Research On The Key Technologies Of Manufacturing Cell Formation

There are large numbers of small-medium enterprises, which adopt multiple products and small batch production mode, in our country at present. How to provide the individuation and high quality products using limit cost is the key of survive for manufacturing enterprise. Inspired by principles and advantages of the group technology (GT) philosophy, cellular manufacturing system (CMS) designed for lot size production has recently became popular, and with the modest ancillary support can approach the economical benefits of mass production systems. Cell formation (CF) is the first and important stage in designing a CMS in order to form a set of manufacturing cells.The method of determining the cell number of cell formation, the optimal approach of cell formation for CMS, evaluation and selection of cell formation individuals and development of software platform are deeply discussed in this dissertation. The main work is described as follows:The approach to determining the optimal cell number of manufacturing cell formation is presented. The difference of weighting exponent, cluster center and metrics how to have an impact upon the clustering results and membership function are studied in the beginning. Afterwards, a method to determine the optimal m value is given. Two-order partial derivative of the objective function for FCM is calculated, and the variational weighting exponent m is obtained that can prevent the parameter from being the unique value and play an important role in the process of fuzzy clustering. Moreover, in order to avoid a single validity index can not assess correctly, partition coefficient (PC), classification entropy (CE), Fukuyama and Sugeno (FS) and Xie and Beni (XB) are considered as multi-performance indexes to evaluate the cluster validity, and then an optimal number c is chosen based on these validity measures.A multi-objective optimization method based on preference of cell formation is proposed. Firstly, the representation models of cell formation problem in existence are investigated; further, the relation between the utilization of manufacturing resource and benefit is discussed. In this study, the established mathematic optimized model considers the total similarity, total processing cost, total processing time and total investment. Secondly, due to the combinatorial nature of cell formation problem and the characteristics of multi-objective and multi-constrain, a novel method of evolutionary algorithm with preference is proposed. The analytic hierarchy process (AHP) is adopted to determine scientifically the weights of the sub-objective functions. The satisfaction of constraints is considered as a new objective, the ratio of the population which doesn't satisfy all constraints is assigned as the weight of new objective. In addition, the self-adaptation of weights is applied in order to converge more easily towards the feasible domain. Therefore, both features multi-criteria and constrains are dealt with simultaneously. Finally, an example is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method in designing the manufacturing cells.A decision support system based on scenario for multi-attribute selection of cell formation schemes is developed. The system combines fuzzy set theory and group decision with the AHP to decrease the influence of decision makers' subjective preferences and control the uncertain and imprecise variations during evaluation process. The importance weights of different criteria and the ratings of various alternatives under different criteria are evaluated in linguistic terms represented by fuzzy numbers. The intangible criteria and criteria weights are determined by group decision which can integrate all decision makers' subjective opinions based on different scenarios. Besides, fuzzy value of each of the alternatives is computed by making use of standard fuzzy arithmetic. The degree of confidence and risk index are also joined, so that decision makers can adjust them to match real context. Finally, a case of individual selection about cell formation is given, and the simulation results demonstrate the proposed approach is both effective and robust. The system helps user select preferred individual from candidates.On the basis of theoretic research above, the prototype system of manufacturing cell formation is developed. The successful implementation in enterprise testifies the feasibility of several theories and methods presented in this dissertation.