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Fuzzy overall equipment effectiveness and line performance measurement using artificial neural network

Mahsa Fekri Sari (Department of Industrial Engineering, Qazvin Islamic Azad University, Qazvin, Iran)
Soroush Avakh Darestani (Department of Industrial Engineering, Qazvin Islamic Azad University, Qazvin, Iran)

Journal of Quality in Maintenance Engineering

ISSN: 1355-2511

Article publication date: 14 January 2019

Issue publication date: 23 April 2019

558

Abstract

Purpose

The overall equipment effectiveness (OEE) is a powerful metric in production as well as one of the methods in evaluating function for measuring productivity in the production process. In the existing method, measuring OEE is based on three main elements consisting availability, performance and quality. The purpose of this paper is to evaluate the recognized metrics of production: OEE and overall line effectiveness (OLE) by using smart systems techniques.

Design/methodology/approach

In this paper, to improve the calculative methods and productivity with three methods: measuring OEE using Mamdani fuzzy inference systems (FIS), measuring OEE using Sugeno FIS, and measuring OLE using FIS and artificial neural networks (ANNs) are proposed.

Findings

The proposed methodologies aim to decrease some weaknesses of OEE and OLE methods by exploiting intelligent system techniques, such as FIS and ANNs. In particular, this research will solve the following issues that occur in manual and automatic data gathering. This technique is an effective way of measuring OEE and OLE with regard to different weights of losses as well as difference in the weight of the machines. In addition, it allows the operator’s knowledge to take a part in the measurement using uncertain input and output with implementation of linguistic terms. The presented method is the details and capabilities of those methods in various tested scenarios, and the results have been fully analyzed.

Originality/value

In relation to other methodologies, it allows the operator’s knowledge to take part in the measurement using uncertain input and output with implementation of linguistic terms. The presented method is the details and capabilities of those methods in various tested scenarios, and the results have been fully analyzed.

Keywords

Citation

Fekri Sari, M. and Avakh Darestani, S. (2019), "Fuzzy overall equipment effectiveness and line performance measurement using artificial neural network", Journal of Quality in Maintenance Engineering, Vol. 25 No. 2, pp. 340-354. https://doi.org/10.1108/JQME-12-2017-0085

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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