Material selection for milling cutter inserts in High-Speed machining applications using the CARCACS Method

• Milling cutter insert material prioritized using the CARCACS method for effective decision-making. • Decision matrix developed with suitable material alternatives and application-specific criteria. • Silicon carbide ranks highest among the seven materials evaluated based on defined criteria. • Results validated through comparison with other MCDM methods and Spearman’s rank correlation. • Sensitivity analysis confirms the robustness and stability of the top-ranked material alternative. Strategic material selection in engineering applications is essential, averting part failure, enhancing performance, and optimizing costs amid conflicting factors like improved functionality, reduced weight, and cost efficiency. Selecting appropriate milling cutter insert material is crucial for high-speed and hard machining, ensuring durability, wear resistance, sharpness, and stability while balancing cost-effectiveness, performance, tool life, accuracy, and productivity under extreme conditions. A systematic approach is crucial to address material selection challenges, identifying criteria and eliminating unsuitable alternatives to select the most suitable. The paper strategically focuses on formulating a comprehensive case study for selecting the most suitable milling cutter insert material by constructing a decision matrix with viable material alternatives and multiple evaluation criteria for prioritizing them. The multi-criteria decision-making (MCDM) problem is solved using the CARCACS method. The effectiveness of the employed decision-making methodology in addressing the presented case study is confirmed by benchmarking its results against those obtained from alternative MCDM methods. Additionally, sensitivity analysis and rank correlation coefficient tests are conducted to ensure the robustness and stability of the ranking outcomes. Silicon carbide is consistently identified as the optimal material for a milling cutter insert, achieving unanimous top-ranking status across various MCDM methods and sensitivity analysis scenarios.