Lean Manufacturing has become a paramount production paradigm in many industrial sectors and Overall Equipment Effectiveness (OEE) is a widely accepted and adopted lean metric for any type of machine/equipment. However, the standard OEE formulation presents two important limits: (i) it deals with a single machine, and (ii) gives a deterministic measure of effectiveness. The objective of this paper is to overcome both of these two shortcomings by proposing a Fuzzy approach for measuring the OEE of a manufacturing line (OEEML). Hence, starting from a possible definition of OEEML, this paper provides a framework to measure its modal value and its variability on an entire manufacturing line. The approach exploits Fuzzy Triangular Numbers instead of burdensome stochastic quantities to measure this variability. Furthermore, it integrates a method which enables us to avoid the annoying overestimation effect of FTNs. The integrated approach has proved to be useful in consistently capturing the OEEML variations, also, both the modal value and the range obtained from its application are good estimators of both the OEEML and its variability. A full case study is finally provided to show the effectiveness of the proposed approach in diagnosing problems and addressing improvement actions.
Integrating uncertainty considerations within the OEE of a manufacturing line
Braglia Marcello;Frosolini Marco;
2019-01-01
Abstract
Lean Manufacturing has become a paramount production paradigm in many industrial sectors and Overall Equipment Effectiveness (OEE) is a widely accepted and adopted lean metric for any type of machine/equipment. However, the standard OEE formulation presents two important limits: (i) it deals with a single machine, and (ii) gives a deterministic measure of effectiveness. The objective of this paper is to overcome both of these two shortcomings by proposing a Fuzzy approach for measuring the OEE of a manufacturing line (OEEML). Hence, starting from a possible definition of OEEML, this paper provides a framework to measure its modal value and its variability on an entire manufacturing line. The approach exploits Fuzzy Triangular Numbers instead of burdensome stochastic quantities to measure this variability. Furthermore, it integrates a method which enables us to avoid the annoying overestimation effect of FTNs. The integrated approach has proved to be useful in consistently capturing the OEEML variations, also, both the modal value and the range obtained from its application are good estimators of both the OEEML and its variability. A full case study is finally provided to show the effectiveness of the proposed approach in diagnosing problems and addressing improvement actions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.