Title: Fuzzy weighted association rule based solution approaches to facility layout problem in cellular manufacturing system
Authors: S. Altuntas; T. Dereli; H. Selim
Faculty of Engineering, Department of Industrial Engineering, Bayburt University, 69000 Bayburt, Turkey
Faculty of Engineering, Department of Industrial Engineering, University of Gaziantep, 27310, Gaziantep, Turkey
Faculty of Engineering, Department of Industrial Engineering, Dokuz Eylul University, 35160 Izmir, Turkey
Abstract: This study aims to propose new solution approaches based on fuzzy weighted association rules for facility layout problem in a cellular manufacturing system. The facility layout problem under concern has two important aspects, namely; fuzzy product route and fuzzy machine weight. Number of machine types as well as the number of machines in each type is determined in order to define a fuzzy product route. A fuzzy set is then assigned for each machine type to match them with appropriate products. Alternative routes for each product and machine weights are defined by fuzzy functions. Market demand is also used to assign weights to the machines. Three solution approaches, namely fuzzy weighted association rule mining (FWARM), Gyenesei's weighted quantitative association rules (WQAR) and normalised weighted association rule mining (NWARM) based approaches, are proposed in this study. To the authors' best knowledge, this is the first attempt which considers fuzzy weighted association rule-based data mining approaches to the facility layout problem. An illustrative example is presented to demonstrate the usefulness of the proposed approaches.
Keywords: weighted association rules; facility layout; cellular manufacturing systems; CMS; data mining; fuzzy logic; fuzzy weighted ARM; association rule mining; FWARM; weighted quantitative association rules; WQAR; normalised weighted ARM; NWARM; WARM; manufacturing cells; cell layout.
Int. J. of Industrial and Systems Engineering, 2013 Vol.15, No.3, pp.253 - 271
Available online: 29 Aug 2013