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

研究启动奖：质量保证中一些重要主题的决策分析方法

• 批准号: 9209344
• 负责人: Telba Irony
• 金额: $ 9万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-08-01 至 1997-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9209344&HistoricalAwards=false
• 关键词: Research; Initiation; Award; Decision; Analysis

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.

质量保证是一个统计技术 和解决问题的方法，以实现和 提高质量。 在这个项目中，质量的重要主题 保证将在贝叶斯的背景下进行研究 统计和决策分析。 第一个主题是 这是统计过程控制。 基于控制图 质量的后验分布和可信区间 指标将被定义和分析。 第二个主题是 探讨的是评估概率的动机 传统上用于质量保证的分布。 这些 模型将通过分析背后的物理推导出来， 制造系统。 通常，需要使用诊断 测试，以决定是否来自一个 生产线符合要求。 第三个专题 要研究的是诊断测试的校准， 删失数据 质量是成功、成长和发展的关键因素， 增强竞争地位。 总有一个实质性的 从任何有效的计划中获得的投资回报， 提高质量。 这些计划导致市场增加 渗透率、更高的生产率和更低的整体成本 制造业和服务业。