Statistics Seminar

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Title: Quality improvement: from autos and chips to nano and bio Speaker:  Dr. C. F. Jeff Wu Abstract: Quality improvement (QI) has a glorious history, starting from Shewhart’s path-breaking work on statistical process control to Deming’s high-impact work on quality management. Statistical concepts and tools played a key role in such work. As the applications became more sophisticated, elaborate statistical methods were required to tackle the problems. In the last three decades, QI has seen more use of experimental design and analysis, particularly the methodology of robust parameter design (RPD). I will first review some major ideas in RPD, focusing on its engineering origin and statistical methodology. I will then discuss more recent work that expands the original approach, including the use of feedback control and operating window. To have an effective solution, the subject matter knowledge often needs to be incorporated. Techniques for fusing data with knowledge will be presented. For advanced manufacturing and high-tech applications, there are new challenges and possible paradigm shift posed by three features: large varieties, small volume and high added value. I will speculate on some new directions and technical development. Throughout the talk, the ideas will be illustrated with real examples, ranging from the traditional (autos and chips) to the modern (nano and bio). Note: This would be a rehearsal talk for the Deming lecture to be given on July 31, JSM.


  • Workflow Status: Published
  • Created By: Anita Race
  • Created: 07/24/2012
  • Modified By: Fletcher Moore
  • Modified: 10/07/2016


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