Title: Intelligent estimation of burning limits to aid in cylindrical grinding cycle planning

Authors: R. Deiva Nathan, L. Vijayaraghavan, R. Krishnamurthy

Addresses: Department of Mechanical Engineering, Indian Institute of Technology, Madras, India. Department of Mechanical Engineering, Indian Institute of Technology, Madras, India. Department of Mechanical Engineering, Indian Institute of Technology, Madras, India

Abstract: The drive towards productivity improvement in the competitive manufacturing environment has led to the increased use of artificial intelligence technologies to optimise and control the machining process. This ensures the production of high quality components at shorter cycle times. This paper presents a scheme for optimising the cycle time of a two-stage grinding cycle while grinding a series of pieces without intermediate wheel dressing. The scheme presented uses a feedforward artificial neural network to estimate the burning limit under continuous grinding conditions, which is used as the wheel life criterion.

Keywords: burning limit estimation; grinding cycle optimisation; neural networks; steel grinding.

DOI: 10.1504/IJHVS.2001.001154

International Journal of Heavy Vehicle Systems, 2001 Vol.8 No.1, pp.48-59

Published online: 01 Jul 2003 *

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