Genetic Algorithm Based Re- configuration of Plant Layouts A case study on Akaki Spare Parts and Hand Tools Factory

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This paper describes a novel method based on genetic algorithms (GA) to solve the facilities re–configuration problem. Developing a proper floor layout is an important step in designing manufacturing facilities due to the impact of the layout to material handling cost and time, and its direct consequence on the overall productivity of the shop floor. Poor layout would result in having more parts spending longer time in moving from one facility to the other, and results in increased material handling costs. In contrast to the block layout the objective of facilities re-configuration is to find the appropriate placement of facilities with in the existing boundary of the factory floor for the new product coming in to the manufacturing system. The genetic algorithm based method developed to solve this uses the objective of minimizing the movement of materials being processed in the factory. This thesis investigates the potential of genetic algorithms in re-configuring factory floor facilities and presents a computer automated system for performing facilities reconfiguration task of an existing factory floor. The system integrates the powerful graphical capabilities of AutoCAD and the intricate search and optimization abilities of genetic algorithms for the purpose of solving facilities re-configuration problem. The computer automated system is implemented via Visual Basic 6.0. The interface features of Visual Basic and AutoCAD are utilized to capture the geometrical details of the existing factory floor layout and to represent the final solution graphically. Akaki Spare Parts and Hand Tools factory is selected as one of the factory which is suffering from re-configuration of its factory floor facilities. The final part of this thesis shall validate the systems performance taking ASPSC’s hand tools and cutlery division facilities as a case which is mostly dedicated to produce one type of product at a time.



Mechanical Engineering