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Authors
Affiliations
1 School of Mechanical Engg., SASTRA (Deemed University), Thanjavur-613 402, IN
2 Dept. of Production Engg., National Institute of Technology, Trichy-625 015, IN
3 Dept. of Mechanical Engg., Kumaraguru College of Engg., Coimbatore-641 006, IN
4 Dept. of Computer Science and Engg., PR Engg. College, Thanjavur-613 403, IN
Source
Manufacturing Technology Today, Vol 3, No 12 (2004), Pagination: 8-11
Abstract
Flexible Manufacturing System (FMS) is a highly automated system consisting of computer controlled machines and peripherals combined with intensive material and dataflow. Extensive research has been conducted to design and solve the operational problems of FMS, but many of the problems still remain unsolved. In particular, the scheduling task, the control problem during the operation, is of importance owing to the dynamic nature of the FMS such as flexible parts, tools and Automated Guided Vehicle (AGV) routings. Owing to its highly automated nature, a typical FMS has a high investment cost. Hence, it becomes necessary to identify the most efficient scheduling rules at the operating stage. Automated Guided Vehicles (AGVs) are among various advanced material handling techniques that are finding increasing applications today. They can be interfaced to various other production and storage equipment and controlled through an intelligent computer control system. Simultaneous scheduling can be defined as the scheduling of machines and a number of identical AGVs in a FMS. In this paper, simultaneous scheduling of parts and AGVs is done for a particular type of FMS environment by using a nontraditional optimization technique called Genetic Algorithm (GA). The problem considered is a large variety problem and objective is combined objective (minimizing penalty cost and minimizing machine idle time). The results are found and conclusions are presented.
