A computer-aided system for monitoring quality using traceable information. (28th November 2022)

• Record Type: Journal Article
• Authors: Bougdira, Abdesselam; Akharraz, Ismail; Ahaitouf, Abdelaziz
• Is Part Of: International journal of computer aided engineering and technology. Volume 18:Number 1/2/3(2023)
• Page Start: 19
• Page End: 38
• Publication Date: 2022-11-28
• Subjects: artificial intelligence -- fuzzy computing -- ontology -- traceability -- canning industry; Computer-aided engineering -- Periodicals; 620.00285
• Languages: English
• ISSNs: 1757-2657

Abstract

This paper proposes the usage of traceability data to enhance the continuous evaluation and monitoring of quality. The current study focuses on processing activities where it is difficult to detect and evaluate the possible degradation of quality. It has indeed a special interest in possible gaps that are not bridged by existing quality methods and practices, especially tasks that involve significant physical contact with manual labour. Therefore, this research introduces a computer-aided system that combines ontology-based knowledge with a fuzzy-based decision-making process. The proposed model can ensure the main traceability functions, including identifying, tracing, and tracking. Also, it can handle the various attributes associated with processing activities to assess the possible loss of quality. In case of unconformity, this monitoring function enables decision-makers to intervene appropriately. The developed system has also been illustrated through a fish canning case study.