Production planning and worker assignment in a dynamic virtual cellular manufacturing system

Nikoofarid, Elnaz; Aalaei, Amin

doi:10.1080/17509653.2012.10671211

Cited by 13 publications

(11 citation statements)

References 24 publications

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“…Therefore, it is possible to accept null hypothesis in this case (Cameron, 2012;Sekaran, 2003). More rigorous data analyses can be performed, for example, by means of multi-objective programming (Xu and Yao, 2009), a dynamic virtual environment (Nikoofarid and Aalaei, 2012), a resource assignment model under fuzzy environment (Yao and Xu, 2012), and a multi-criteria decision analysis (Makan et al, 2012). However, these analyses are beyond the scope of this paper.…”

Section: Discussionmentioning

confidence: 99%

A study of the factors affecting construction time in Western Australia

Wong¹,

Vimonsatit²

2012

Sci. Res. Essays

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Delays are major problems that face the Western Australia's construction industry. Delays can lead to many negative effects such as cost overruns, and is of high concern to those who are involved in the construction industry. This study was set to identify the major causes of delays in the Western Australian construction industry, by means of a literature review and a questionnaire survey. A total of 48 delay factors were obtained from literature review and were further categorised into eight major groups that contributed to the causes of delay. The questionnaire survey was distributed to the targeted respondents from a combination of clients, contractors, and consultants in Perth, Western Australia. About 32 respondents participated in the survey. Based on the data received, albeit limited, the top ten most important causes identified were: (1) Shortage of skills; (2) Financial difficulties; (3) Shortage of labour; (4) Unrealistic deadlines for project completion; (5) Unforeseen ground conditions; (6) Poor organization of the contractor or consultant; (7) Poor communication; (8) Underestimation of time of completion; (9) low speed of decision; and (10) Design errors made by designers.

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Section: Discussionmentioning

confidence: 99%

A study of the factors affecting construction time in Western Australia

Wong¹,

Vimonsatit²

2012

Sci. Res. Essays

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“…A genetic algorithm was employed to solve the problem. Worker flexibility is also studied by Murali et al, 20 Hamedi et al, 16 and Nikoofarid and Aalaei 21 in VCMSs. Goldengorin et al 5 proposed a flexible CF model based on the p-median problem to adapt real-life constraints such as capacities and operational sequences.…”

Section: Literature Reviewmentioning

confidence: 98%

“…The proposed mathematical model captures the capability of workers in doing different jobs. Nikoofarid and Aalaeib 21 presented a mathematical model for a production-planning problem in dynamic virtual cells by considering the demand and part mix variations, machine capacities and the availability of the workers. Another study in dynamic systems was proposed by Soolaki.…”

Section: Literature Reviewmentioning

confidence: 99%

Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

Baykasoğlu

Topaloğlu

Şenyüzlüler

2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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Cell formation deals with grouping of machines and parts in manufacturing systems according to their compatibility. Manufacturing processes are surrounded with an abundance of complex constraints which should be considered carefully and represented clearly for obtaining high efficiency and productivity. Constraint programming is a new approach to combinatorial optimization and provides a rich language to represent complex constraints easily. However, the cell formation problems are well suited to be solved by constraint programming approach since the problem has many constraints such as part-machine requirements, availabilities in the system in terms of capacity, machine and worker abilities. In this study, the cell formation problem is modeled using machine, part processing and worker flexibilities via resource element–based representation. Resource elements define the processing requirements of parts and processing capabilities of machines and workers, which are resource-independent capability units. A total of 12 case problems are generated, and different search phases of constraint programming are defined for the solution procedure. The cell formation problem is modeled in both constraint programming and integer programming, and a comparative analysis of constraint programming and integer programming model solutions is done. The results indicate that both the models are effective and efficient in the solution of the cell formation problem.

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“…The objective of their proposed model was finding optimum number of virtual cells to minimize production, material transportation, inventory and manufacturing costs in each period. Nikoofarid and Aalaei (2012) designed a mathematical model for production planning in a dynamic virtual cellular manufacturing (DVCM) considering demand and part mix variation, machine capacity and as machine and worker availability as the main constraints. Han et al (2014) addressed the problem of virtual cellular multi-period dynamic reconfiguration.…”

Section: Literature Reviewmentioning

confidence: 99%

A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem

et al. 2016

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Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one of important topics in CMS, have led to the introduction of virtual CMS (VCMS). This research addresses a bi-objective dynamic virtual cell formation problem (DVCFP) with the objective of finding the optimal formation of cells, considering the material handling costs, fixed machine installation costs and variable production costs of machines and workforce. Furthermore, we consider different skills on different machines in workforce assignment in a multi-period planning horizon. The biobjective model is transformed to a single-objective fuzzy goal programming model and to show its performance; numerical examples are solved using the LINGO software. In addition, genetic algorithm (GA) is customized to tackle large-scale instances of the problems to show the performance of the solution method.

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Production planning and worker assignment in a dynamic virtual cellular manufacturing system

Cited by 13 publications

References 24 publications

A study of the factors affecting construction time in Western Australia

A study of the factors affecting construction time in Western Australia

Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem

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