A systematic review of artificial intelligence in the detection of cutting tool breakage in machining operations

Abstract

Automatic detection of the cutting tool breakage plays a vital role in the automation of machining operations. However, up to now, few artificial intelligence (AI) models in the detection of cutting tool breakage have been practically applied in manufacturing. There are technological gaps between the research and practice. This systematic review comprehensively analyzed all the relevant studies to promote the practical application of AI models in the automatic detection of cutting tool breakage. Twenty-one studies were included in the qualitative analysis, and nine studies were included in the quantitative analysis. The most used AI model was the support vector machine, and the most used input signal was cutting force. The results showed that AI had good accuracy in the detection of cutting tool breakage. In future studies, the application of AI needs to be further confirmed by more cutting experiments conducted in real-time on various cutting conditions.