طراحی سیستم کانبان دو معیاره با استفاده از روش بازپخت شبیه سازی شده
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|10450||2002||16 صفحه PDF||سفارش دهید||5820 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers & Industrial Engineering, Volume 41, Issue 4, February 2002, Pages 355–370
In the kanban system, the main decision parameters are the number of kanbans and lot size. In this paper, an attempt has been made to set the number of kanbans at each station and the lot size required to achieve the best performance using simulated annealing technique. A simulation model with a single-card system has been designed and used for analysis. A bi-criterion objective function comprising of mean throughput rate and aggregate average kanban queue has been used for evaluation. Different perturbation schemes have been experimented and compared.
Just in time (JIT) production system is the manufacturing philosophy of producing what is needed at the right time and in right quantity (Hutchins, 1993). Kanban coupled with pull system of production is used as means of implementing JIT. Kanban means a ‘visible card’, which serves as a planning and information tool to smoothen the flow of material through the manufacturing and assembly process. The workstations located along the production lines only produce or deliver desired components when they receive a card and empty container, indicating that more parts will be needed in production. Each workstation will only produce enough components to fill containers and then stop. In addition, kanban limits the amount of inventory in the process by acting as an authorisation to produce. The essential elements in the design of kanban production system are the number of kanbans needed to link processes together and the appropriate unit of lot size (Berkley, 1992a).
نتیجه گیری انگلیسی
A simulation model of the single-card kanban system has been developed to determine the number of kanbans and lot size. A bi-criteria objective function consisting of throughput and aggregate kanban queue has been employed to obtain a solution that maximises the objective function value. Simulated annealing algorithm has been employed to search the solution space. Two types of perturbation schemes have been tried out. The results showed that there is no significant difference between the two schemes. It can be concluded that SAA can be applied to determine the kanban system parameters with the bi-criteria objective function.