Abstract

In modern industry, machinery must become increasingly flexible and automatic. In order to increase productivity, enhance quality and reduce cost, machine tools have to work free of any failure. When a failure occurs in a machine tool, it is necessary to identify the causes as early as possible. Machine tool condition monitoring is very important to achieve this goal. Condition monitoring is generally used on the critical subsystem of any machine tool. This paper endeavors to focus on the condition monitoring aspects on the machine tool element. In the present study, a critical subsystem has been identified based on the failure data analysis. Condition monitoring techniques like vibration monitoring, acoustic emission, Shock Pulse Method (SPM) and surface roughness have been successfully used for fault identification.

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