OPTIMIZATION OF PRESS-FIT PROCESSES

Abstract

The press-fit process is an efficient, low-cost method for joining parts. The parts that must be joined interfere with each other’s occupation of space; therefore, contact dimensions and their tolerances influence the quality of the assembly. The traditional method for the selection of contact dimensions and their tolerances is based on engineering experience. The idea of the research work presented in this paper is to optimize the press-fit process at an early stage of development process, involving prediction and optimization of the joining force and consequently the prediction and minimization of the rejection rate. Accordingly, several finite-element (FE) simulations of the press-fit process for predicting the joining forces were conducted, considering input-parameter variations (material properties: yield stress, hardening exponent; geometry: shaft diameter, guide diameter of the core, functional diameter of the core; friction coefficient). Based on FE simulations and 47 different input-parameter-variation results, the empirical model for predicting the joining force using the response-surface methodology (RSM) was obtained. By using RSM and a stochastic Monte Carlo simulation, the rejection rate was also determined. The predicted and the actual rejection rates for selected process parameters were 1.4 % and 1.5 %, respectively. Consequently, the press-fit process can also be optimized to reduce the rejection rate using the same Monte Carlo simulation. The results of the analysis show that the rejection rate can be reduced from 1.4 % to 0.2 %.