Least Cost Tolerance Allocation for Mechanical Assemblies with Automated Process Selection

TLDR

Tolerance allocation among mechanical assembly components can greatly influence manufacturing costs, and when multiple manufacturing processes are available, the problem becomes a discrete optimization challenge. The authors evaluated systematic search strategies—including discrete and continuous optimization schemes—against exhaustive search, measuring CPU time and combination counts to identify the minimum‑cost process set for an assembly.

Abstract

The allocation of tolerances among the components of a mechanical assembly can significantly affect the resulting manufacturing costs. If cost versus tolerance data are available for each dimension, the least cost tolerance allocation may be determined by optimization techniques. However, when alternate manufacturing processes are available for some of the components, a discrete optimization problem results. An exhaustive search of all possible combinations of processes will determine the global optimum, but the number of combinations increases geometrically, becoming very large for assemblies of only moderate complexity. Several methods were tested for systematically searching for the minimum cost process set for an assembly. Both discrete and continuous optimization schemes were compared to an exhaustive search, based on CPU times and the number of combinations required to find the global optimum.