ارائه یک مدل ریاضی کارآ برای مسئله طراحی چیدمان تسهیلات در فضای پیوسته در یک سیستم تولید سلولی (مطالعه موردی: شرکت BATA) (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
اساس کارکرد سیستم های تولید سلولی بر پایه تعریف و شناسایی نوعی شباهت در میان قطعاتی است که باید در یک دوره برنامه ریزی تولید شوند. تشکیل سلول و طراحی چیدمان از مراحل مهم اجرای این نوع از سیستم های تولیدی اند. در این مقاله یک مدل برنامه ریزی ریاضی غیرخطی جدید برای مسئله تشکیل سلول ارائه شده است که در آن با بهره گیری از مفهوم فاصله متعامد، چیدمان ماشین آلات در یک فضای پیوسته تعیین می شود. در مدل ارائه شده، با استفاده از مزایای در نظر گرفتن جانمایی سلولی در تابع هدف، هزینه های جابه جایی درون و بین سلولی قطعات دقیق محاسبه می شود. با توجه به پیچیدگی های مسئله، مدل ریاضی ارائه شده ازنظر پیچپدگی در زمره مسائل سخت قرار می گیرد که برای حل آن از الگوریتم ژنتیک و ازدحام ذرات استفاده شده است. به منظور نشان دادن کارآیی مدل و الگوریتم های حل ارائه شده، از اطلاعات تولیدی یک مسئله واقعی استفاده شده و 30 نمونه مسئله دیگر در ابعاد مختلف ارائه شده است که نتایج حاصل بیانگر عملکرد بهتر الگوریتم ژنتیک در مقایسه با الگوریتم ازدحام ذرات در کیفیت جواب های حاصل شده است.Proposing an efficient mathematical model for the continuous layout design in a cellular manufacturing system The real-case of BATA company
Purpose: The fundamental function of a cellular manufacturing system (CMS) is based on the definition and recognition of the type of similarity among the parts that should be produced in a planning period. Cell formation (CF) and cell/machine layouts are two major steps in implementing the CMS design. This paper aims to propose a new mathematical nonlinear programming model for cell formation that employs the rectilinear distance concept to determine layout in a continuous space. In the proposed model, the benefits of cellular layout consideration are used, and the objective function computes the cost of cell reconfiguration and the costs of intra-cell and inter-cell material handling movements. Due to its problem complexity, a genetic algorithm (GA) and a particle swarm optimization (PSO) algorithm are proposed to solve the problem. To address the efficiency of the linearized model and solution methods, the production information of a real case study is used and 30 test problems in different dimensions are presented. Design/methodology/approach: In this paper, a mathematical programming model of cell formation and cell layout has been proposed in a continuous space, using the concept of rectilinear distance. In the proposed model, production information similar to the production flow between machines, alternative process routing, cells capacity, and the inter-cell and intra-cell transportation costs has been considered. Due to the nature and complexity of the proposed model, two metaheuristic algorithms, i.e., GA and PSO have been also developed for larger problems. Findings: In this paper a real case study in the BATA company was studied and the result of configuration was illustrated. By computing the efficiency of the linearized model and solution methods, the production information of a real case study was used and 30 test problems in different dimensions were presented. Findings highlighted the high efficiency of the genetic algorithm in solving large-scale problems. Research limitations/implications: Issues such as assuming similar dimensions for machines or their constant availability are considered as the limitations of this study. For future research, the following subjects can be attractive and the present study can provide the necessary background for researchers who seek to work on such subjects: Considering unequal dimensions for machines; in the proposed model, machines were considered as squares of equal area with unit dimension. To obtain a more appropriate schema from the space of a job shop, machines’ dimensions can be assumed as the input parameters. Developing probabilistic models and fuzzy model factors (e.g., available machines, operation time, costs, transportation time, and demand for each part) can be considered fuzzy or probabilistic. To make the model more realistic, production data such as setup times and holding inventory between periods can be incorporated. Also, the proposed model can be integrated with the scheduling problem. Practical implications: CMS, which is the most important application of GT, overcomes the inefficiency of traditional approaches by reducing transportation time and distance. A flow shop layout has high efficiency in a mass production system, while a job shop is a very flexible system for producing various parts. Each of these systems does not have any other benefits. The CMS is an approach between the two manufacturing systems and aims to improve flexibility and efficiency to produce manufacturing groups in different sizes. In a CMS, machines and parts assignment to cells must impose a minimum cost on the system. Due to the practical nature of the proposed mathematical model, a real case was studied in which, the production information of the BATA company was used. Originality/value: In this study, a new non-linear mixed-integer programming model was proposed which considered the simultaneous cell formation and intra-cell and inter-cell layouts in a continuous space. The
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