本文選題：PECVD + 氮化硅薄膜　； 參考：《上海交通大學》2015年博士論文

【摘要】：等離子體增強化學氣相沉積(Plasma Enhanced Chemical Vapor Deposition,PECVD)的氮化硅(Si N x)薄膜(以下簡稱PECVD氮化硅薄膜)是提高太陽能電池光電轉換效率的關鍵,研究PECVD氮化硅薄膜制造過程的質量控制技術能夠提高產品的成品率、合格率、優(yōu)質率,促進太陽能電池相關行業(yè)的快速發(fā)展,對我國太陽能電池行業(yè)有非常重要的理論和現實意義。在國內外已有的研究成果的基礎上,本文圍繞著PECVD氮化硅薄膜制造過程質量控制提出工藝參數具有相關性時的故障診斷、制造初期的質量控制和兩種失控模式下的質量控制三個的科學問題�；谝延械牡璞∧こ练e技術、正交試驗設計、貝葉斯理論、多元統(tǒng)計技術、多元診斷、計算機仿真技術等研究了PECVD氮化硅薄膜的工藝參數快速優(yōu)化、基于路徑圖的制造過程故障診斷、基于貝葉斯理論制造過程初期的質量控制、兩種失控模式下多元統(tǒng)計過程質量控制四個關鍵技術,建立了PECVD氮化硅薄膜的工藝參數快速優(yōu)化模型,基于路徑圖的多元故障診斷模型,基于貝葉斯理論的制造過程初期質量控制模型,基于多種總體協(xié)方差矩陣估值構建的多元指數加權移動平均(Multivariate Exponentially Weighted Moving-Average,MEWMA)控制圖的質量控制模型。具體研究內容從以下幾個方面展開:(1)分析了PECVD氮化硅薄膜的制造過程,論述了氮化硅薄膜的關鍵質量特征以及影響關鍵質量特征的關鍵影響因素。闡述了PECVD氮化硅薄膜制造過程質量控制的特點,分析了基于統(tǒng)計過程控制的質量控制方法應用于PECVD氮化硅薄膜制造過程時存在的問題,提出了PECVD氮化硅薄膜制造過程質量控制的科學問題,提出了與PECVD氮化硅薄膜制造過程質量控制方法相關的四個關鍵技術,提出了PECVD氮化硅薄膜質量控制模型。(2)通過領域知識和專家意見獲取氮化硅薄膜的主要影響因子和質量特性參數,利用單因素物理實驗確定了各主要影響因子和質量特征值之間的關系,提出了沉積參數快速優(yōu)化的一般過程,給出了基于“綜合評分法”多響應優(yōu)化過程的綜合評分計算方法和評分規(guī)則,分析得到最佳的沉積工藝參數,從而減少了大量的實際物理試驗,提出了PECVD氮化硅薄膜制造過程的工藝參數快速優(yōu)化方法。(3)利用領域內專家的經驗構建氮化硅薄膜故障診斷路徑圖,研究了基于路徑圖的MYT分解方法,將傳統(tǒng)的MYT方法中所有!種可能分解方式歸結成一種統(tǒng)一的含有個獨立因式的分解方式,并在過程均值向量與協(xié)方差矩陣未知的情況下利用F分布確定各分解項的控制上限。通過已確定的各分解項的控制上限,確定各個變量對失控信號的貢獻值,并且用它來確定導致制造過程失控的根本原因,實現PECVD氮化硅薄膜多元統(tǒng)計過程診斷,解決了在PECVD氮化硅薄膜制造過程工藝參數具有相關性及過程均值向量與協(xié)方差矩陣未知的情況下的故障診斷問題,提出了基于路徑圖的PECVD氮化硅薄膜制造過程故障診斷方法。(4)針對在PECVD氮化硅薄膜制造過程初期具有多批次小批量的制造特征,經常面臨樣本容量不足的問題,提出了基于貝葉斯理論的PECVD氮化硅薄膜制造初期的質量控制方法。利用ANOVA方差檢驗和Bartlett齊次檢驗的方法從歷史批次中篩選出與當前批次類似的樣本數據,利用貝葉斯理論分析歷史數據提供的先驗信息,引入EWMA系數來調節(jié)歷史信息在總信息中所占的比重,將總體均值和總體方差的估值表示為歷史批次和當前批次的總體均值和總體方差的加權平均,利用這些估值建立控制圖和計算過程能力指數,構建PECVD氮化硅薄膜的制造初期的質量控制方法。(5)針對PECVD氮化硅薄膜制造過程的多輸入多輸出、兩種失控模式的特點,提出了基于總體協(xié)方差矩陣不同估值MEWMA控制圖的PECVD氮化硅薄膜制造過程的質量控制方法。Hotelling2和MEWMA控制圖使用的前提都是要求總體協(xié)方差矩陣已知,但是在實際制造過程中總體協(xié)方差矩陣通常都是未知的,需要使用樣本協(xié)方差矩陣作為估計值,基于不同的估計值構建控制圖的監(jiān)控性能有著重大的不同。本文在相關總體協(xié)方差估值研究成果的基礎上提出五種總體協(xié)方差估值和MEWMA統(tǒng)計量的數學表達式;其次,對基于總體協(xié)方差的五種估值構建的MEWMA控制圖進行了仿真研究,尋找在在均值向量發(fā)生階躍偏移和單向持續(xù)偏移的條件下監(jiān)控效果最優(yōu)的MEWMA控制圖;構建兩種失控模式下PECVD氮化硅薄膜制造過程的質量控制方法。本文以問題為導向,企業(yè)的實際需求為依托,以統(tǒng)計學為理論根據,以正交試驗設計、計算機仿真、物理試驗為手段,研究了PECVD氮化硅薄膜制造過程質量控制方法,為氮化硅薄膜的質量控制建立了新的方法論,并結合企業(yè)實際將文中所提的技術方法應用到PECVD氮化硅薄膜制造過程質量控制當中,取得了較好的經濟價值。
[Abstract]:The plasma enhanced chemical vapor deposition (Plasma Enhanced Chemical Vapor Deposition, PECVD) silicon nitride (Si N x) thin film (hereinafter referred to as PECVD silicon nitride thin film) is the key to improve the photoelectric conversion efficiency of solar cells. The study of the quality control technology of the manufacturing process of PECVD silicon nitride film can improve the product yield and the rate of qualification. The high quality rate and the rapid development of the solar cell related industries have very important theoretical and practical significance for the solar cell industry in China. Based on the existing research results at home and abroad, this paper focuses on the fault diagnosis when the process parameters of the PECVD silicon nitride thin film manufacturing process are related, and the early manufacturing period. The scientific problems of quality control and three quality control under two kinds of out of control mode. Based on the existing silicon nitride film deposition technology, orthogonal test design, Bayes theory, multivariate statistical