Some Efficient Control Charts for Monitoring Process Locatio

发布时间：2023-04-29 04:20

　　统计过程控制(SPC)包含了一系列统计检测程序,用以确保产品制造或服务满足一定的质量标准或者符合消费者或客户的需求。控制图是统计过程控制中的一个重要方法,被广泛运用于区分变化中的随机因素和非随机因素。设计、发展有效的控制图对改善过程监督来说总是值得的。这篇论文针对不同情形为改善过程控制提出了一些新的有效的控制图,对于产品质量从业人员来说,使用这些新的控制图将有助于监测和提高产品质量。当我们能够获得被监控的质量特征有关的补充信息时,我们可以方便地使用它来提高控制图的效率从而增加控制图的敏感性。在这个背景下,针对监控一般过程的中心位置,我们通过使用比例型估计量替代简单的均值估计量将辅助信息带入CUSUM控制图。在Shewhart控制图中通过利用单个样本的信息对过程状态作出决定,这将会推迟对小位移的监测。此外,这可能使工程师们基于单个样本信息决定过程状态变得十分困难。在此框架中,我们提出了一般化多个非独立状态(GMDS)抽样体系,它拓展了非独立状态(MDS)抽样体系。这个控制图策略包含了两对控制极限,结合了Shewhart体系和MDS体系。我们整合了GMDS体系来设计变量控制图以有效监督正态...

【文章页数】：140 页

【学位级别】：博士

【文章目录】：
Abstract
摘要
Chapter 1 Introduction
    1.1. Statistical Process Control
    1.2. Control Chart
        1.2.1. Phase-Ⅰ and Phase-Ⅱ Control Charts
        1.2.2. Variable and Attribute Control Charts
        1.2.3. Nonparametric Control Charts
    1.3. Some Modified Control Charts for Process Location
    1.4. Motivation
    1.5. Outline of the Thesis
Chapter 2 CUSUM Control Charts using Ratio-Type Estimators
    2.1. Introduction
    2.2. Location Estimators Based on Auxiliary Information
    2.3. General Structure of the Proposed CUSUM Charts
        2.3.1. Algorithm
    2.4. Performance Evaluation
    2.5. Comparison with the Existing Control Charts
        2.5.1. Illustrative Example
    2.6. Conclusion
Chapter 3 Optimal Synthetic Tukey’s Control Charts
    3.1. Introduction
    3.2. Tukey’s Control Chart
    3.3. The Conforming Run Length Chart
    3.4. The Proposed Optimal Synthetic Tukey’s Control Charts
        3.4.1. Computation of ARL Values
        3.4.2. Algorithm
    3.5. Performance Evaluation and Comparison
        3.5.1. Simulation Study
        3.5.2. Real Data Application
    3.6. Conclusion
Chapter 4 A Variable Control Chart under Generalized Multiple Dependent State Sampling
    4.1. Introduction
    4.2. Proposed (?) Control Chart
    4.3. Results and Discussion
    4.4. Comparative Study
        4.4.1. Simulation Study
        4.4.2. Application of the Proposed Chart in Injection Mold Process
        4.4.3. Case Study
    4.5. Conclusion
Chapter 5 Control Charts for Multivariate Poisson Count Data
    5.1. Introduction
    5.2. The Design Structures of the MP Control Charts
        5.2.1 Algorithm
    5.3. Performance Evaluation
    5.4. Performance Comparison
        5.4.1 Simulation Study
        5.4.2 Illustrative Example
    5.5. Conclusion
Chapter 6 Distribution-Free Homogeneously Weighted Moving Average Control Charts
    6.1. Introduction
    6.2. Nonparametric HWMA Control Charts
        6.2.1. The Design Structure of the Proposed NPHWMA-SN Control Chart
        6.2.2. The Design Structure of the Proposed NPHWMA-SR Control Chart
    6.3. Performance Evaluation and Comparison
        6.3.1. Algorithm
        6.3.2. NPHWMA-SN chart
        6.3.3. NPHWMA-SR chart
    6.4. Application
        6.4.1. Application of NPHWA-SN chart
        6.4.2. Application of NPHWA-SR chart
    6.5. Conclusion
Chapter 7 Discussion
    7.1. Future Recommendations
Bibliography
Publications
Acknowledgements



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