TY - JOUR

T1 - Overall Equipment Effectiveness (OEE) and Process Capability (PC) measures - a relationship analysis

AU - Garza Reyes, Jose Arturo

AU - Eldridge, Stephen

AU - Barber, Kevin

PY - 2010

Y1 - 2010

N2 - Purpose – Overall equipment effectiveness (OEE) and process capability (PC) are commonly used and well-accepted measures of performance in industry. These measures, however, are traditionally applied separately and with different purposes. The purpose of this paper is to investigate the relationship between OEE and PC, how they interact and impact each other, and the possible effect that this relationship may have on decision making.Design/methodology/approach – The paper reviews the OEE and PC background. Then, a discrete-event simulation model of a bottling line is developed. Using the model, a set of experiments are run and the results interpreted using graphical trend and impact analyses.Findings – The paper demonstrates the relationship between OEE and PC and suggests the existence of a “cut-off point” beyond which improvements in PC have little impact on OEE.Practical implications – PC uses the capability indices (CI) to help in determining the suitability of a process to meet the required quality standards. Although statistically a Cp/Cpk equal to 1.0 indicates a capable process, the generally accepted minimum value in manufacturing industry is 1.33. The results of this investigation challenge the traditional and prevailing knowledge of considering this value as the best PC target in terms of OEE.Originality/value – This paper presents a study where the relationship between two highly used measures of manufacturing performance is established. This provides a useful perspective and guide to understand the interaction of different elements of performance and help managers to take better decisions about how to run and improve their processes more efficiently and effectively.

AB - Purpose – Overall equipment effectiveness (OEE) and process capability (PC) are commonly used and well-accepted measures of performance in industry. These measures, however, are traditionally applied separately and with different purposes. The purpose of this paper is to investigate the relationship between OEE and PC, how they interact and impact each other, and the possible effect that this relationship may have on decision making.Design/methodology/approach – The paper reviews the OEE and PC background. Then, a discrete-event simulation model of a bottling line is developed. Using the model, a set of experiments are run and the results interpreted using graphical trend and impact analyses.Findings – The paper demonstrates the relationship between OEE and PC and suggests the existence of a “cut-off point” beyond which improvements in PC have little impact on OEE.Practical implications – PC uses the capability indices (CI) to help in determining the suitability of a process to meet the required quality standards. Although statistically a Cp/Cpk equal to 1.0 indicates a capable process, the generally accepted minimum value in manufacturing industry is 1.33. The results of this investigation challenge the traditional and prevailing knowledge of considering this value as the best PC target in terms of OEE.Originality/value – This paper presents a study where the relationship between two highly used measures of manufacturing performance is established. This provides a useful perspective and guide to understand the interaction of different elements of performance and help managers to take better decisions about how to run and improve their processes more efficiently and effectively.

KW - Manufacturing systems

KW - Performance measures

KW - Process analysis

KW - Production processes

U2 - 10.1108/02656711011009308

DO - 10.1108/02656711011009308

M3 - Journal article

VL - 27

SP - 48

EP - 62

JO - International Journal of Quality and Reliability Management

JF - International Journal of Quality and Reliability Management

IS - 1

ER -