Research Initiation Award: A Decision Analysis Approach to Some Important Topics in Quality Assurance

质量保证是一个使用统计技术和解决问题的方法来实现和提高质量的领域。在这个项目中，将在贝叶斯统计和决策分析的背景下调查质量保证方面的重要主题。要解决的第一个主题是统计过程控制。将定义和分析基于质量指标的后验分布和可信度区间的控制图。第二个要探讨的主题是传统上在质量保证中采用的概率分布评估的动机。这些模型将通过分析制造系统背后的物理原理而得到。通常，为了确定来自生产线的产品是否符合要求，有必要使用诊断测试。要研究的第三个主题是基于审查数据的诊断测试的校准。质量是通向成功、成长和增强竞争地位的关键因素。任何旨在提高质量的有效计划都会带来可观的投资回报。这些计划增加了市场渗透率，提高了生产率，降低了制造和服务的总成本。

Quality assurance is a field in which statistical techniques and problem-solving methods are used in order to achieve and improve quality. In this project, important topics in quality assurance will be investigated in the context of Bayesian statistics and decision analysis. The first topic to be addressed is Statistical Process Control. Control charts based on posterior distributions and credibility intervals for quality indexes will be defined and analyzed. The second topic to be explored is the motivation underlying assessments of probability distributions traditionally adopted in quality assurance. These models will be derived by analyzing the physics behind the manufacturing systems. Often, it is necessary to use diagnostic tests in order to decide whether or not items coming from a production line are conforming to requirements. The third topic to be studied is the calibration of diagnostic tests based on censored data. Quality is a key factor leading to success, growth and enhanced competitive position. There is always a substantial return on investment from any effective program designed to improve quality. These programs result in increased market penetration, higher productivity and lower overall costs of manufacturing and services.