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

K.Jayaram*, K. Sankaranarayanasamy**, S. Arunachalam***, Tom Page****
*,** Department of Mechanical Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu, India. Description
*** School of Computing and Technology, University of East London, UK.
**** Lecturer, Department of Design and Technology, Loughborough University, Loughborough, UK.


Tolerance synthesis directly influences the functionality of products and their related production costs. The problem of synthesis is to discretise tolerances without affecting overall product functionality. A promising method of tolerance synthesis is to assign component tolerances that minimize the cost of production of an assembly. In this paper, a 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 accompanying case studies are used to investigate the efficiency and effectiveness of the proposed methodology.


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

How to Cite this Article?

Jayaram, K., Sankaranarayanasamy, J. K., Arunachalam, S., and Page, T.(2010). A Neural Network Approach To Tolerance Synthesis And Cost Optimisation In Assembly. i-manager’s Journal on Future Engineering and Technology, 5(2), 9-16.


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