technology, multivariate diagnosis, computer simulation technology, the rapid optimization of PECVD silicon nitride thin film is studied, based on the path map manufacturing process. Fault diagnosis is based on the quality control of the initial manufacturing process of Bayesian theory and the four key technologies of multivariate statistical process quality control under two out of control modes. The rapid optimization model of the process parameters of PECVD silicon nitride film is established, the multiple fault diagnosis model based on the path graph, and the initial quality control of the manufacturing process based on the Bayesian theory. The model is based on the multi index weighted moving average (Multivariate Exponentially Weighted Moving-Average, MEWMA) control model based on a variety of overall covariance matrix valuations. The specific research contents are carried out from the following aspects: (1) the manufacturing process of PECVD nitrogen silicon thin film is analyzed, and the correlation of silicon nitride film is discussed. Key quality characteristics and key influencing factors affecting key quality characteristics are discussed. The quality control characteristics of PECVD silicon nitride thin film manufacturing process are described. The problems existing in the application of quality control method based on statistical process control to the manufacturing process of PECVD silicon nitride thin film are analyzed. The quality control of the manufacturing process of PECVD silicon nitride thin film is proposed. Four key technologies related to the quality control method of PECVD silicon nitride thin film manufacturing process are put forward. The quality control model of PECVD silicon nitride film is proposed. (2) the main influence factors and quality characteristic parameters of the silicon nitride film are obtained by field knowledge and expert opinion. The main factors are determined by single factor physical experiment. The relationship between the influence factor and the quality characteristic value is put forward, and the general process of rapid optimization of the deposition parameters is put forward. The comprehensive scoring method and scoring rule based on the multi response optimization process based on the "comprehensive scoring method" are given. The optimum parameters of the deposition process are analyzed, and a large number of actual physical tests are reduced, and PECVD nitriding is proposed. The rapid optimization method for process parameters of silicon film manufacturing process. (3) using the experience of experts in the field to construct the fault diagnosis path map of the silicon nitride film, and study the MYT decomposition method based on the path graph, and sum up all the possible decomposition methods in the traditional MYT method into one independent factorization method, and in the process of the process. In the case of the unknown mean vector and covariance matrix, the F distribution is used to determine the upper limit of the control of each decomposition item. The contribution value of each variable to the runaway signal is determined through the upper control upper limit of the determined Decomposition terms, and it is used to determine the root cause of the loss of control in the manufacturing process, and