Genetic cell formation using ratio level data in cellular manufacturing systems

Manufacturing cell formation is a useful strategy in batch type production industries for enhancing productivity and flexibility. The basic idea rests on grouping the parts into part families and the machines into machine cells. Most of the literature used zero-one incidence matrix representing the part visiting a particular machine as one and zero otherwise. The output is generated in the form of block diagonal structure where each block represents a machine cell and a part family. In such models real life production factors such as operation time and sequence of operations are not accounted for. In this paper, the operational time of the parts required for processing in the machines is considered. It is attempted to develop an algorithm using genetic algorithm (GA) with a combined objective of minimizing the total cell load variation and the exceptional elements. The results are compared with the solutions obtained from K-means clustering and C-linkage clustering algorithms.