{"title":"Generalized Utilization-Based Similarity Coefficient for Machine-Part Grouping Problem in Cellular Manufacturing","authors":"Tamal Ghosh","doi":"10.24425/MPER.2019.131449","DOIUrl":null,"url":null,"abstract":"This article intends to justify the gap in the research of similarity coefficient driven approach- es and cell formation problems (CFP) based on ratio data in cellular manufacturing systems (CMS). The actual implication of ratio data was vaguely addressed in past literature, which has been corrected recently. This research considered that newly projected CFP based on ration data. This study further revealed the lack of interest of researchers in investigation for an appropriate and improved similarity coefficient primarily for CFP based on ratio data. For that matter a novel similarity coefficient named as Generalized Utilization-based Simi- larity Coefficient (GUSC) is introduced, which scientifically handles ratio data. Thereafter a two-stage cell formation technique is adopted. First, the proposed GUSC based method is employed to obtained efficient machine cells. Second, a novel part allocating heuristic is proposed to obtain effective part families. This proposed approach is successfully verified on the test problems and compared with algorithms based on another similarity coefficient and a recent metaheuristic. The proposed method is shown to obtain 66.67% improved solutions.","PeriodicalId":45454,"journal":{"name":"Management and Production Engineering Review","volume":"10 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Management and Production Engineering Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24425/MPER.2019.131449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 1
Abstract
This article intends to justify the gap in the research of similarity coefficient driven approach- es and cell formation problems (CFP) based on ratio data in cellular manufacturing systems (CMS). The actual implication of ratio data was vaguely addressed in past literature, which has been corrected recently. This research considered that newly projected CFP based on ration data. This study further revealed the lack of interest of researchers in investigation for an appropriate and improved similarity coefficient primarily for CFP based on ratio data. For that matter a novel similarity coefficient named as Generalized Utilization-based Simi- larity Coefficient (GUSC) is introduced, which scientifically handles ratio data. Thereafter a two-stage cell formation technique is adopted. First, the proposed GUSC based method is employed to obtained efficient machine cells. Second, a novel part allocating heuristic is proposed to obtain effective part families. This proposed approach is successfully verified on the test problems and compared with algorithms based on another similarity coefficient and a recent metaheuristic. The proposed method is shown to obtain 66.67% improved solutions.
期刊介绍:
Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production and logistic systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work, supply chain optimization and logistics. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.