Optimal geometric tolerance design framework for rigid parts with assembly function requirements using evolutionary algorithms

• Published in: International journal of advanced manufacturing technology Vol. 73; no. 9-12; pp. 1219 - 1236
• Main Authors: Saravanan, A., Balamurugan, C., Sivakumar, K., Ramabalan, S.
• Format: Journal Article
• Language: English
• Published: London Springer London 01-08-2014; Springer Nature B.V
• Subjects: Assembly; CAE) and Design; Classification; Combinatorial analysis; Computer-Aided Engineering (CAD; Concurrent engineering; Design; Design engineering; Engineering; Engineers; Evolutionary algorithms; Evolutionary computation; Genetic algorithms; Industrial and Production Engineering; Mechanical Engineering; Media Management; Optimization; Original Article; Redesign; Sorting algorithms; Tolerances; Sensitive factor and tolerance optimization; Geometrical dimensioning and tolerancing; Assembly function requirement; Elitist Non-dominated Sorting Genetic Algorithm; Differential evolution algorithm; Composite position tolerance
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-014-5908-2

Tolerance design is always a challenging task for engineers, since it need to satisfy multidisciplinary functions. Engineering design is done in two stages: assembly design and detail design. In the first stage, an assembly is designed considering certain system level functions and in secondary detail design stage; decomposition of the assembly is done and process tolerancing is employed for the parts. At the secondary detail design stage, designer adopts geometrical dimensioning and tolerancing (GD&T) concepts for process tolerancing. Hence, assembly and detail design are done in different phases with dissimilar perspectives. As a result, geometric tolerance design often lands in conflict, redesign, and in the case of concurrent engineering, costly reiterations are performed. This conflict occurs because of two vital reasons: (1) a gap exists between these two design stages and no common relation between them; (2) GD&T is adopted in the secondary stage, which is not available in primary stage. This paper offers a framework for a design engineer to bridge the gap and to establish the relation between these stages. A nonlinear combinatorial optimization problem is framed based on assembly function requirement (AFR), and tolerance values are optimized with appropriate constraints. Nontraditional Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and differential evolution (DE) algorithms are used to solve the problem. For the allocated position tolerances, appropriate sensitive factors are indicated to facilitate design improvement. Finally, a case study is used to illustrate the complete framework.