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Simultaneous Tolerance Synthesis for Manufacturing and Quality using Evolutionary Algorithms

Simultaneous Tolerance Synthesis for Manufacturing and Quality using Evolutionary Algorithms

Y. S. Rao (Sri Veeravenkata Satyanarayana (SVVSN) Engineering College, India), C. S. P. Rao (National Institute of Technology, India), G. Ranga Janardhana (Jawaharlal Nehru Technological University, India), and Pandu R. Vundavilli (DVR & Dr. HS MIC College of Technology, India)
Copyright: © 2011 |Volume: 2 |Issue: 2 |Pages: 20
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781613505540|DOI: 10.4018/jaec.2011040101
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MLA

Rao, Y. S., et al. "Simultaneous Tolerance Synthesis for Manufacturing and Quality using Evolutionary Algorithms." IJAEC vol.2, no.2 2011: pp.1-20. https://doi.org/10.4018/jaec.2011040101

APA

Rao, Y. S., Rao, C. S., Janardhana, G. R., & Vundavilli, P. R. (2011). Simultaneous Tolerance Synthesis for Manufacturing and Quality using Evolutionary Algorithms. International Journal of Applied Evolutionary Computation (IJAEC), 2(2), 1-20. https://doi.org/10.4018/jaec.2011040101

Chicago

Rao, Y. S., et al. "Simultaneous Tolerance Synthesis for Manufacturing and Quality using Evolutionary Algorithms," International Journal of Applied Evolutionary Computation (IJAEC) 2, no.2: 1-20. https://doi.org/10.4018/jaec.2011040101

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Abstract

Tolerance plays a major role in the manufacturing industry, as it affects product design, manufacturing, and quality of the product. This paper considers product design, manufacturing, and quality simultaneously, and introduces a concurrent approach for tolerance allocation using evolutionary algorithms. A non-linear model that minimizes the combination of manufacturing cost and quality loss simultaneously, in a single objective function has been considered. In the proposed work, evolutionary algorithms (that is, Genetic Algorithms (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO)) have been used to determine the optimal tolerances at the minimum manufacturing and quality loss cost. The application of the proposed methodology has been demonstrated on a simple mechanical assembly.

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