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The development of biomedical devices has improved the quality of life for millions of people. The increase in life expectancy generates an increase in the demand for these devices. One of the most used materials for these purposes is 316 L austenitic stainless steel due to its mechanical properties and good biocompatibility. The objective of the present investigation was to identify the dependence between the main cutting force, the initial speed of the tool wear, the surface roughness, and the parameters of the cutting regime. Based on these dependencies, a multi-objective optimization model is proposed to minimize the energy consumed and initial wear rate, as well as to maximize productivity, maintaining the surface roughness values below those established by the ISO 5832-1 standard. The wear of the cutting tool was measured on a scanning electron microscope. For the optimization process, a genetic algorithm based on NSGA-II (Non-nominated Sorting Genetic Algorithm) was implemented. The input variables were the cutting speed and the feed in three levels. The cutting force and surface roughness were set as restrictions. It is concluded that the mathematical model allows for the optimization of the cutting regime during dry turning and with the use of MQL (Minimum Quantity Lubrication) with BIDEMICS JX1 ceramic tools (NTK Cutting Tools, Wixom, MI, USA), of AISI 316 L steel for biomedical purposes. Pareto sets and boundaries allow for choosing the most appropriate solution according to the specific conditions of the workshop where it is applied, minimizing the initial progression of tool wear and energy consumed, and maximizing productivity by guaranteeing the surface roughness values established for these types of parts according to the standard. |
