Research On The Number Of Manufacturing Cells Based On Product Demand State

Cell manufacturing is an important application of group technology,and cell production is one of the effective production methods today.In order to better adapt to the variability of the market environment and the flexibility of the production cycle,the cell manufacturing system with low investment and low reconstruction cost has become one of the best choices for small and medium-sized manufacturing enterprises in China.Cell formation is the first step in implementing cell manufacturing,and it is related to whether cell manufacturing can be successfully implemented.The determination of the optimal number of manufacturing cells is the key to the problem of cell formation.At present,the research on the optimal number of manufacturing cells is mainly based on the determination of product demand,and rarely considers the fluctuation of product demand.Moreover,the determination of the best number of existing manufacturing cells is mostly based on experience.In view of the deficiencies of the existing research,this article comprehensively considers the two situations of product demand determination and fluctuating demand to determine the optimal number of manufacturing cells.In the case of product demand determination,an improved fuzzy C-means algorithm is proposed from the perspective of load balancing,and the optimal number of manufacturing cells is determined based on this.First of all,in order to be able to evaluate the load balancing situation in the cell formation,considering the product demand,the part-equipment matrix is redesigned,and on the basis of this,both the intra-cell and inter-cell load balancing are considered simultaneously,and a new evaluation is proposed indicator V_L.Secondly,to improve the subtraction clustering method to determine a reasonable initial clustering center,and to improve the parameter r_a in the subtraction clustering method,this paper proposes a convenient and effective calculation method that meets the cell formation characteristics.Afterwards,by improving the membership degree,the algorithm convergence speed is accelerated.Finally,the improved fuzzy C-means algorithm is designed and programmed,combined with testing and comparison with literature data to verify the effectiveness and superiority of this method.In the case of fluctuations in product demand,the common situation of choosing fluctuations to follow a normal distribution is selected,and the optimal number of manufacturing cells is determined by constructing a layered cell manufacturing system.First,the Jaccard similarity coefficient is improved to construct a similarity matrix between parts,and the ALC clustering algorithm based on the similarity coefficient method is used to divide the part family,and then the relevant knowledge of probability is used to identify the configuration of the manufacturing cells,and then through construct a mathematical model to minimize the number of open manufacturing cells,determine the type of manufacturing cells required for each part family,and finally determine the optimal number of manufacturing cells by selecting the total number of equipment as evaluation indicators.The research in this paper solves the problem of determining the optimal number of manufacturing cells in cell formation,and provides a theoretical basis for the application of cell manufacturing in actual production.