Title: Investigation of chatter stability in boring tool and tool wear prediction using neural network

Authors: K. Ramesh; T. Alwarsamy; S. Jayabal

Addresses: Government College of Technology, Coimbatore-641 013, Tamilnadu, India ' Directorate of Technical Education, Chennai-600 025, Tamilnadu, India ' Government College of Engineering, Bargur-635 104, Tamilnadu, India

Abstract: Chatter vibrations were induced during boring process due to cantilever shape of boring bars. These vibrations further leads to an increase in temperature of the boring tool which increases the tool wear. This present investigation is focused on selection of suitable damping material for the boring tool in various positions in order to reduce tool wear. Various damping materials such as copper, cast iron, brass, phosphor bronze, gun metal, steel and aluminium are considered for analysis. A conventional lathe which is attached with a temperature measurement setup was used to conduct experiments for various levels of speed, depth of cut, damping materials and its position from the cutting edge to measure tool wear and temperature. Tool wear and temperature were accurately predicted using artificial neural network model and it was compared with the experimental values.

Keywords: chatter stability; boring tools; tool wear prediction; artificial neural networks; ANNs; impact dampers; cutting force; chatter vibration; tool vibration; tool chatter; temperature; damping materials.

DOI: 10.1504/IJMPT.2013.052789

International Journal of Materials and Product Technology, 2013 Vol.46 No.1, pp.47 - 70

Received: 02 Jul 2011
Accepted: 23 Feb 2012
Published online: 21 Jun 2014 *

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