The project concerns the role of statistical design, modeling, and analysis in quality engineering. Because industrial experimentation is usually expensive, emphasis is given to techniques and strategies which minimize experimental effort, and maximize information gained from analysis of results. Central topics are: reduction of variation; designing products robust to transmitted variation and to environmental variation; modeling control processes to achieve better understanding of the roles and possible conflicts between statistical process control (SPC) and automatic process control (APC); developing bases for choosing standards; and data-based prediction of possible future upsets.
