1Assistant Professor, Department of Mechanical Engineering, K.L.E.F (K.L) University, Guntur
2Head, Mechanical Engineering, Govt Polytechnic College, Paderu, Vishakhapatnam
3Director & Professor, Department of Mechanical Engineering, J.N.T. University, Kakinada
4Research Scholar, U.C.E. J.N.T. University, Kakinada, Andhra Pradesh, India
*Corresponding Author Email: medikondu@kluniversity.in
Online published on 11 March, 2014.
High degree of flexibility and quick response times have become essential features of modern manufacturing systems where customers are demanding for a variety of products with reduced product life cycles. Flexible manufacturing system (FMS) is proved to be the right answer to meet these challenges of global competition. The performance of an FMS is highly dependent on the selection of the right scheduling policy for the control system. Traditionally scheduling problems consider machines as the only constraining resources but this is no longer correct as material handling equipment is becoming more and more valuable resource in an FMS. Hence its operations should be optimized and above all synchronized with machine operations. Scheduling of an FMS is a well known NP-hard problem which is very complex, due to additional considerations like material handling and alternative routing. Literature reveals that, in many of the cases scheduling of both the machines and material handling system was addressed independently. Hence in this work an attempt has been made to schedule both of them simultaneously Optimum Automated Guided Vehicles (AGVs) operation plays a crucial role in improving the performance of Flexible Manufacturing System (FMS). One of the main elements in the implementation of AGV is task scheduling. This will enhance the productivity, Minimize delivery cost and optimally utilize the entire fleet. This enhance article Deals with hybrid Genetic Vehicle Heuristic Algorithm (HGVHA) for simultaneous Scheduling of machines and AGVs minimization of mean tardiness function The method is found to provide better solution.
Flexible Manufacturing System, Automated Guided Vehicle, Hybrid Genetic Vehicle Heuristic Algorithm