just two days for example, depending on the customer.
Since most PLCs and data acquisition devices conform to the Open Process Control (OPC) standards which allow any OPC enabled software to integrate with them, the retrieval of OEE data doesn’t have to be complex or expensive. Our experience has shown that a return on the investment involved in measuring OEE is nearly always within 12 months, and often far sooner.
Labour, energy and carbon costs
OEE is only one figure which, alone, cannot reduce energy and labour costs or carbon emissions. Therefore it is important that the OEE system is not a ‘tailored OEE solution’ but works with an enterprise manufacturing intelligence (EMI) software system. EMI software is the first step to achieving the ‘data rich and information rich’ environment that is required to tackle these costs, rather than the ‘data rich, information poor’ environment, which is a common complaint of many senior level decision makers in industry.
It is important that the data and information from different parts of the business can be contextualised within a unified production model providing users with information that can help them take real time decisions by order, machine or productions steps, or, for example, analyse the carbon footprint and related energy cost by the same metrics. OEE can be considered a part of a live, real-time business management system that makes available contextualised information to everyone in the organisation, aiding them to make more accurate decisions, quicker.
With a platform in place through the OEE approach, companies can then extend the information infrastructure to control carbon costs and achieve full potential by examining the defined KPIs and adapting business practises to make improvements.
It is very important that the operators and owners are able to conduct their data to analyse, optimise and take more solid business decisions in order to be ready for the next challenge!
Uwe Kueppers is director of information software (EMEA region), Rockwell Automation
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