Tolerance modelling in selective assembly for minimizing linear assembly tolerance variation and assembly cost by using Taguchi and AIS algorithm

The quality of any product depends upon its component tolerance and assembly variations. Most products are composed of more than one component. These products require some type of assembly during production. Assembly is the process of joining two or more parts together. The functional performance of an assembled product and its manufacturing cost are directly affected by the individual component tolerances. However, tolerance is inevitable because manufacturing exactly equal parts is impossible. When the components are assembled together interchangeably, the assembly tolerance is the sum of the component tolerances. If the required assembly tolerance variation is less than the sum of the components' tolerances, the rejection rate of assemblies will be more. In such cases, the selective assembly is the method to achieve tight assembly tolerance with the components manufactured at wider tolerances. This is accomplished by partitioning produced components into groups prior to random assembly. The mating components in the selective groups are then assembled at random. In this paper, artificial immune system (AIS) algorithm is developed to obtain the best combination of selective group with minimum variation in the assembly tolerance and least loss value within the specification range. The concept of Taguchi's loss function is applied into the selective assembly method to evaluate the deviation from the mean. The selection of number of groups for selective assembly is also analyzed in this paper.