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Cellular manufacturing system (CMS) is an application of Group technology (GT) which harness the benefits of high production rate of a flow shop while maintaining flexibility, and utilizing facilities, of a job-shop. CM necessitates that parts and machines are allocated into cells to produce the identified part families so that productivity and flexibility of the system can be improved. In this paper, Non-dominated Sorting Genetic Algorithm II (NSGA II) has been proposed for clustering based on multiple objectives ie inter cellular movements and within cell load variations are considered to generate the pareto front. The processing data like operation sequence, machine capacity, processing time and batch sizes have been considered to form the realistic generalized cells. A case study has been considered to illustrate the developed methodology of cellular manufacturing.