Author : Furquan Khan and Amit Sahay

Automated Guided Vehicles (AGVs) are among the fastest and advanced material handling technology that are utilized in various industrial applications today. They can be overlapped to various other manufacturing and storage system and controlled through an advanced computer control system. Flexible Manufacturing systems (FMS) are compatible for concurrent manufacturing of a good sort of parts in low quantity. The Flexible Manufacturing systems elements can operate in a non parallel manner and the scheduling problems are harder. The use of AGVs is increasing day by day for the fabric movement in production lines of flexible manufacturing plants. The purpose is to extend efficiency in material transfer and increase manufacturing. Though the hardware of Automated Guided Vehicle has made remarkable enhancement in the field but the software control of the speed still lacks in many applications. 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 seek out 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’ve worked upon eight problems, with different no. of machines and no. of jobs. The input parameters used are time period matrix and time interval matrix with the amount of machines and number of jobs. The results obtained are very quite close to the results obtained by other techniques and by other scholars.

Keywords: Automated Guided Vehicles, loading point, delivering point, make span time, genetic algorithm, flexible manufacturing system, time travel matrix, problem time matrix, chromosome

Article published in International Journal of Current Engineering and Technology, Vol.11, No.1 (Jan/Feb 2021)