Performance measurement using ove...
International Journal of Production Research, Vol. 46, No. 13, 1 July 2008, 3517���3535 Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion P. MUCHIRI* and L. PINTELON Centre for Industrial Management (CIB), Katholieke Universiteit Leuven, Celestijnenlaan 300A, 3001 Heverlee, Belgium (Revision received November 2006) The quest for improving productivity in the current global competitive environment has led to a need for rigorously defined performance-measurement systems for manufacturing processes. In this paper, overall equipment effective- ness (OEE) is described as one such performance-measurement tool that measures different types of production losses and indicates areas of process improvement. Analysis is done on how OEE has evolved leading to other tools like total equipment effectiveness performance, production equipment effectiveness, overall factory effectiveness, overall plant effectiveness, and overall asset effectiveness. Two industrial examples of OEE application are discussed, and the differences between theory and practice analysed. Finally, a framework for classifying and measuring production losses for overall production effectiveness is proposed. The framework harmonizes the differences between theory and practice and makes possible the presentation of overall production/asset effectiveness that can be customized with the manufacturers needs to improve productivity. Keywords: Performance measurement Overall equipment effectiveness Manufacturing 1. Introduction The evolution towards a global economy has expanded the base of competition for virtually all businesses. By the very nature of the word competition, it is implied that someone out there is always keeping score. The tally on the scorecard may be a measure of more sales, increased profit or a growing customer base. Regardless of the criteria of measurement used, to remain competitive, you have to put up more points on the board. In order to beat competition, there is a basic business demand to get better at what is done and at meeting customers��� expectations. As noted by Fleischer et al. (2006), the competitiveness of manufacturing companies depends on the availability and productivity of their production facilities. Huang et al. (2003) also state that due to intense global competition, companies are striving to improve and optimize their productivity in order to remain competitive. This would be possible if the production losses were identified and eliminated so that the manufacturers could bring their products to the market at a minimum cost. *Corresponding author. Email: firstname.lastname@example.org International Journal of Production Research ISSN 0020���7543 print/ISSN 1366���588X online �� 2008 Taylor & Francis http://www.tandf.co.uk/journals DOI: 10.1080/00207540601142645
This situation has led to a need for a rigorously defined performance measurement system that is able to take into account different important elements of productivity in a manufacturing process. The total productive maintenance (TPM) concept, launched by Nakajima (1988) in the 1980s, provided a quantitive metric called overall equipment effectiveness (OEE) for measuring productivity of individual equipment in a factory. It identifies and measures losses of important aspects of manufacturing namely availability, performance, and quality rate. This supports the improvement of equipment effectiveness and thereby its productivity. The OEE concept is becoming increasingly popular and has been widely used as a quantitative tool essential for measurement of productivity especially in semiconductor-manufacture operations (Huang et al. 2003). Manufacturers in other industries have also embraced it to improve their asset utilization. The industrial application of OEE, as it is today, varies from one industry to another. Though the basis of measuring effectiveness is derived from the original OEE concept, manufacturers have customized OEE to fit their particular industrial requirements. Furthermore, the term OEE has been modified in literature to different other terms with regard to the concept of application. This has led to broadening of OEE to overall factory effectiveness (OFE), overall plant effectiveness (OPE), overall throughput effectiveness (OTE), production equipment effectiveness (PEE), overall asset effectiveness (OAE), and total equipment effectiveness performance (TEEP). The objective of this paper is to investigate how the OEE tool has evolved with time and how it has been applied to fit the individual needs of the industries. Two industrial examples are analysed to show how the OEE concept is applied to enhance productivity in industries and the different types of production losses measured. To harmonize the different OEE concepts in literature and practice, a general framework with different categories of production losses has been developed. This framework gives different categories of losses that are important in measuring overall production effectiveness. Finally, this paper discusses the benefits and challenges of using the OEE measurement tool and the type of processes where its benefits are significant. 2. OEE measurement tool: overview The OEE measurement tool was developed from the TPM concept launched by Nakajima (1988). The goal of TPM is to achieve zero breakdown and zero defects related to equipment. The consequence of reducing breakdowns and defects is improvements in production rate, reductions in costs, reductions in inventory, and eventually increases in labour productivity. The TPM concept puts much attention on production equipments, since they have a high influence on quality, productivity, cost, inventory, safety and health, and production output. This is especially true for highly automated processes. OEE is defined as a measure of total equipment performance, that is, the degree to which the equipment is doing what it is supposed to do (Williamson 2006). It is a three-part analysis tool for equipment performance based on its availability, performance, and quality rate of the output. It is used to identify for an equipment 3518 P. Muchiri and L. Pintelon
the related losses for the purpose of improving total asset performance and reliability. It categorizes major losses or reasons for poor performance and therefore provides the basis for setting improvement priorities and beginning of root cause analysis. It can point to hidden capacity in a manufacturing process and lead to balanced flow. OEE is used to track and trace improvements or decline in equipment effectiveness over a period of time (Bulent et al. 2000). Confusion exists as to whether OEE indeed measures effectiviness (as depicted by its name) or whether it is an efficiency measure. In the literature (US Department of Energy 1995), effectiveness is defined as a process characteristic that indicates the degree to which the process output conforms to the requirements. It indicates whether things are done correctly. Efficiency, on the other hand, is defined as a process characteristic indicating the degree to which the process produces the required output at minimum resource cost. It indicates whether things are done correctly. The three measures (availability rate, performance rate, and quality rate) captured by the OEE tool indicates the degree of conformation to output requirements. Therefore, indeed the OEE tool is a measure of effectiveness. This is in agreement with the definition in literature that OEE measures the degree to which the equipment is doing what it is supposed to do, based on availability, performance, and quality rate (Williamson 2006). The OEE tool is designed to identify losses that reduce the equipment effectiveness. These losses are activities that absorb resources but create no value. According to Jonsson and Lesshammar (1999), the losses are due to manufacturing disturbances that are either chronic or sporadic. Chronic disturbances are small and hidden, and are a result of several concurrent causes. Sporadic disturbances on the other hand are more obvious since they occur quickly and have large deviations from the normal state. It is a bottom-up approach where an integrated workforce strives to achieve overall equipment effectiveness by eliminating six large losses (Nakajima 1988). The six large losses are given below, with some examples from a palletizing plant in a brewery as analysed by Pintelon et al. (2000). Downtime losses: (1) Breakdown losses categorized as time losses and quantity losses caused by equipment failure or breakdown. For example, a breakdown of palletizing plant motor in a brewery leads to downtime and thus production loss. (2) Set-up and adjustment losses occur when production is changing over from requirement of one item to another. In a brewery plant, this type of loss is encountered during set-ups between different products, testing during start-ups, and fine tuning of machines and instruments. Speed losses: (3) Idling and minor stoppage losses occur when production is interrupted by temporary malfunction or when a machine is idling. For example, dirty photocells on palletizing machines cause minor stoppages. Though they are quickly fixed, much capacity is lost due to their frequency. (4) Reduced speed losses refer to the difference between equipment design speed and actual operating speed. In a palletizing plant, the use of unadapted pallets leads to longer processing times for the same number of bottles leading to speed losses. Performance measurement using overall equipment effectiveness 3519