Journal of Advanced Mechanical Design, Systems, and Manufacturing
Online ISSN : 1881-3054
ISSN-L : 1881-3054
Papers
Development of tool life prediction system for square end-mills based on database of servo motor current value
Hiroyuki KODAMAMakoto SUZUKIKazuhito OHASHI
Author information
JOURNAL OPEN ACCESS

2025 Volume 19 Issue 1 Pages JAMDSM0001

Details
Abstract

Accurate prediction of tool life is crucial for reducing production costs and enhancing quality in the machining process. However, such predictions often rely on empirical knowledge, which may limit inexperienced engineers to reliably obtain accurate predictions. This study explores a method to predict the tool life of a cutting machine using servo motor current data collected during the initial stages of tool wear, which is a cost-effective approach. The LightGBM model was identified as suitable for predicting tool life from current data, given the challenges associated with predicting from the average variation of current values. By identifying and utilizing the top 50 features from the current data for prediction, the accuracy of tool life prediction in the early wear stage improved. As this prediction method was developed based on current data obtained during the very early wear stage in experiments with square end-mills, it was tested on extrapolated data using different end-mill diameters. The findings revealed average accuracy rates of 71.2% and 69.4% when using maximum machining time and maximum removal volume as thresholds, respectively.

Content from these authors
© 2025 by The Japan Society of Mechanical Engineers

This article is licensed under a Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International] license.
https://creativecommons.org/licenses/by-nc-nd/4.0/
Next article
feedback
Top