Original scientific paper

https://doi.org/10.21278/TOF.454025420

A New Association Analysis-Based Method for Enhancing Maintenance and Repair in Manufacturing

Adel Al-Shayea ; Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia
Emad Abouel Nasr orcid.org/0000-0001-6967-7747 ; Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia; Faculty of Engineering, Mechanical Engineering Department, Helwan University, Cairo, Egypt
Hisham Al-Mubaid ; Computer Science Department, University of Houston – Clear Lake, Houston, TX 77058, USA
Abdulrahman Al-Ahmari ; Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia
Ali K. Kamrani ; Industrial Engineering Department, College of Engineering, University of Houston, Houston, TX 77204 4008, USA
Husam Kaid ; Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia
Haitham A. Mahmoud ; Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia; Faculty of Engineering, Mechanical Engineering Department, Helwan University, Cairo, Egypt

Abstract

Maintenance and quality of products are absolutely crucial for any organization to succeed in the industrial and manufacturing engineering. Current research studies have confirmed the presence of a high correlation between these two factors, namely maintenance and quality of products, in industrial organizations. Nevertheless, no extensive research has been conducted in order to study the link between maintenance and the quality of products in manufacturing. In this paper, we conduct a study in this domain and examine the relationship patterns between maintenance and the quality of product using manufacturing data on maintenance and the product quality. Specifically, we employ association analysis and association rule mining with large and extensive sets of product quality, repair, and maintenance data. Our main objective is to discover interesting and non-trivial associations for feature failure resulting in the repair or maintenance of a product with unapproved quality. The results of evaluation are quite interesting. The resulting association rules with high values of confidence and lift suggest some essential associations between the product features and the failure; such findings have not been known and used before. This can help quality engineers and maintenance teams to enhance maintenance and repair operations and lower the overall cost of manufacturing.

Keywords

Association Rule Mining in Manufacturing; Data Mining in Manufacturing; Quality Control; Maintenance and Repair in Manufacturing

Hrčak ID:

274029

URI

https://hrcak.srce.hr/274029

Publication date:

18.3.2022.

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