مقاله به زبان انگلیسی با عنوان The selection of the best control rule for a multiple-load AGV system using simulation and fuzzy MADM in a flexible manufacturing system

مقاله به زبان انگلیسی با عنوان The selection of the best control rule for a multiple-load AGV system using simulation and fuzzy MADM in a flexible manufacturing system

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مقاله به زبان انگلیسی با عنوان The selection of the best control rule for a multiple-load AGV system using simulation and fuzzy MADM in a flexible manufacturing system

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مقاله به زبان انگلیسی با عنوان The selection of the best control rule for a multiple-load AGV system using simulation and fuzzy MADM in a flexible manufacturing system

مقاله به زبان انگلیسی با عنوان The selection of the best control rule for a multiple-load AGV system using simulation and fuzzy MADM in a flexible manufacturing system

مقاله به زبان انگلیسی با عنوان The selection of the best control rule for a multiple-load AGV system using simulation and fuzzy MADM in a flexible manufacturing system

در فرمت ورد . 24 صفحه قابل ويرايش

 

Abstract: In this paper, pick up-dispatching problem together with delivery-dispatching problem of a multiple-load automated guided vehicle (AGV) system have been studied. By mixing different pick up-dispatching rules, several control strategies (alternatives) have been generated and the best control strategy has been determined considering some important criteria such as System Throughput (ST), Mean Flow Time of Parts (MFTP), Mean Tardiness of Parts (MFTP), AGV Idle Time (AGVIT), AGV Travel Full (AGVTF), AGV Travel Empty (AGVTE), AGV Load Time (AGVLT), AGV Unload Time (AGVUT), Mean Queue Length (MQL) and Mean Queue Waiting (MQW) were used in a part manufacturing system where each part had a due date. For ranking and selecting the best control strategy, a new framework based on MADM methods including fuzzy MADM and TOPSIS method (as one of MCDM methods) were developed to evaluate different strategies. For this reason, a field study was conducted to evaluate the importance weight of each criterion according to experts’ views. Then several simulation experiments which had been based on a flow path layout to find the results were conducted. Finally, by using TOPSIS method, the control strategies which had been based on the weights obtained from fuzzy MADM and the simulation results were ranked. Furthermore, a similar approach was used for determining the optimal fleet size in the flow path layout. The main contribution of this paper is developing a new approach combining the top managers’ views in selecting the best control strategy for AGV systems while trying to optimize the fleet size at the mean time by combining MADM, MCDM and simulation methods. The results show that the proposed approach is efficient and robust enough to be used in application fields like warehouses, ports and production lines.

Keywords: Multiple-load AGV system, Pick up-dispatching rules; Delivery-dispatching rules; Fuzzy MADM, TOPSIS, MCDM, Flexible Manufacturing System (FMS) and Fleet size optimization.


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