【摘要】：輪廓控制是利用控制圖理論對呈現特定函數關系（此函數關系稱為輪廓）的過程（或產品）質量特性進行控制，是質量工程領域統(tǒng)計過程控制中的研究熱點。本文將針對復雜產品制造加工過程中的實際問題，主要就輪廓內測量點位置發(fā)生變化、輪廓內數據存在相關性、輪廓特定變異預先已知和輪廓中變量為角度變量 等情況下的輪廓控制方法分別進行研究。首先，針對不同輪廓內測量點位置發(fā)生變化的情況，構建了基于線輪廓度誤差的非線性輪廓聯合控制圖，給出了聯合控制圖的設計方法。比較研究表明，聯合控制圖在檢測參數誤差時非常有效，且優(yōu)于其他基于差異度量的控制方法；而且在同時檢測過程中的參數誤差和形狀誤差時對于小偏移非常敏感。另外，提出了聯合控制圖的實施步驟和過程調整原則，有利于控制方法的現場應用和對實際 生產過程的調整。其次，當輪廓內數據存在相關關系時，構建了基于高斯過程模型的內部相關性線性輪廓聯合控制圖,提出了兩種休哈特類型多元控制圖分別用于監(jiān)測第二階段中輪廓線性部分和內部相關性。所提方法在與其他方法比較研究中考慮了不同受控輪廓內部相關強度。仿真比較結果顯示，當檢測線性部分的變異時，所提方法在受控線性輪廓內部相關性較強時的控制性能較好；在監(jiān)控線性輪廓內部相關性時，所提方法對于相關關系的較大偏移更為敏感。而且，應用分析研究表明， 所提聯合控制圖在實際應用中較為方便，，而且能有效對過程進行控制。再次，對于預先已知過程發(fā)生特定類型變異的情況，建立了三種用于快速檢測過程中線性輪廓形狀變化的定向控制圖。比較研究顯示，所提定向控制圖均能快速檢測出過程中特定變異，且具有穩(wěn)健性；當失控輪廓在受控輪廓附近波動時，所提方法對線性輪廓的形狀變化較為敏感；當失控輪廓偏離受控輪廓較多時，在 輪廓內測量點個數較多時所提方法也能快速有效檢測線性輪廓的形狀變化。最后，研究了角度變量線性輪廓控制方法，建立了角度變量線性輪廓的第二階段控制圖，并提出了第一階段控制方法。模擬仿真分析表明，所提第二階段控制圖能快速有效地檢測過程變異。
[Abstract]:Contour control is a control of the process (or product) quality characteristics that presents a specific functional relationship (or product profile) by using the control chart theory. It is a hot topic in statistical process control in the field of quality engineering. Aiming at the practical problems in the process of manufacturing and processing of complex products, this paper will mainly focus on the change of the position of the measuring points in the contour and the correlation of the data in the contour. The contour control methods are studied under the condition that the specific variation of contour is known in advance and the variables in the contour are angular variables. Firstly, the joint control chart of nonlinear contour based on line contour error is constructed for the change of measuring point position in different contours, and the design method of joint control chart is given. The comparative study shows that the joint control chart is very effective in detecting parameter errors and is superior to other control methods based on difference measurement, and is very sensitive to small offset when the parameter errors and shape errors are detected simultaneously. In addition, the implementation steps of the joint control chart and the principle of process adjustment are put forward, which is beneficial to the field application of the control method and the adjustment of the actual production process. Secondly, when the data in the contour has the correlation relation, the joint control chart of the internal correlation linear contour based on Gao Si process model is constructed. Two types of Heinhart multivariate control charts are proposed to monitor the linear and internal correlation of the contour in the second stage. In comparison with other methods, the proposed method takes into account the internal correlation strength of different controlled contours. The simulation results show that the proposed method has better control performance when the variation of the linear part is detected when the internal correlation of the controlled linear contour is strong. The proposed method is more sensitive to the large deviation of the correlation relationship when monitoring the internal correlation of the linear profile. Furthermore, the application analysis shows that the proposed joint control chart is more convenient in practical application and can effectively control the process. Thirdly, three directional control charts are established for rapid detection of changes in linear contour shape when a specific type of variation occurs in a process known in advance. The comparative study shows that the proposed directional control charts can quickly detect the specific variation in the process and have robustness, and when the runaway contour fluctuates near the controlled contour, the proposed method is more sensitive to the change of the shape of the linear contour. When the runaway contour deviates more from the controlled contour, the proposed method can detect the shape change of the linear contour quickly and effectively when the number of measured points in the contour is more. Finally, the linear contour control method of angle variable is studied, the second stage control diagram of linear contour of angle variable is established, and the first stage control method is proposed. Simulation results show that the proposed second stage control chart can detect process variation quickly and effectively.
【學位授予單位】：天津大學
【學位級別】：博士
【學位授予年份】：2013
【分類號】：TH16

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