Cell formation in group technology: review, evaluation and directions for future research

The initial stage in the facilities design of cellular manufacturing systems involves the identification of part families and machine groups and forming cells possessing specific manufacturing capabilities. A new heuristic for the part family/machine group formation (PF/MGF) problem is presented in this paper. The distinguishing feature of this heuristic is its consideration of several practical criteria such as within-cell machine utilization, work load fractions, maximum number of machines that are assigned to a cell, and the percentage of operations of parts completed within a single cell. Computational results, based on several examples from the literature, show that this heuristic performs well with respect to more than one criteria. The heuristic also clarifies the source of various arguments in the literature concerning the ‘goodness’ of the solutions obtained by other researchers. An application of the heuristic to a large sample of industrial data involving 45 workcentres composed of 64 machines,...

A within-cell utilization based heuristic for designing cellular manufacturing systems

The aim of this work is to establish a methodology for an effective working of Reconfigurable Manufacturing Systems (RMSs). These systems are the next step in manufacturing, allowing the production of any quantity of highly customised and complex products together with the benefits of mass production. In RMSs, products are grouped into families, each of which requires a system configuration. The system is configured to produce the first family of products. Once it is finished, the system is reconfigured in order to produce the second family, and so forth. Therefore, the effectiveness of a RMS depends on the formation of the best set of product families. Therefore, a methodology for grouping products into families, which takes into account the requirements of products in RMSs, is an issue of core importance. These requirements are modularity, commonality, compatibility, reusability, and product demand. The methodology starts by calculating, for each product requirement, a matrix that summarises the similarity between pairs of products. Then, through the use of the AHP methodology, a unique matrix that comprises the similarity values between products is obtained. The Average Linkage Clustering algorithm is applied to this matrix in order to obtain a dendogram that shows the diverse sets of product families that may be formed.

A systematic approach for product families formation in Reconfigurable Manufacturing Systems

This paper reports the development of a number of similarity-based coefficients designed for applying hierarchical cluster analysis to the group technology machine cell formation problem. The paper also discusses an experimental investigation applying these and other well-known similarity coefficients in conjunction with some well-known clustering algorithms. The mixture model experimental approach is used for the investigation. A number of problems were generated via simulation, randomly ‘mixed’ to hide the original cellular structure, and the clustering techniques applied. Extensions of prior research include the development of new similarity coefficients, their comparative evaluation, and the incorporation of the concept of part ‘weighting’ into the cluster analysis, and hence, cell formation

An experiment investigating the application of clustering procedures and similarity coefficients to the GT machine cell formation problem

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author’s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.

http://apem-journal.org/Archives/2010/APEM5-3_151-162.pdf

Dynamic cellular manufacturing systems design—a comprehensive model

This paper provides an heuristic for the planning and study of machine-component groups in flexible production cells and flexible manufacturing systems. The problem of group formation defined on master-component process routes is undertaken in terms of minimum differences between masters and maximum combinations of masters. Group formation is a ‘hard’ combinatorial problem subject to exponential growth of complexity as the number of decision-making variables increases. The heuristic is designed to search the solution space of the problem in monotone-increasing order of solution costs so as to avoid the enumeration of solutions for cost minimization.

Machine-component group formation: an heuristic method for flexible production cells and flexible manufacturing systems

Statistical analysis of machine utilization has shown that about 45% of machine time is spent in tool changes between jobs. Reducing job change-over costs can therefore make a big difference in machine utilization. Job change-over costs depend greatly on the job sequence chosen for a. given job collection, and this paper shows that systematic job sequencing can reduce machine setting time by as much as 80%. Apart from the direct benefit accruing from systematic job sequencing, there can be indirect benefits through a continuing programme of tool and tooling standardization. The method is available in both a manual version and a computerized version, and a demonstration is given.

Multi-tool job sequencing for tool-change reduction

Recent developments in CAM and FMS require a computer-aided interface to connect product design and production planning to a manufacturing organisation which has been structured into mutually independent, cellular subsystems for flexible production. The paper provides some ideas and concepts for the planning, implementation and control of flexible production systems. These may be thought of as containing either flexible production cells or flexible manufacturing systems, A ‘flexible’ solution to the manufacturing organisation problem is a scheme in which the hospitality of cells towards product batches and the flexibility of jobs towards cells are maximised simultaneously. A changeover from FPCs to FMSs may constitute the ultimate goal of a modern organisation for manufacture.

Gunter Purcheck

Papers

Machine-component group formation: an heuristic method for flexible production cells and flexible manufacturing systems

Multi-tool job sequencing for tool-change reduction

Computer-aided organisation for manufacture