Simulation-based methodology for machine cell design

Kamrani, Ali Κ.; Hubbard, Kevin M.; Parsaei, Hamid R.; Leep, Herman R.

doi:10.1016/s0360-8352(97)00159-9

Cited by 13 publications

(8 citation statements)

References 6 publications

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“…Simulation is widely used in the world and therefore it is very familiar ( [20], [21], [22] and other). The most important reasons and advantages of simulation methodology for modelling manufacturing systems are that [21]:…”

Section: Simulation Studiesmentioning

confidence: 99%

“…• manufacturing cell sizing such as number of duplicates of each type of machine in the cell, queue sizes, and others design parameters (e.g in [20], [22]); • comparison of functional, cellular and hybrid layouts (e.g in [23], [24], [25]); • productivity analysis (e.g in [26], [27], [30]);…”

Section: Simulation Studiesmentioning

confidence: 99%

“…[20], [21], [22], [25], [30] and others. In this study, which evaluate the effect of transfer time in CM system four performance measures were employed.…”

Section: Performance Measuresmentioning

confidence: 99%

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An improvement of a cellular manufacturing system design using simulation analysis

Hachicha¹,

Masmoudi²,

Haddar³

2007

Int j simul model

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Cell Formation (CF) problem involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. Many researches have suggested methods for CF. Few of these methods; have addressed the possible existence of exceptional elements (EE) in the solution and the effect of correspondent intercellular movement, which cause lack of segregation among the cells. This paper presents a simulation-based methodology, which takes into consideration the stochastic aspect in the cellular manufacturing (CM) system, to create better cell configurations. An initial solution is developed using any of the numerous CF procedures. The objective of the proposed method which provides performances ratings and cost-effective consist in determine how best to deal with the remaining EE. It considers and compares two strategies (1) permitting intercellular transfer and (2) exceptional machine duplication. The process is demonstrated with a numerical example.

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Section: Simulation Studiesmentioning

confidence: 99%

Section: Simulation Studiesmentioning

confidence: 99%

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An improvement of a cellular manufacturing system design using simulation analysis

Hachicha¹,

Masmoudi²,

Haddar³

2007

Int j simul model

View full text Add to dashboard Cite

show abstract

“…These methods consist of the testing of alternative designs using simulation and selecting the most suitable design based on multicriteria decision-making techniques or knowledge-based decision tools. Kamrani, Hubbard, Parsaei, and Leep (1998) used a simulation-based methodology for machine cell design. Both design and manufacturing attributes were considered.…”

Section: Integrating Simulations Into the Design Processmentioning

confidence: 99%

An integrated methodology for manufacturing systems design using manual and computer simulation

Paquet

Lin

2003

Hum Ftrs & Erg Mfg Svc

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Traditional approaches to manufacturing systems design utilize a sequential procedure that focuses on production capacity requirements, with human operator task design developed late in the systems design phase. Implementing manufacturing systems in this way is difficult when operations management must design flexible and efficient processes, with an often incomplete understanding of how people can best perform within the system. This study developed an integrated methodology that uses both manual and computer simulations to evaluate system performance and ergonomic issues early in the system design process. Information about operator performance and ergonomics is obtained in the manual simulations, while estimates of operator utilization and system throughput is obtained through computer simulations. An iterative design process is used, with the results of manual and computer simulations informing each other during subsequent simulations. An industrial case study is presented here to demonstrate the effectiveness of this methodology. The results show that the methodology can be used to design manufacturing systems with significant savings in labor cost and improved manufacturing system flexibility.

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“…the performance of machine cell equipments, workshop layout and the whole system running status) in addition to the scheduling rules [1][2][3]. There are many papers on the problems of combining scheduling rules and optimisation in which many efficient ways are put forward [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A New Simulation Optimisation System for the Parameters of a Machine Cell Simulation Model

Guo

Chen

Wang

et al. 2003

The International Journal of Advanced Manufacturing Technology

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Combinatorial scheduling rules optimisation has been a focus of most of the studies about flexible manufacturing systems (FMS), in the design and control of which, the performance optimisation of a machine cell is of great importance. To optimise the performance of a machine cell, the paper describes the design of a simulation optimisation system. It is constructed according to the principle of separating the models from the algorithms. The system consists of a simulation module and an optimisation module. The optimisation algorithms are the core of the paper, a new hybrid optimisation algorithm is proposed by combining the features of region-shrunk genetic algorithms with an enhanced continuous tabu search. The paper provides an example to demonstrate the validity of the system.

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Simulation-based methodology for machine cell design

Cited by 13 publications

References 6 publications

An improvement of a cellular manufacturing system design using simulation analysis

An improvement of a cellular manufacturing system design using simulation analysis

An integrated methodology for manufacturing systems design using manual and computer simulation

A New Simulation Optimisation System for the Parameters of a Machine Cell Simulation Model

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