Yusuf, H. and Panoutsos, G. orcid.org/0000-0002-7395-8418 (2020) Multi-criteria decision making using Fuzzy Logic and ATOVIC with application to manufacturing. In: 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 19-24 Jul 2020, Glasgow, UK. IEEE ISBN 9781728169330
Abstract
In this paper multi-criteria decision making (MCDM) is investigated as a framework for classification of part quality in a manufacturing process. The importance of linguistic interpretability of decisions is highlighted, and a new framework relying on the integration of Fuzzy Logic and an existing MCDM method is proposed. ATOVIC, previously developed as a TOPSIS-VIKOR-based MCDM framework is enhanced with a Fuzzy Logic framework for decision making - Fuzzy-ATOVIC. This research work demonstrates how to add linguistic interpretability to decisions made by the MCDM framework. This contributes to explainable decisions, which can be crucial on numerous domains, for example on safety-critical manufacturing processes. The case study presented is the one of ultrasonic inspection of plastic pipes, where thermomechanical joining is a critical part of the manufacturing process. The proposed framework is used to classify (take decisions) on the quality of manufactured parts using ultrasonic images around the joint region of the pipes. For comparison, both the original and the Fuzzy Logic-enhanced MCDM methods are contrasted using data from manufacturing trials and subsequent ultrasonic testing. It is shown, that Fuzzy-ATOVIC provides a framework for linguistic interpretability while the performance is the same or better compared to the original MCDM framework.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | multi-criteria decision making; ATOVIC; Fuzzy Logic; classification; manufacturing; ultrasonic testing |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Oct 2020 07:27 |
Last Modified: | 26 Aug 2021 00:38 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/fuzz48607.2020.9177772 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:166731 |