A semi-analytical model for predicting tool wear progression in drilling CFRP

In drilling carbon fiber reinforced polymer (CFRP), tool wear could significantly aggravate the drilling defects, and accurately predicting the tool wear progression is crucial for instructing tool change and preventing drilling defects in automatic production. The tool wear progression is usually modelled based on pure empirical methods, where the fundamental cutting interactions are neglected, and this is limited for applications. This paper established a semi-analytical model for tool wear progression prediction by combining the fundamental interaction analyses between tool and workpiece as the analytical part and regression analysis of three fitting parameters as the empirical part in drilling CFRP with a cemented carbide drill bit. The tool wear is featured and evaluated by the wear rate and the average half axis lengths based on tool wear characteristics. According to the cutting interactions between the drill bit and the CFRP workpiece, the wear rate is predicted based on the abrasive wear model and a previously proposed cutting force model. Combining the wear rate and wear geometry, the average half axis lengths are also predicted. The prediction errors of the wear rate and the average half axis lengths are less than 25% and 15%, respectively, with one test group for calibrating three coefficients. In addition, the effects of tool geometrical parameters on the tool wear progression are revealed for drilling CFRP.

Automated summary

In this paper, a semi-analytical model is established to predict tool wear progression in CFRP drilling, combining fundamental cutting interactions analysis and regression analysis, and describing and evaluating tool wear based on wear rate and average half axis lengths.