A summary of methods applied to tool condition monitoring in drilling

Abstract

This paper presents a summary of the monitoring methods, signal analysis and diagnostic techniques for tool wear and failure monitoring in drilling that have been tested and reported in the literature. The paper covers only indirect monitoring methods such as force, vibration and current measurements, i.e. direct monitoring methods based on dimensional measurement etc. are not included. Signal analysis techniques cover all the methods that have been used with indirect measurements including e.g. statistical parameters and Fast Fourier and Wavelet Transform. Only a limited number of automatic diagnostic tools have been developed for diagnosis of the condition of the tool in drilling. All of these rather diverse approaches that have been available are covered in this study. In the reported material there are both success stories and also those that have not been so successful. Only in a few of the papers have attempts been made to compare the chosen approach with other methods. Many of the papers only present one approach and unfortunately quite often the test material of the study is limited especially in what comes to the cutting process parameter variation, i.e. variation of cutting speed, feed rate, drill diameter and material and also workpiece material. 

Energy efficiency improvements in dry drilling with optimised diamond-like carbon coatings

“…No lubricant was used and analysis of the results focussed on the drilling torque, power consumption of the spindle drive motor and the number of holes drilled before failure. Online monitoring of tool degradation is attractive economically and technically, and this experiment monitored the analogue current, which proportionally correlates to the drilling torque [11,12]. Since the cutting parameters (i.e., spindle speed, feed rate, drill geometry) are similar during each run of experiment, the variation in current signals can be attributed solely to the drill condition.…”

Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals

“…Root mean square (RMS) is the most common parameter used in statistical analysis [16]. Its value contains all the energy in the signal and therefore also all the noise and all elements that depend on the cutting process.…”

In-situ tool wear monitoring and its effects on the performance of porcine cortical bone drilling: a comparative in-vitro investigation

“…In the last three decades, various studies have been reported on the monitoring of drill wear which is focused on industrial applications (Jantunen 2002). However, drilling method in surgical operation theater is different as compared to industrial application.…”