(A) hierarchical divisive clustering method for machine-component grouping problems

Abstract

This thesis proposes a hierarchical devisive algorithm for the machine-component grouping problem whose objective is to identify the part families requiring similiar manufacturing operations and from the associated groups of machines. First part of this thesis is devoted to developing a hierarchical divisive algorithm based on graph theory to find the natural part families. The objective is to form components into part families such that the degree of interrelations is high among components within the same part family and low between components of different part families. From the machine-component matrix, the components similarity graph is derived. By separating a graph into two subgraphs iteratively, the part families are found. Since finding a set of optimal part families through total enumeration is prohibitive in terms of time and effort even for problems with a moderate number of components, a heuristic algoritm is proposed. A charatericstic of the proposed algorithm is that the number of the part families and constituent parts of each family are determined naturally. It needs neither human judgment nor any specification of the number of the part families in advance. The algorithm is illustrated with numerical examples. Second part of this thesis focuses on establishing cell design procedures. The aim is to create cells in which the most expensive and important machines-called key machine-have a reasonably high utilization and the machines should be allocated to minimizel the intercell mevement of machine loads. To fulfil the above objectives, 0-1 integer programming model is developed and the solution procedures are found. To illustrate the machine allocation procedures, a hypothetical example is considered. Finally an attempt is made to show the validity of the proposed algorithm. Several problems appearing in the literature are solved by the proposed method. The results are compared with those of the other approaches.