Study On Robust Optimization Method For Multiple Response Parameters Based On Fuzzy Theory

With the improvement of demand standards and production complexity,to achieve robust optimization of multiple responses,it is necessary to consider the conflicting or association relationship between the responses,which is difficult measured with fixed weight,and considering the robustness of the optimization results.Due to the fuzziness of the response relationship and the uncertainty of the relationship between the response quality and the comprehensive quality index.This paper considered the robust optimization process of multiple response parameters as a fuzzy complex nonlinear system,and study the robust optimization method based on fuzzy theory.Because of the weight method relies on the weight distribution,lack of using the effective information and ignore the relationship between the responses.Based on the useful information provided by the productive process,the fuzzy logic reasoning method is used to excavate the uncertainty relation between the responses,and the quality characteristics of the multiple responses are calculated by the conditional synthesis and the fuzzy relation calculation.And study on the robust optimization design base on the fuzzy logic reasoning.With the increase of noise factors and level setting,the number of experiments will fold increase.The BP neural network prediction model of good nonlinear mapping ability,which can establish the relationship between the factors and response,to predict the response values reducing the number of repeated experiments and the cost of experiments.When the number of noise is large and difficult to measure,it cannot set the noise factors and parameters,according the quality fluctuation value measure the robustness of system though the many experiments.Based on the hesitant fuzzy set allows the membership number of elements is set not unique,to assemble the quality fluctuation response value,which can avoid the partial response information loss in mean and variance calculation,and though the hesitant fuzzy decision to determine the optimal robust parameter combination.The fuzzy theory and robust optimization is combined to explore and innovate the robust optimization process,solving the problems existing in the application of quality tools for complex production process and quality requirements of enterprises,enriching the theoretical research results in the field of quality engineering.