A Review on Tool Life in Coal Measures Rocks

Abstract

Tungsten carbide inserts in rock drill bits are predominantly used in drilling rocks, particularly in mining industries. The research studies performed on drill bits have been limited to several factors such as collecting failure data of bit components from the field, conducting wear tests considering rock properties, and introducing new coated insert materials. The role of Artificial Intelligence (AI) and Machine Learning (ML) for the betterment of tool wear with real-time data is limited. The present study has offered an evaluative perspective of an essential industrial issue. In this review, a concept map presents a visual organization and representation of knowledge obtained during the study. Utilizing the propositions from the concept map, a brief review of the integrated concepts of researchers relating drill bits, failure data, numerical and statistical models, wear analysis, reliability assessment, and prerequisites in developing new materials have been discussed in the backdrop of the present study.