Comparison of two models for predicting tool wear and cutting force components during high speed trimming of CFRP

Because of the low thermal conductivity of Carbon Fibre Reinforced Polymers (CFRPs) during high speed-trimming, cutting forces and tool wear significantly increase the temperature at the contact zone, which is then completely transferred to the cutting tool and exceeds the permitted thermal stability limit of the cutting material. This then leads to a drastic reduction of the tool life, thermal damage, poor quality, and in some cases, rejection of machined parts. This paper presents the development of tool wear and cutting force prediction models in the trimming of CFRPs. A 3/8 in. diameter CVD diamond-coated carbide tool with six straight flutes was used to trim 24-ply carbon fibre laminates. The results obtained using a scanning electron microscope (SEM) showed increasing defect rates with increased tool wear. Two models were adjusted to predict tool wear and cutting force for different values of cutting speed, feed and cutting length. One of them is a multiplicative statistical model, and the other, an exponential model. Outcomes from the two models were analysed and compared. The ANOVA approach was also used to test the overall significance of the models by applying F-tests. The results obtained show that the exponential model is better capable of accurately predicting the cutting force and tool wear under the conditions studied. To enhance the prediction accuracy of the tool wear model, the cutting force was added as a variable in the tool wear model. Results show that the enhanced multiplicative model provided higher predictive capabilities than the exponential model.