Multi-objective optimization of thermoplastic CF/PEKK drilling through a hybrid method: An approach towards sustainable manufacturing

Carbon-fibre-reinforced-polyetherketonketone (CF/PEKK) has attracted increasing interest in the aviation industry due to its self-healing properties and ease of recycle repair. However, machining performance CF/PEKK is not well understood there a lack optimization study for minimizing hole damage improving production efficiency. Here, we report first multi-objective drilling. A hybrid algorithm integrating Non-dominated Sorting Genetic Algorithm-II (NSGA-II) Techniques Order Preference by Similarity Ideal Solution (TOPSIS) deployed obtain Pareto solutions rank multiple based on closeness ideal solutions. To highlight impact different matrix outcome, comparative with conventional thermoset carbon fibre reinforced epoxy composite (CF/epoxy) carried out time. Experimental validation shows proposed method can achieve 91.5–95.7% prediction accuracy effectively controlled delamination thermal within permissible tolerance. The vastly optimal drilling parameters identified as compared CF/epoxy attributed thermoplastic nature unique thermal/mechanical interaction characteristics displayed during process.