Design of a cellular manufacturing system: A syntactic pattern recognition approach

Wu, Hong; Venugopal, R.; Barash, Moshe M.

doi:10.1016/0278-6125(86)90002-6

Cited by 57 publications

(11 citation statements)

References 4 publications

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“…This can be difficult, as there does not seem to be any analytic means to calculate k for a particular matrix. Wu et al (1986) use a syntactic pattern recognition approach to identify elementary strings of machines that are then clustered using an SLCA dendrogram. The use of SLCA in clustering requires us to guess the number of clusters (Wu et al 1986).…”

Section: Machine-part Matrix Cluslering-an Overviewmentioning

confidence: 99%

“…Wu et al (1986) use a syntactic pattern recognition approach to identify elementary strings of machines that are then clustered using an SLCA dendrogram. The use of SLCA in clustering requires us to guess the number of clusters (Wu et al 1986). This renders the method susceptible to the generic drawbacks ofSLCA.…”

Section: Machine-part Matrix Cluslering-an Overviewmentioning

confidence: 99%

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Principal component analysis for evaluating the feasibility of cellular manufacturing without initial machine-part matrix clustering

Arvindh

Irani

1994

International Journal of Production Research

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Section: Machine-part Matrix Cluslering-an Overviewmentioning

confidence: 99%

Section: Machine-part Matrix Cluslering-an Overviewmentioning

confidence: 99%

Principal component analysis for evaluating the feasibility of cellular manufacturing without initial machine-part matrix clustering

Arvindh

Irani

1994

International Journal of Production Research

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“…Syntactic pattern recognition techniques evolved from formal language theory are applied to the family formation problem by Wu et al (1986). Xu and Wang (1989) have developed a part family formation method based on fuzzy mathematics in which the uncertainty inherent in the similarity measurement is emphasized in the family formation process.…”

Section: Artificial Intelligence Methodsmentioning

confidence: 99%

Establishment of a neurocomputing model for part family/machine group identification

Moon

1992

J Intell Manuf

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The part family/machine group identification (or formation) is the crux of implementing Group Technology, and a well-studied subject. However, most of the approaches have neglected the original family concept proposed by Burbidge, that there are already 'naturally occurring' families existing. A desirable approach should be that of identifying these families rather than forcing to form the families. This paper describes a neurocomputing model which is inspired by the way the biological neuronal systems reach intelligent decisions. A comprehensive survey of previous approaches is presented. The simulation results from an example are provided to show how the model is used to identify the part families and the machine groups. The advantages of the neurocomputing model and future directions are discussed.

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“…Lemoine and Mutel (1983) presented a dynamic clustering technique for machine grouping. Wu et al (1986) suggested a method based on pattern recognition.…”

Section: Introductionmentioning

confidence: 99%

Machine grouping problem in cellular manufacturing systems— an integer programming approach

Gunasingh

Lashkari

1989

International Journal of Production Research

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In this paper a methodology is proposed to group the machines in cellular manufacturing systems based on the tooling requirements of the parts, toolings available on the machines and the processing times. Two 0-1 integer programming formulations are proposed. These formulations assume that the part families are known. The first formulation groups the machines based on the compatibility of parts with machines. The second formulation groups the machines in order to minimise the cost of allocating the machines and the cost of intercell movement. These formulations take into account the limitations on the number of machines in a group and the number of machines available of a particular type. The application of these formulations is illustrated using an example.

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Design of a cellular manufacturing system: A syntactic pattern recognition approach

Cited by 57 publications

References 4 publications

Principal component analysis for evaluating the feasibility of cellular manufacturing without initial machine-part matrix clustering

Principal component analysis for evaluating the feasibility of cellular manufacturing without initial machine-part matrix clustering

Establishment of a neurocomputing model for part family/machine group identification

Machine grouping problem in cellular manufacturing systems— an integer programming approach

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