Publication Type : Journal Article
Publisher : Journal of Materials Research and Technology
Source : Journal of Materials Research and Technology, Volume 9, Number 1, p.1032 - 1042 (2020)
Url : http://www.sciencedirect.com/science/article/pii/S2238785418313061
Keywords : Feature extraction, Machine Learning Algorithm, Milling process, Sensor fusion, Tool condition monitoring system
Campus : Coimbatore
School : School of Engineering
Department : Mechanical Engineering
Year : 2020
Abstract : The most important improvement in metal the cutting industry is the continuous utilization of cutting tools and tool condition monitoring system. In the metal cutting process, the tool condition has to be administered either by operators or by online condition monitoring systems to prevent damage to both machine tools and workpiece. Online tool condition monitoring system is highly essential in modern manufacturing industries for the rising requirements of cost reduction and quality improvement. This paper summaries various monitoring methods for tool condition monitoring in the milling process that have been practiced and described in the literature.
Cite this Research Publication : T. Mohanraj, Shankar, S., Rajasekar, R., Dr. Sakthivel N.R., and Pramanik, A., “Tool condition monitoring techniques in milling process — a review”, Journal of Materials Research and Technology, vol. 9, pp. 1032 - 1042, 2020.