Forming part families by using genetic algorithm and designing machine cells under demand changes

Jeon, Geonwook; Leep, Herman R.

doi:10.1016/j.cor.2005.03.033

Cited by 77 publications

(29 citation statements)

References 22 publications

(33 reference statements)

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“…Defersha and Chen (2006) used parallel machines and outsource services to overcome dynamic part demand defects in cell forming process. Jeon and Leep (2006) presented a model for scheduling dynamic cells where machine failures can cause waiting times and reduce system capacity accordingly. Tavakkoli-Moghaddam, Aryanezhad, et al (2007) considered dynamic part demands and parts mixed for a reconfigurable part routing problem.…”

Section: Fig 1 Intracellular and Intercellular Materials Transferringmentioning

confidence: 99%

A new method for decreasing cell-load variation in dynamic cellular manufacturing systems

Delgoshaei¹,

Ariffin²,

Baharudin³

et al. 2016

10.5267/j.ijiec

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Cell load variation is considered a significant shortcoming in scheduling of cellular manufacturing systems. In this article, a new method is proposed for scheduling dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. The aim of this method is to control cell load variation during the process of determining the best trading off values between in-house manufacturing and outsourcing. A genetic algorithm (GA) is developed because of the high potential of trapping in the local optima, and results are compared with the results of LINGO ® 12.0 software. The Taguchi method (an L_9 orthogonal optimization) is used to estimate parameters of GA in order to solve experiments derived from literature. An in-depth analysis is conducted on the results in consideration of various factors, and control charts are used on machine-load variation. Our findings indicate that the dynamic condition of product demands affects the routing of product parts and may induce machine-load variations that yield to cell-load diversity. An increase in product uncertainty level causes the loading level of each cell to vary, which in turn results in the development of "complex dummy sub-cells". The effect of the complex sub-cells is measured using another mathematical index. The results showed that the proposed GA can provide solutions with limited cell-load variations.

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Section: Fig 1 Intracellular and Intercellular Materials Transferringmentioning

confidence: 99%

A new method for decreasing cell-load variation in dynamic cellular manufacturing systems

Delgoshaei¹,

Ariffin²,

Baharudin³

et al. 2016

10.5267/j.ijiec

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show abstract

“…On the other hand, in the CMS C it is assumed that each part is processed in one cell or outsourced totally considering machine capacity (Schaller, 2007;Jeon & Leep, 2006;Ghezavati & Saidi-Mehrabad, 2011). This approach is clearly illustrated in Fig.…”

Section: Classical Cms Modelmentioning

confidence: 99%

“…The main purpose of CMS is to determine the parts families and machine cells under pre-defined objectives and constraints. The CMS has more advantages such as: decreased setup times, reduced work-in-process inventories, improved product quality, shorter lead times, reduced tool requirements, improved productivity, better quality and production control, increment in flexibility and decreased material handling cost (Solimanpur et al, 2009;Jeon & Leep, 2006). The issue of CMS has been widely investigated in the literature and it has received more attention by authors in the recent decades (see Singh (1993) for a literature review on CMS).…”

Section: Introductionmentioning

confidence: 99%

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A mathematical model in cellular manufacturing system considering subcontracting approach under constraints

Forghani¹,

Sobhanallahi²,

Mirzazadeh³

et al. 2012

MSL

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In this paper, a new mathematical model in cellular manufacturing systems (CMSs) has been presented. In order to increase the performance of manufacturing system, the production quantity of parts has been considered as a decision variable, i.e. each part can be produced and outsourced, simultaneously. This extension would be minimized the unused capacity of machines. The exceptional elements (EEs) are taken into account and would be totally outsourced to the external supplier in order to remove intercellular material handling cost. The problem has been formulated as a mixed-integer programming to minimize the sum of manufacturing variable costs under budget, machines capacity and demand constraints. Also, to evaluate advantages of the model, several illustrative numerical examples have been provided to compare the performance of the proposed model with the available classical approaches in the literature.

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“…A simulated annealing algorithm was applied to solve the presented problem. Jeon and Leep [17] developed a two-phase procedure to con gure a CMS. In the rst phase, they used a genetic algorithm to obtain part families using a new similarity coecient.…”

Section: Introductionmentioning

confidence: 99%

A two-stage stochastic model for designing cellular manufacturing systems with simultaneous multiple processing routes and subcontracting

2017

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Abstract. In recent decades, many researchers have studied the cellular manufacturing system with consideration of various issues such as scheduling, production planning, layout, reliability, etc. However, limited research papers have investigated this problem in an uncertain environment. The present paper addresses a stochastic problem in cellular manufacturing systems considering simultaneous multiple routings and subcontracting. In the developed problem, each part can be simultaneously produced in multiple processing routes. It is also assumed that the unsatis ed part demands as a result of limited machine capacity or high manufacturing cost could be outsourced. A two-stage stochastic programming approach is employed to take the uncertainty into consideration and to formulate the problem. The objective function is to minimize the summation of production, subcontracting, material handling, and machine idleness costs. A sample average approximation method is applied as a solution method. Also, for further illustration of the problem, a numerical example is solved and sensitivity analyses are conducted. Finally, through some numerical examples extracted from related literature, the advantages of constructing a stochastic optimization model for the problem are demonstrated.

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Forming part families by using genetic algorithm and designing machine cells under demand changes

Cited by 77 publications

References 22 publications

A new method for decreasing cell-load variation in dynamic cellular manufacturing systems

A new method for decreasing cell-load variation in dynamic cellular manufacturing systems

A mathematical model in cellular manufacturing system considering subcontracting approach under constraints

A two-stage stochastic model for designing cellular manufacturing systems with simultaneous multiple processing routes and subcontracting

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