Genetic algorithms in statistical tolerancing

Authors:
A. Shan;R. N. Roth;R. J. Wilson
Affiliations:
Department of Mechanical Engineering The University of Queensland Qld, 4072, Australia;Department of Mechanical Engineering The University of Queensland Qld, 4072, Australia;Department of Mathematics The University of Queensland Qld, 4072, Australia
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2003

Citing 1
Cited 1

Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning

Improved algorithm for tolerance allocation based on Monte Carlo simulation and discrete optimization

Computers and Industrial Engineering

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Abstract

An important aspect in manufacturing design is the distribution of geometrical tolerances so that an assembly functions with given probability, while minimising the manufacturing cost. This requires a complex search over a multidimensional domain, much of which leads to infeasible solutions and which can have many local minima. As well, Monte-Carlo methods are often required to determine the probability that the assembly functions as designed. This paper describes a genetic algorithm for carrying out this search and successfully applies it to two specific mechanical designs, enabling comparisons of a new statistical tolerancing design method with existing methods.