Predicting cutting tool life: models, modelling, and monitoring

This review presents a comprehensive examination of recent advancements in the modelling and monitoring of cutting tool life, emphasizing its critical role in enhancing manufacturing efficiency and cost-effectiveness. The paper discusses the primary wear mechanisms, such as abrasive, adhesive, diffusive, and chemical wear. Traditional and modern predictive models, including Taylor's, Colding's, and Usui's tool life models, are evaluated. The review also covers a range of modelling approaches from empirical to numerical and analytical methods, alongside cutting tool monitoring techniques. The paper concludes by identifying future research directions, hybrid models that combine empirical and analytical techniques, and the creation of comprehensive datasets. The goal is to provide practitioners and researchers with insights into the next wave of innovations in tool life optimization, fostering advancements in adaptive self-learning tool performance predictive systems and integrated monitoring technologies.