Recommendation system and method for cutter and coating combination based on workpiece parameters

A recommendation system for matching cutter and coating combinations based on workpiece parameters, comprising:

• an experimental module, configured for, under different combinations of cutter parameters and coating parameters, conducting machining experiments on a workpiece to be machined with known workpiece parameters to determine machining performance data corresponding to each of the different combinations;
• wherein the machining performance data comprises:
• workpiece cutting performance data and cutter characteristic data;
• a prediction-model-establishment module, configured for establishing a performance-prediction model;
• wherein combinations of cutter parameters and coating parameters, and the known workpiece parameters of the workpiece to be machined are served as input features of the performance-prediction model, and the workpiece cutting performance data and the cutter characteristic data are served as output labels of the performance-prediction model, and the performance-prediction model is trained;
• a simulation module, configured for randomly combining the cutter parameters and the coating parameters, establishing individuals in an initial population, and inputting the individuals in the initial population and the known workpiece parameters of the workpiece to be machined into the trained performance-prediction model, to obtain the workpiece cutting performance data and the cutter characteristic data;
• a data-processing module, configured for processing the cutter characteristic data to obtain a life-evaluation coefficient for evaluating life of a cutter;
• and processing the workpiece cutting performance data to obtain a quality-evaluation coefficient for evaluating quality of a workpiece;
• and linearly processing the life-evaluation coefficient and the quality-evaluation coefficient to obtain a comprehensive evaluation coefficient;
• an iterative optimization module, configured for iteratively optimizing the individuals in the initial population through a genetic algorithm based on minimization of the comprehensive evaluation coefficient, to obtain optimal individuals;
• and configured for extracting an optimal value of the cutter parameters and an optimal value of the coating parameters based on the optimal individuals;
• and
• a recommendation module, configured for selecting an optimal combination of a cutter with an optimal value and a coating with an optimal value and recommending to a user.