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Similarity-Based Cluster Analysis for the Cell Formation Problem

Similarity-Based Cluster Analysis for the Cell Formation Problem
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Author(s): Riccardo Manzini (University of Bologna, Italy), Riccardo Accorsi (University of Bologna, Italy)and Marco Bortolini (University of Bologna, Italy)
Copyright: 2013
Pages: 23
Source title: Industrial Engineering: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-1945-6.ch029

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Abstract

This chapter illustrates the cell formation problem (CFP) supported by similarity based methods. In particular, problem oriented indices are based on several factors which play an important role in the determination of the value of similarity between two generic machines, e.g. the number of machines visited by each part, the sequence of manufacturing operations, the production quantity for each part, et cetera. A numerical example illustrates the basic steps for the implementation of an effective hierarchical procedure of clustering machines into manufacturing cells and parts/products into families of parts. Literature presents many indices, but a few significant case studies and instances not useful to properly compare them and support the best choice given an operating context, i.e. a specific production problem. As a consequence the authors illustrate an experimental analysis conducted on a literature problem oriented instance to compare the performance of different problem settings and define best practices and guidelines for professional and practitioners.

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