Grouping Maching using Genetic Algorithm for Dynamic Cell Layout Design

Abstract

Changes in the manufacturing sector due to changes in shorter product life cycles, market demands and also use of the latest technology in the company, this will result in changes in process flow and also change the layout in the production section, causing dynamic layout problems. Dynamic layout problems can be solved by using a manufacturing cell formation method which has a high degree of flexibility. In this study, algorithms used for grouping machines into manufacturing cells are Direct Clustering Algorithm and Rank Order Clustering. Then it will be improved by using Genetic Algorithm. The Dynamic Modified Spanning Tree Algorithm is also used to sort machines into a layout with a single-row structure and determine the length of the planning time window in the future. The goals of this research is to get the best solution from the two methods of grouping machines/parts into manufacturing cells and to obtain improvement results using Genetic Algorithms. For the design industry, the resulting dynamic cell layout is expected to reduce production costs, save material handling, be efficient in material flow, which in turn will be able to compete globally.