Statistical Methods for Process Understanding and Improvement

用于过程理解和改进的统计方法

• 批准号: 184125-2012
• 负责人: Steiner, Stefan
• 金额: $ 1.75万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=523042
• 关键词: Statistical; Methods; Process; Understanding; Improvement

My research develops innovative statistical methods for process improvement and understanding. More specifically, I propose to continue my work in the following three areas among others: Statistical Engineering, Measurement System Assessment, and Process Monitoring and Understanding. The results of my research which tackle real world problems have the potential to greatly influence industrial practice. Specific goals include improving the definition and widening the application of Statistical Engineering and developing a field failure prediction methodology applicable at Research in Motion, based on data from a variety of sources, including manufacturing, final test, warrant and customer usage. In addition, I plan to develop new and better plans and analyses for the assessment and comparison of measurement systems. Here a specific focus will be on relaxing questionable assumptions and tackling non-standard measurement characteristics, such as, counts, bounded data and multivariate data. A third research theme focuses on developing models and methods for monitoring processes when the output characteristics are not directly comparable and to better understand their performance. One specific project involves developing a method for monitoring the surgical learning curve. I also propose to re-examine the fundamental concepts and terminology of Statistical Process Control (SPC). The current environment has little coherence and many contradictions that result in confusion. Developing a consistent and concise set of definitions will improve SPC understanding and hopefully successful usage.

我的研究开发了创新的统计方法，用于过程改进和理解。更具体地说，我建议在以下三个领域继续我的工作：统计工程，测量系统评估，过程监控和理解。我的研究成果解决了真实的世界问题，有可能极大地影响工业实践。具体目标包括改进统计工程的定义和扩大其应用，并根据来自各种来源的数据（包括制造、最终测试、保修和客户使用），开发适用于Research in Motion的现场故障预测方法。此外，我计划为评估和比较测量系统制定新的和更好的计划和分析。在这里，一个具体的重点将是放松有问题的假设和解决非标准的测量特性，如计数，有界数据和多变量数据。第三个研究主题侧重于开发模型和方法，用于在输出特性不直接可比时监测流程，并更好地了解其性能。一个具体的项目涉及开发一种监测手术学习曲线的方法。我还建议重新审视统计过程控制（SPC）的基本概念和术语。目前的环境缺乏一致性，有许多矛盾，导致混乱。开发一套一致和简洁的定义将提高SPC的理解和成功的使用。