Abstract
Nakajima defined the ‘Overall Equipment Effectiveness’ (OEE) indicator to measure the performance losses of a company. Since then, variants have been proposed by authors and standardisation bodies to make it more suitable for new production contexts. OEE allows measuring performance losses and is used to determine improvement projects.
The use of different OEE measurement systems can lead to different improvement projects; i.e. the use of inappropriate measurement systems leads to the resolution of wrong problems. It is, therefore, necessary to understand OEE and its variants to choose the most appropriate measurement system and thus focus improvement efforts on the least efficient processes. This need is initially specified by a French-Spanish industrial group.
However, to our knowledge, there is no comparative study of the different OEE measurement systems.
Our review of the scientific literature and international standards revealed four measurement systems widely used and commonly applied in industry, namely, Nakajima, ISO, SEMI and AFNOR. We analysed these different measurement systems in depth, proposed a reference taxonomy of loss families, and compared them all. These measurement systems were then applied to the case of one of the industrial group’s plants to determine their adequacy and compare them with the existing OEE measurement system of the industrial group. An OEE calculator offering these different measuring systems has been programmed and installed in the factory.
The main results of this research work are as follows. First, a reference taxonomy of loss families is proposed. The effective comparison carried out for the four widely used measurement systems is the second tangible result. Finally, this study made it possible to determine and validate the main characteristics to be taken into account in the final choice of an OEE measurement system in a real case.
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Notes on contributors
Fatma Kechaou
Fatma Kechaou is a researcher in Operations Management and Mechanical engineering. She received his PhD from the ENS Paris Saclay in Productics and Industrial Engineering in 2020. Her research interests are related to production system management and Statistico-cognitive decision making. His main research work focuses on the integration of the digital transition in production control and management of operations through causal models.
Sid-Ali Addouche
Sid-Ali Addouche is an Associate-Professor of Operations Management and Logistics at IUT de Montreuil, University Paris8. He obtained his PhD from the University of Franche-Comté in 2003. His research topics include production system management and control, supply chain sustainability and resilience management and in service support of systems and infrastructures. His research work focuses on verticalising the digital transformation of enterprises, integrating smart data into decision making, and obsolescence prediction methodologies and techniques, and obsolescence resilient systems engineering. He has supervised more than a dozen theses and he is the author of more than 70 articles in academic journals and conferences.
Marc Zolghadri
Marc Zolghadri is a Professor of Operations Management and Logistics at Supmeca, Paris. He received his PhD from the University of Bordeaux, and obtained his habilitation in 2010. His research interests are related to product and system redesign and upgrading, supply chain redesign and management, and control of complex systems. His main research work is focussed on driving the digital transformation of enterprises, engineering change management, and obsolescence prediction methodologies and techniques, and obsolescence resilient systems engineering. He is the author of more than 140 articles in academic journals and conferences.