A new method for optimizing process parameters of active measurement grinding based on grey target decision making

Abstract

Active measurement technology is used widely in the modern precision-grinding process; currently, however, it is tedious and time consuming to adjust the process parameters of grinding process. This process usually depends on the experience of operators, which directly affects the processing efficiency and intelligent control level. Aiming to optimize these grinding-process parameters, we propose a grey target decision-making method based on the uniform effect measure to realize the intelligent optimization of process parameters. First, we obtain the experimental data of process parameters and evaluation parameters using the orthogonal experimental method, and then we calculate and analyze the degree of relation between process parameters and evaluation parameters based on grey system theory. Then we can obtain the process parameters that have the greatest influence on the workpiece surface roughness, workpiece roundness, and grinding process time. Second, through the proposed grey target decision-making method based on the uniform effect measure, and combined with grey relation analysis, we assign the weights of different evaluation parameters. By optimizing the calculation of multigroup evaluation parameters, we obtain the group of evaluation parameters with the best synthetic effect and identify the optimal combination of parameters to guide production. Through a large number of experimental verifications and analyses, we find that the proposed grinding process parameters optimization method can obtain the best combination of process parameters and can effectively improve processing quality and processing efficiency. The research results provide a theoretical basis for the optimization of grinding process parameters and enhance the intelligent degree of precision grinding.