Tolerance analysis and synthesis using the mean shift model

Tolerance design plays an important role in the modern design process by introducing quality improvements and limiting manufacturing costs. In this paper a method for statistical tolerance analysis and synthesis is presented. This method is implemented using the mean shift model of Chase and Greenwood, providing a systematic approach to evaluate the mean shift factor. This method considers all the principal factors that affect the statistical sum of a certain number of assembly dimensions. In particular, the considered factors include the mean shift ratio, the confidence level, the number of dimension of the assembly and the tolerance assortment between the component dimensions. An implementation of the mean shift model for tolerances synthesis is described. The tolerances synthesis is performed in an unusual way, taking into account in the optimization process the typical parameters that affect the product variability. For this purpose the method uses four types of condition for the dimensional tolerances: fixed tolerance value, fixed mean shift ratio, fixed mean shift and fixed natural variability. Furthermore, in the optimization process, the service variability is considered under two conditions: fixed and valuable service variability. A case study is presented and the results of some simulations are discussed.