本文選題：復(fù)雜作用關(guān)系過程 + 穩(wěn)健性參數(shù)設(shè)計(jì)��； 參考：《鄭州大學(xué)》2014年碩士論文

【摘要】：穩(wěn)健性參數(shù)設(shè)計(jì)是提高制造過程穩(wěn)定性,減小產(chǎn)品質(zhì)量波動(dòng)的主要方法。隨著技術(shù)水平的不斷提高,眾多行業(yè)出現(xiàn)了大量的作用關(guān)系復(fù)雜的制造過程,這些過程擁有多個(gè)極值點(diǎn),而且其影響因子與響應(yīng)輸出之間存在高階非線性關(guān)系�，F(xiàn)有的穩(wěn)健性參數(shù)設(shè)計(jì)方法由于實(shí)驗(yàn)設(shè)計(jì)方式、模型形式的限制,只能局部優(yōu)化參數(shù),不適用于復(fù)雜工藝過程的穩(wěn)健性研究。如何在可行域全局范圍內(nèi)對質(zhì)量特性的均值與方差進(jìn)行有效建模,進(jìn)而實(shí)現(xiàn)復(fù)雜作用過程全局意義上的穩(wěn)健性優(yōu)化,成為制造業(yè)質(zhì)量改進(jìn)的關(guān)鍵問題之一。本文從全局穩(wěn)健性的角度探究復(fù)雜作用過程的參數(shù)優(yōu)化問題,主要研究內(nèi)容如下： (1)構(gòu)建了基于支持向量機(jī)的單一響應(yīng)模型。采用單一響應(yīng)建模方式,研究可控因子變差和噪聲因子波動(dòng)規(guī)律對響應(yīng)輸出的影響,并結(jié)合因子的聯(lián)合概率分布,以多重積分的形式呈現(xiàn)該影響規(guī)律；進(jìn)而利用支持向量機(jī)優(yōu)良的泛化性能,建立起復(fù)雜作用關(guān)系過程全局范圍內(nèi)響應(yīng)均值與方差的連續(xù)變化模型。在擬合模型的基礎(chǔ)上,通過取點(diǎn)將擬合值與實(shí)際值及雙響應(yīng)擬合值進(jìn)行對比分析,證明了所提方法具有良好的擬合性能和預(yù)測性能。 (2)對建立的模型進(jìn)行了穩(wěn)健性參數(shù)尋優(yōu)研究。提出利用可行域劃分方法研究望大、望小問題的全局尋優(yōu)過程；針對遺傳算法提出使用均勻設(shè)計(jì)構(gòu)造初始種群,針對序列二次規(guī)劃方法提出使用可控因子組合角點(diǎn)和中心點(diǎn)作為初始點(diǎn),然后使用改進(jìn)后的算法對非線性問題進(jìn)行最優(yōu)值求解。 (3)利用所提建模優(yōu)化方法進(jìn)行仿真及實(shí)證研究。運(yùn)用單一響應(yīng)建模構(gòu)建電感電阻串聯(lián)電路和螺母生產(chǎn)過程的近似模型,使用所提優(yōu)化策略對回歸模型進(jìn)行參數(shù)尋優(yōu),通過分析選取最佳因子組合方案,驗(yàn)證結(jié)果表明了所提建模方法和優(yōu)化策略在復(fù)雜作用關(guān)系過程穩(wěn)健性參數(shù)優(yōu)化研究中的有效性和實(shí)用性。 本文提出了適用于復(fù)雜作用關(guān)系過程的全局式穩(wěn)健性參數(shù)優(yōu)化思想及相應(yīng)的實(shí)現(xiàn)方法和應(yīng)用技術(shù)路線,研究成果拓展了穩(wěn)健性參數(shù)設(shè)計(jì)的研究領(lǐng)域,對于制造業(yè)減少過程波動(dòng),提高產(chǎn)品質(zhì)量具有顯著的現(xiàn)實(shí)意義和較高的實(shí)用價(jià)值。
[Abstract]:Robustness parameter design is the main method to improve the stability of the manufacturing process and reduce the fluctuation of product quality. With the continuous improvement of the technical level, a large number of industries have a large number of complex manufacturing processes. These processes have multiple extreme points, and there is a high order nonlinear relationship between the impact factor and the response output. Some robust parameter design methods are limited by experimental design method and model form, only local optimization parameters can not be applied to the robustness study of complex process process. How to model the mean and variance of the quality characteristics effectively in the global scope of the feasible domain, and then realize the stability and robustness in the global significance of the complex process process. It is one of the key problems of quality improvement in manufacturing industry. This paper explores the parameter optimization of complex process from the perspective of global robustness. The main contents are as follows:
(1) a single response model based on support vector machine is constructed. Using a single response modeling method, the influence of the variation of controllable factor and the fluctuation law of noise factor on the response output is studied. Combined with the joint probability distribution of factors, the influence law is presented in the form of multiple integral, and then the excellent generalization performance of the support vector machine is built. A continuous variation model of the mean and variance in the global response process is established. On the basis of the fitting model, the fitting values are compared with the actual values and the two response values. It is proved that the proposed method has good fitting performance and predictive performance.
(2) the robust parameter optimization of the established model is studied. The global optimization process is studied by using the feasible domain division method. The initial population is constructed by using uniform design for genetic algorithm, and the control factor combination corner and the center point are used as the initial point for the sequence two programming method. Then, the improved algorithm is used to solve the nonlinear problem.
(3) using the proposed modeling optimization method to carry out simulation and empirical research. An approximate model of inductor resistance series circuit and nut production process is constructed by using single response modeling. The optimization strategy is used to optimize the parameters of the regression model, and the best factor combination scheme is selected. The results show the modeling method and the advantage of the proposed model. The effectiveness and practicability of chemical strategy in robust parameter optimization of complex interaction processes.
In this paper, the global robustness parameter optimization idea, the corresponding implementation method and the application technical route for the complex interaction process are proposed. The research results expand the research field of the robustness parameter design, and have significant practical significance and high practical value for the manufacturing industry to reduce the process fluctuation and improve the quality of the product.
【學(xué)位授予單位】：鄭州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TB472

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