ANALYZING THE VIBRATION EFFECT OF CUTTING TOOL ON SURFACE ROUGHNESS OF TURNING WORK PIECE IN LATHE MACHINE

Authors

  • Sawant Akshay Shasheekant Mechanical Engineering Department Dr. Vitthalrao Vikhe Patil College of Engineering, Ahmednagar, India
  • Prof. Narwade P.A. Mechanical Engineering Department Dr. Vitthalrao Vikhe Patil College of Engineering, Ahmednagar, India

DOI:

https://doi.org/10.17605/OSF.IO/6QYGM

Keywords:

Cutting tool, Modal analysis, FFT

Abstract

Tool condition observation systems area unit essential in small milling applications. A tool's slenderness needs high-precision observation systems for on-line measurements. In most cases, tool health is indirectly calculable by process and analyzing the cutting method parameters cutlery wear may be a essential development that influences the standard of the machined half. Vibration signals from metal cutting processes are investigated for varied functions, together with in-process tool wear monitoring. Reducing the machining energy consumption (MEC) of machine tools for turning operations is important to market manufacturing producing. during this study, the link between vibration and gear wear is investigated throughout high-speed dry turning by victimization applied math parameters. it's aimed to show however tool wear and therefore the work piece surface roughness changes with tool vibration signals. For this purpose, a series of experiments were conducted in a lathe machine. Modal analysis of each traditional and wear cutlery are going to be perform for locating Natural frequency of cutting tools in ANSYS 19 code. Experimental testing of cutlery are going to be perform using FFT instrument. afterward the comparative analysis are going to be dispensed between the experimental and analysis results and afterward the result & conclusion are going to be drawn.

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Published

2022-02-28

How to Cite

Sawant Akshay Shasheekant, & Prof. Narwade P.A. (2022). ANALYZING THE VIBRATION EFFECT OF CUTTING TOOL ON SURFACE ROUGHNESS OF TURNING WORK PIECE IN LATHE MACHINE. Open Access Repository, 9(02), 79–89. https://doi.org/10.17605/OSF.IO/6QYGM

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Articles