Keynote Speaker:

Sallie Keller-McNulty, Dean of Engineering, Rice University (also 2006 President of the American Statistical Association)

Title: Reliability Reloaded

In this age of exponential growth in science and technology, the capability to evaluate the performance, reliability, and safety of complex systems presents new challenges. Today's methodology must respond to the ever increasing demands for such evaluations to provide key information for decision and policy makers at all levels of government and industry, problems ranging from national security to space exploration. Scientific progress in integrated reliability assessment requires the development of processes, methods, and tools that combine diverse information types (e.g., experiments, computer simulations, expert knowledge) from diverse sources (e.g., scientists, engineers, business developers, technology integrators, decision-makers) to assess quantitative performance metrics that can aid decision-making under uncertainty. These are highly interdisciplinary problems. The principle role of the statistician is to bring statistical sciences thinking and application to these problems. By the nature of our training, statisticians frequently assume the role of scientific integrator, hence are well poised to lead the development of integrated reliability assessments. However, this puts the statistician closer to policy pressures and politics. This talk will focus on the growing challenges facing statistical sciences in the domain of integrated reliability assessment and how we, as statisticians, must separate the scientific method from the politics of the scientific process to develop assessment methodology that will facilitate the decision making processes.

Plenary Speakers:

William Q. Meeker, Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences, Iowa State University

Using Simulation and Graphics as an Aid in Planning Complicated Experiments

The combination of Monte Carlo simulation and graphics provides powerful tools for helping to plan complicated experiments. Although the ideas apply more generally, this talk will describe a collection of methods and procedures that have been developed for planning engineering reliability experiments. Such experiments include life tests, accelerated life tests, repeated measures degradation tests, and accelerated destructive degradation tests. The design of such reliability experiments typically requires answering questions about sample size, length of the test and, for accelerated tests, allocation of test units to different levels of the accelerating variable(s). Models for the data from such experiments must accommodate complications such as random effects, nonlinear estimation, and censoring. As such, standard experimental design tools need to be extended. I will describe methods that employ graphical displays for combinations of large-sample approximations for precision metrics and for the display of simulation results. Simulation will be shown to be a particularly versatile and valuable tool for providing insights into such complicated experimental design problems.

Way Kuo, http://www.ece.utk.edu/bios/Faculty/Kuo.html

University Distinguished Professor and Dean of Engineering, University of Tennessee

Issues Related to Reliability of Nanoelectronics

Nanoelectronics is a driving force for strong economic growth in the U.S., and some analysts predict that its impact will bring about the next industrial revolution. In the 2005 National Academy’s publication of Keck Futures Initiative, yield/reliability is cited as the key element of the success of nano fabrication and manufacturing. However, very little actual research and development has been conducted on yield/reliability assessment and improvement in nanoelectronics. One reason for this dearth of research is that reliability modeling in nanoelectronics presents an interdisciplinary subject that heavily involves new physics phenomena and statistics. In nanoelectronics, feature sizes are so small that it may affect global behavior and cause system failure, and, consequently, reliability modeling of both the time-dependent and the spatio-temporal evolution of nano defects must take into consideration. All these issues will be addressed in this talk.

Edward G. Schilling, Professor Emeritus, Rochester Institute of Technology

Lessons From a Career in Quality

There is much to be learned from experience. This presentation follows a career in quality and reveals some of the practical lessons that come out of the experience. It will treat various aspects of real life application of statistical quality control.

A. Blanton Godfrey, Dean of the College of Textiles, North Carolina State University

The Lighter Side of Quality

How many people in this room think statistics was their favorite course in college? This is a question I have asked many times in opening an executive quality workshop. Once – but only once – I was surprised. Two people raised their hands. Why is something most of us find fascinating so often the most dreaded course on campus? Why is the easiest way to stop a conversation dead is by mentioning that you’re a statistician? We’ll take a lighter look at quality, productivity and statistics in the hope, perhaps in vain, of keeping some of you awake after dinner.

Thom Mason, Associate Laboratory Director for the Spallation Neutron Source, Oak Ridge National Laboratory

The Spallation Neutron Source: Scientific Opportunities and Challenges in Data Analysis and Visualization

The Spallation Neutron Source will use an accelerator to produce the most intense beams of pulsed neutrons in the world when it is complete in June 2006.  It will serve a diverse community of users with interests in condensed matter physics, chemistry, engineering materials, biology, and beyond.  The combination of improved source intensity and a new generation of high performance scattering instruments will produce structural and dynamic information of greater quality, and in much greater volumes, than has previously been available.  The scientific opportunities and the challenges posed by these new capabilities will be described together with the hardware and software underpinning the science.