to diagnose the multivariate statistical process of the PECVD silicon nitride film, The problem of fault diagnosis in the process of PECVD silicon nitride film manufacturing process is solved. A fault diagnosis method for PECVD silicon nitride thin film manufacturing process based on path graph is proposed. (4) there are many batches of small batch in the initial stage of the manufacturing process of PECVD silicon nitride thin film. The quality of the quantity is often faced with the problem of the shortage of sample size. The quality control method of the PECVD silicon nitride film based on Bayesian theory is proposed. The sample data similar to the current batch are screened from the historical batch using the ANOVA variance test and the Bartlett homogeneous test, and the history is analyzed by the Bayesian theory. The prior information provided by the data is introduced, and the EWMA coefficient is introduced to regulate the proportion of historical information in the total information. The estimation of the overall mean and the overall variance is expressed as the weighted average of the overall mean and the overall variance of the historical batch and the current batch, and the control charts and the calculation process capacity index are established by these valuations, and the PECVD silicon nitride is constructed. The quality control method of the early manufacturing of the film. (5) in view of the characteristics of the multiple input multiple output and two out of control modes in the PECVD silicon nitride film manufacturing process, the precondition of the quality control method.Hotelling2 and the MEWMA control chart based on the PECVD silicon nitride film manufacturing process based on the MEWMA control diagram of the overall covariance matrix is proposed. It is required that the overall covariance matrix is known, but the overall covariance matrix in the actual manufacturing process is usually unknown, and the sample covariance matrix should be used as an estimated value. The monitoring performance of the control chart based on the different estimated values is very different. This paper is based on the results of the Research on the overall covariance estimation. Five mathematical expressions of the total covariance estimations and MEWMA statistics are given. Secondly, the MEWMA control graph based on the five estimations of the total covariance is simulated to find the best MEWMA control chart under the condition of the step shift and the one-way continuous migration of the mean vector; and the construction of the two out of control mode PECV The quality control method of D silicon nitride thin film manufacturing process is based on the problem oriented, the actual demand of the enterprise, based on the statistics theory, the method of orthogonal test design, computer simulation and physical test as the means to study the quality control method of the PECVD silicon nitride thin film manufacturing process, which has established the new quality control of the silicon nitride film. The method is applied to the quality control of the PECVD silicon nitride film manufacturing process with the practice of the enterprise, and it has achieved good economic value.
【學位授予單位】：上海交通大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：TB383.2;TM914.4
，

本文編號：1967969