Multi-objective Robust Optimization Design Of Rare Earth Polishing Powder Polishing Process

Robust optimization design with multi-objective response is a frontier field of optimization design.In the design process,only the optimality of optimization results is considered,while the robustness of optimization results and the economy of the process are ignored,which leads to the problems of large fluctuation of product performance and high manufacturing cost.Therefore,how to integrate the ideas of robustness and economy into the robust optimization design of multiple quality characteristics will become the core problem that needs to be solved in the optimal design of multi-response products.Based on rare earth polishing powder,polishing process as the research object,select four controllable factor analysis its cutting rate of cerium polishing powder and scratches,put forward a kind of satisfaction function and the quality loss function the multi-objective robust optimization design method of combining method can solve the multi-objective optimization results to some extent the robustness and the process of economic problems,The optimal combination of technological parameters and the preparation of high performance rare earth polishing slurry were obtained.The main research work of this paper is as follows:(1)As the scientificity and rationality of each objective response weight in multiobjective robust optimization design have a direct impact on the reliability of the optimization effect,this paper adopts a weighting method that comprehensively considers the subjective weight and objective weight of each response.Average assignment method is adopted to define the subjective weight,determine the objective weight of entropy theory,considering both draw lessons from the engineer or test both technical personnel of the pilot experience and analysis of the sample data of objective information,avoids the single information science is not strong,cause response weights for this article solve the problem of multi-objective robust design optimization solid foundation.(2)To solve the problem of how to consider the optimality and robustness of the optimization results simultaneously in the multi-objective robust optimization design of cerium-based polishing powder polishing process,a method of optimizing the comprehensive satisfaction function of each response mean and signal-to-noise ratio simultaneously was adopted in this paper.The method ensures the optimality of the optimization results by optimizing the mean value,while optimizing the SNR to avoid the inconsistency of the results caused by the fluctuation of the response variance,and turns the multi-objective problem into a simplified problem to solve the maximum value of the optimization objective function.Compared with the method considering only the mean value,the results show that this method can provide some reference for the multi-objective robust optimization design of rare earth polishing powder polishing process.(3)In view of the problem of how to reduce the loss degree between actual usage and ideal value in multi-objective robust optimization design,a method of multivariate quality loss function based on signal-to-noise ratio is adopted.In this method,the quality loss of response is considered on the basis of the optimization of the satisfaction function,so that the decision basis of multi-objective response optimization design is changed from the single index of comprehensive satisfaction to two evaluation indexes of comprehensive satisfaction and comprehensive quality loss,which provides a more comprehensive theoretical basis for the comprehensive evaluation of multi-objective optimization design schemes.At the end of the paper,the reliability and effectiveness of the proposed method are verified by comparative analysis,and the focus and direction of future research are clarified.