SAPFOCS: a metaheuristic based approach to part family formation problems in group technology
نویسندگان
چکیده
This article deals with Part family formation problem which is believed to be moderately complicated to be solved in polynomial time in the vicinity of Group Technology (GT). In the past literature researchers investigated that the part family formation techniques are principally based on production flow analysis (PFA) which usually considers operational requirements, sequences and time. Part Coding Analysis (PCA) is merely considered in GT which is believed to be the proficient method to identify the part families. PCA classifies parts by allotting them to different families based on their resemblances in: (1) design characteristics such as shape and size, and/or (2) manufacturing characteristics (machining requirements). A novel approach based on simulated annealing namely SAPFOCS is adopted in this study to develop effective part families exploiting the PCA technique. Thereafter Taguchi's orthogonal design method is employed to solve the critical issues on the subject of parameters selection for the proposed metaheuristic algorithm. The adopted technique is therefore tested on 5 different datasets of size 5 {\times} 9 to 27 {\times} 9 and the obtained results are compared with C-Linkage clustering technique. The experimental results reported that the proposed metaheuristic algorithm is extremely effective in terms of the quality of the solution obtained and has outperformed C-Linkage algorithm in most instances.
منابع مشابه
Simulated annealing and artificial immune system algorithms for cell formation with part family clustering
Cell formation problem (CFP) is one of the main problems in cellular manufacturing systems. Minimizing exceptional elements and voids is one of the common objectives in the CFP. The purpose of the present study is to propose a new model for cellular manufacturing systems to group parts and machines in dedicated cells using a part-machine incidence matrix to minimize the voids. After identifying...
متن کاملA two Stage Heuristic Solution Approach for Resource Assignment during a Cell Formation Problem
Design of Cellular Manufacturing System involves four major decisions: Cell formation (CF), Group layout (GL), Group scheduling (Gs) and Resource assignment (RA). These problems should be regarded, concurrently, in order to obtain an optimal solution in a CM environment. In this paper a two stage heuristic procedure is proposed for CF and RA decisions problem. The solution approach contains a ...
متن کاملIntegrated Approach for Cellular Manufacturing a Case Study (TECHNICAL NOTE)
To cope with fast changing customer requirements, industrial demands and to meet stringent specifications of customers Cellular Manufacturing Systems has become an effective tool in hands of manufacturers. Most of the published literature on cell formation earlier considers only the data available in the route sheets and ignored subproblems associated with cell formation. There is a need to dev...
متن کاملIntegrative Cell Formation and Layout Design in Cellular Manufacturing Systems
This paper proposes a new integrative view of manufacturing cell formation and both inter-cell and intra-cell layout problems. Cells formation and their popular bi-directional linear layout are determined simultaneously through a Dynamic Programming algorithm (with the objective of minimizing the inter-cell flow cost under a cell size constraint). This Dynamic Programming algorithm is implement...
متن کاملA new metaheuristic genetic-based placement algorithm for 2D strip packing
Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. I...
متن کامل