Abstract

The article presents a methodology for multi-objective compromise optimization of the process of turning on CNC machines with robotic loading by the methods of determining the optimum compromise area and carrying out optimization, using the generalized arithmetic mean utility function with weight coefficients. The methodology has been applied to determine the optimal cutting conditions, ensuring the best combination of technological parameters for the CNC turning process when machining parts made of 42CrMoS4 steel with cutting tools from different manufacturers. A complex study and modeling of the main technological parameters (production rate, cutting tool lifetime, and roughness of machined surfaces) in the CNC turning process have been performed depending on the conditions of cutting. By applying a genetic algorithm, the optimal conditions for implementing the process using both optimization methods have been determined, and a comparative analysis of the technological parameters has been made. Models have been created for predicting the number of machined parts, which exclude unplanned stops for tool changes, under the specified optimal conditions of cutting, taking into account the capacity of the tool magazine, the loading mechanism, and the volume of the production batch.

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