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Tolerance Synthesis and Cost Optimisation in Assembly: A Neural Network Approach

Karthick Jayaram*, K. Sankaranarayanasamy**, Subramaniam Arunachalam***, Tom Page****

*Research Scholar, Department of Mechanical Engineering, National Institute of Technology, Tlruchirappalli, India.

** Professor, Department of Mechanical Engineering, NIT, Trichy.

*** Senior Lecturer, Manufacturing Systems Engineering, University of East London, UK.

**** Lecturer In Electronic Product Design, Department of Design and Technology, Loughborough University, UK.

Periodicity:May - July'2008
DOI : https://doi.org/10.26634/jfet.3.4.608

Abstract

Tolerance synthesis directly influences the functionality of products and their related production costs. The problem of synthesis is to discretise tolerances without affecting functionality of a product. A promising method of tolerance synthesis is to assign component tolerances that minimize the cost of production of an assembly. In this paper the neural network is applied to fit the cost-tolerance relationship. The neural network has been reported to be an effective tool for determining the relationship between input factor and output responses. The available case studies in the literature for the tolerance synthesis are used to investigate the efficiency and effectiveness of the proposed methodology.

Keywords

Multi-layer Perceptron, Artificial Neural Networks, Tolerance Synthesis, Cost-tolerance Relationship, Regression Analysis.

How to Cite this Article?

Karthick Jayaram, K. Sankaranarayanasamy, S. Arunachalam and Tom Page (2008). Tolerance Synthesis and Cost Optimisation in Assembly: A Neural Network Approach. i-manager’s Journal on Future Engineering and Technology, 3(4), 62-69. https://doi.org/10.26634/jfet.3.4.608

References

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