Fuzzy overall equipment effectiveness and line performance measurement using artificial neural network
Journal of Quality in Maintenance Engineering
ISSN: 1355-2511
Article publication date: 14 January 2019
Issue publication date: 23 April 2019
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