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“A Simulation Modeling of Scheduling of Automated Guided Vehicles in Flexible Manufacturing Systems Environment”
Prof. Sumit Kumar Pandey1, Prof. Amit Sahay2, Prof. Virendra Rajput

Published in: Journal for Advance Research in Applied Sciences
Volume- 5, Issue-6, pp.89-95, Nov 2017
DPI :-> 16.10089.JARAS.2017.V5I6.8995.2113



Abstract
Automated Guided Vehicles (AGVs) are among the fastest and advanced material handling technology that are used in various industrial applications today. Flexible Manufacturing systems (FMS) are well suited for concurrent manufacturing of a wide variety of parts in low quantity. The use of AGVs is increasing day by day for the material movement in production lines of flexible manufacturing plants. The purpose is to increase efficiency in material transfer and increase manufacturing. The order of scheduling of operations on machine centers as well as the scheduling of Automated Guided Vehicles are important factors contributing to the overall efficiency of flexible manufacturing system (FMS). In this work, scheduling of job is done for a particular type of flexible manufacturing system (FMS) environment by using the technique of optimization called the genetic algorithm (GA). A code was developed to find the optimal solution and generate random values in Ms-Excel. When a chromosome is input, the GA works upon it and produces same number of offspring‘s. The number of iterations takes place until the optimum solution is obtained. Here we have worked upon eight problems, with different no. of machines and no. of jobs. The input parameters used are Travel Time matrix and Processing Time matrix with the number of machines and number of jobs. The results obtained are very quite close to the results obtained by other techniques and by other scholars.

Key-Words / Index Term
AGVs; FMS; Make Span Time; DP; LP; GA; Chromosome.

How to cite this article
Prof. Sumit Kumar Pandey1, Prof. Amit Sahay2, Prof. Virendra Rajput , ““A Simulation Modeling of Scheduling of Automated Guided Vehicles in Flexible Manufacturing Systems Environment””, Journal for Advance Research in Applied Sciences, 5, Issue-6, pp.89-95, Nov 2017. DPI:16.10089.JARAS.V5.I6.2113