Associated tolerance optimization approach using manufacturing difficulty coefficients and genetic algorithm
ISSN: 0144-5154
Article publication date: 19 October 2022
Issue publication date: 6 December 2022
Abstract
Purpose
The purpose of this paper is to establish a tolerance optimization method based on manufacturing difficulty computation using the genetic algorithm (GA) method. This proposal is among the authors’ perspectives of accomplished previous research work to cooperative optimal tolerance allocation approach for concurrent engineering area.
Design/methodology/approach
This study introduces the proposed GA modeling. The objective function of the proposed GA is to minimize total cost constrained by the equation of functional requirements tolerances considering difficulty coefficients. The manufacturing difficulty computation is based on tools for the study and analysis of reliability of the design or the process, as the failure mode, effects and criticality analysis (FMECA) and Ishikawa diagram.
Findings
The proposed approach, based on difficulty coefficient computation and GA optimization method [genetic algorithm optimization using difficulty coefficient computation (GADCC)], has been applied to mechanical assembly taken from the literature and compared to previous methods regarding tolerance values and computed total cost. The total cost is the summation of manufacturing cost and quality loss. The proposed approach is economic and efficient that leads to facilitate the manufacturing of difficult dimensions by increasing their tolerances and reducing the rate of defect parts of the assembly.
Originality/value
The originality of this new optimal tolerance allocation method is to make a marriage between GA and manufacturing difficulty. The computation of part dimensions difficulty is based on incorporating FMECA tool and Ishikawa diagram This comparative study highlights the benefits of the proposed GADCC optimization method. The results lead to obtain optimal tolerances that minimize the total cost and respect the functional, quality and manufacturing requirements.
Keywords
Acknowledgements
This work is supported by the doctoral school of the National School of Engineers of Monastir, University of Monastir, Tunisian Ministry of Higher Education and Scientific Research, within the framework of a post doc funding number (ED08ENIM01). The authors gratefully acknowledge their financial support.
Citation
Ghali, M., Elghali, S. and Aifaoui, N. (2022), "Associated tolerance optimization approach using manufacturing difficulty coefficients and genetic algorithm", Assembly Automation, Vol. 42 No. 6, pp. 782-795. https://doi.org/10.1108/AA-02-2022-0024
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited