A probabilistic model for machine cell formation

Seifoddini, Hamid

doi:10.1016/0278-6125(90)90070-x

Cited by 57 publications

(31 citation statements)

References 14 publications

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“…Simulation modelling has been effectively used in numerous studies to deal with the complexity of manufacturing systems (Seifoddini andDjassemi 1997, Sassani 1990). In this study, simulation is used to evaluate the performance of cellular manufacturing with the purpose of investigating the inconsistency between the performance of CM as envisioned by researchers and actual performance of CM as reported by practitioners.…”

Section: Methodsmentioning

confidence: 99%

A simulation analysis of factors influencing the flexibility of cellular manufacturing

Djassemi

2005

International Journal of Production Research

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The performance of cellular manufacturing (CM) systems in a variable demand and flexible workforce environment has been examined using simulation modelling. Discrepancies between academicians and practitioners' findings with respect to flexibility and uneven machine utilization in CM systems are discussed. The views of two parties were incorporated in simulation models to rectify the existing discrepancies. While the results of this study confirm the previous findings of academicians regarding the deterioration of the performance of CM in a variable product mix situation, it appears that those results may be significantly influenced by considering a flexible workforce. The simulation results show that the practice of using flexible crossed-trained operators can improve the flexibility of CM in dealing with an unstable demand and can reduce load imbalance inherent in machine dedication in manufacturing cells.

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Section: Methodsmentioning

confidence: 99%

A simulation analysis of factors influencing the flexibility of cellular manufacturing

Djassemi

2005

International Journal of Production Research

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“…For this reason, the relative stability of product mix is a prerequisite for the satisfactory performance of cellular manufacturing systems. While a cellular manufacturing system outperforms its corresponding job shop system under the product mix for which it is designed, it may fail to do so if the product mix changes (Seifoddini 1990). …”

Section: Definition Of the Problemmentioning

confidence: 99%

“…A few authors have tried to deal with the changing nature of product mix in the development of cellular manufacturing systems. Seifoddini (1990) has proposed a probabilistic machine cell formation model in which the expected value of intercellular material handling costs is used as a criterion for the selection among possible alternative machine cell configurations. Vakhria and Kaku (1993) have considered the impact of demand changes on the performance of cellular manufacturing systems.…”

Section: Introductionmentioning

confidence: 99%

Determination of a flexibility range for cellular manufacturing systems under product mix variations

Seifoddini¹,

Djassemi²

1997

International Journal of Production Research

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One of [he underlying assumptions in cellular manufacturing is that product mix is relalively stable over time. In this paper, a procedure for the sensitivity analysis of Ihe performance ofa cellular manufacturing system with respect to changes in the product mix is presented and a flexibility range representing ihe capability of Ihe system in dealing with these changes is detennined using simulation model ling. The simulation results in this study show that as the changes in ihc product mix increase the superiority of Ihe performance of the cellular manufacturing system to the corresponding job shop system diminishes.

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“…Seifoddini [12] considered uncertainty in form of probabilistic demands for a CFP, but under one period planning horizon. Tavakkoli-Moghaddam et al [13] extended their previous model and considered trapezoid instead of triangular fuzzy numbers to show the demand uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Demand Consideration In A Multi-objective Dynamic Cell Formation Problem Using A Robust Scatter Search

Amoozad-Khalili¹,

Ranjbar-Bourani²,

Al-e-hashem³

2010

J. Math. Computer Sci.

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This paper presents a multi-objective cell formation problem considering alternative process routes and machine utilization with fuzzy demand. Two conflicting objectives include the total cell load variation and sum of the other costs consisting machine cost, inter-cell material handling cost, parts purchasing, operation, maintenance, and reconfiguration of machines cost are to be minimized simultaneously. Moreover, we consider demand in fuzzy condition, because it is more realistic to take into account the inexact and uncertain nature of demand. Due to the complexity of this problem, we develop a scatter search algorithm. Also by using the Taguchi as a robust parameter design method, we tune the effective factors of the developed algorithm on two sizes of benchmark problems that are generated randomly. NSGAII and Scatter Search evaluated and the related results confirm the efficiency and the effectiveness of our proposed Scatter Search provides good output according to some quality measures, especially for large-sized problems.

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A probabilistic model for machine cell formation

Cited by 57 publications

References 14 publications

A simulation analysis of factors influencing the flexibility of cellular manufacturing

A simulation analysis of factors influencing the flexibility of cellular manufacturing

Determination of a flexibility range for cellular manufacturing systems under product mix variations

Fuzzy Demand Consideration In A Multi-objective Dynamic Cell Formation Problem Using A Robust Scatter Search

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