A genetic algorithm tool for designing manufacturing facilities in the capital goods industry

The layout of manufacturing facilities has a large impact on operational effectiveness. This paper describes the use of clustering methods for identifying potential manufacturing cells. It is shown that these approaches produce inconclusive results for capital goods companies that produce complex products. The development of a Genetic Algorithm based optimisation method is described that minimises material movement for a given schedule of work. The model includes geometric information on resources and building constraints. The tool may be used for brown-field or green-field layout design problems. It has been applied using data obtained from an engineer-to-order/make-to-order capital goods company. The algorithm produces layouts that significantly reduce the total distance travelled by components in both green field and brown field situations.