كليدواژه :
سيستم توليد سلولي , تخصيص اپراتور , اثر يادگيري و فراموشي اپراتور , ماشين آلات چندكاره , خرابي ماشين آلات
چكيده فارسي :
در اين نوشتار دو مدل رياضي مختلط عدد صحيح براي طراحي سيستم توليد سلولي ارائه شده است. در مدل اول به بررسي هزينه هاي پيكربندي، پيكربندي مجدد، نصب و قطع ابزار، مصرف ابزار و خرابي ماشين آلات در محيطي پويا پرداخته شده است. در مدل دوم هزينه هاي مربوط به استخدام، اخراج، حقوق و دستمزد اپراتور كمينه مي شود. يكي از نوآوري هاي اساسي اين مدل درنظرگرفتن سطوح مختلف مهارتي بر اساس ويژگي يادگيري و فراموشي اپراتور است. همچنين به منظور به دست آوردن جواب بهينه، مدل سومي طراحي شده است كه هر دو مدل اول و دوم را دربرمي گيرد. مدل ها در نرم افزار گمز كدنويسي شده اند و نمونه هاي عددي از آن ها حل شده است. همچنين، به بررسي مقادير بهينه و زمان حل هر يك از مدل هاي خطي و غير خطي و بررسي مقادير بهينه ي مدل سلسله مراتبي و هم زمان پرداخته شده است.
چكيده لاتين :
Manufacturing flexibility is a basic requirement in order to increase both the revenue and customer satisfaction level. Group technology concept can be implemented in such cases. One of the most important applications of group technology concept in a production environment is Cellular Manufacturing System which includes four main sub problems; Cell formation, Group layout, Scheduling and Resource assignment. The cell formation (CF) is for assigning the machines into cells. The Group layout (GL) tries to find the optimal layout of machines within the cells and cells within the production floors. The group scheduling (GS) problem tries to minimize the total production time and ultimately resource assignment (RA) is to assign the manufacturing resources, such as
operators into cells, optimally. Accordingly, in this paper two mathematical models have been proposed in order to solve the cell formation and human resource assignment problems. The first mode is to minimize the inter/intra cell part trips, system reconfiguration cost, installing/uninstalling costs of tools on/from different machines and machine breakdown cost, respectively. The
second model tries to minimize the operator related issues such as hiring, firing, salary and the training costs. One of the main contributions of this paper is to consider the operator skill level. Actually, the training and forgetting effect of an operator determines his/her work skill level. So, in this paper, this issue is regarded in more details. These two nonlinear models have been linearized and solved using the Gams optimization package. Some numerical examples are generated randomly in order to the performance of proposed models. Moreover, in order to analyze find the optimal solution, the third model, which integrates two mentioned models, has been proposed. Based on the sensitivity analysis of the proposed models, the optimal assignment of operators can significantly improve the solution quality. Also, using the numerical examples' results, the linear model can obtain the optimal solutions in less computational effort in comparison to the nonlinear models.
