Multi-Response Optimization and Predictive Modeling of Drilling Performance in PEEK-CF30 Composites Considering Drill Coating and Cutting Parameters

Abstract

Carbon fiber-reinforced thermoplastic composite drilling is a secondary manufacturing process because the quality of drilled holes affects assembly system performance, structure, and sustainability. This paper compares all drill coating types and cutting conditions for PEEK-CF30 composite drilling utilizing a hybrid experimental-statistical method. DLC-, TiN-, and TiCN-coated HSS drills, as well as cutting speed and feed rate were tested using the Taguchi L27 design. Performance indicators were measured by including thrust force, surface roughness, drilling torque, and energy consumption. Experimental results showed that increasing cutting speed and feed rate increased the thrust force while decreasing torque and energy consumption. Smearing on the hole surface, chip adhesion, and short fiber adhesion/pull were identified as indicators of poor surface quality, and these occurrences increased with increasing drill coating removal at high cutting parameters. In terms of overall performance, the TiCN-coated drill created the lowest thrust force (50.85 N), surface roughness (1.038 & micro;m), torque (17.54 Ncm), and energy consumption (136.45 J) at high feed conditions. Taguchi-based gray relational analysis methodology revealed that the TiCN-coated drill, a cutting speed of 40 m/min, and a feed rate of 0.1 mm/rev are the optimum parameters. Second-order prediction models developed for all responses proved to have high predictive capabilities with coefficients of determination above 94%. Ultimately, drill coating quality considerably affected surface integrity and drilling energy consumption performance in drilling PEEK-CF30. A hybrid optimization and modeling framework demonstrates that the drill quality cutting parameter will allow for optimum selection to ensure efficient processing of advanced thermoplastic composites.