Fall Technical Conference (FTC) Webinar Series
The cost of attending is FREE, but registration is required. To receive the webinar information, you must first register. Please register here: https://www.eventbrite.com/e/ftc-2020-webinar-series-tickets-126000499887
Can’t make it one week? Never fear – the webinar will be recorded and posted to the FTC website.
This is a chance to virtually connect with your FTC friends and colleagues. Hope to see you there as we recognize the work of our colleagues!
The Fall Technical Conference has long been a forum for both statistics and quality and is co-sponsored by the American Society for Quality (Chemical and Process Industries Division and Statistics Division) and the American Statistical Association (Section on Physical and Engineering Sciences and Section on Quality and Productivity).
Week 1: Friday, November 6 1:00 eastern (CPID – Youden)
Speaker: Bobby Gramacy, Virginia Tech (CPID – Youden award)
Title: Replication or Exploration? Sequential Design for Stochastic Simulation Experiments
Abstract: We investigate the merits of replication, and provide methods that search for optimal designs (including replicates), in the context of noisy computer simulation experiments. We first show that replication offers the potential to be beneficial from both design and computational perspectives, in the context of Gaussian process surrogate modeling. We then develop a lookahead based sequential design scheme that can determine if a new run should be at an existing input location (i.e., replicate) or at a new one (explore). When paired with a newly developed heteroskedastic Gaussian process model, our dynamic design scheme facilitates learning of signal and noise relationships which can vary throughout the input space. We show that it does so efficiently, on both computational and statistical grounds. In addition to illustrative synthetic examples, we demonstrate performance on two challenging real-data simulation experiments, from inventory management and epidemiology.
Week 2: Friday, November 13 1:00 eastern (STAT – Bisgaard)
Speakers: Christine M. Anderson-Cook (Los Alamos National Laboratory), Lu Lu (University of South Florida), Peter A. Parker (NASA)
Title: Effective Interdisciplinary Collaboration between Statisticians and Other Subject Matter Experts
Abstract: Progress and innovative solutions to challenging problems often come at the intersection of multiple disciplines. Statisticians frequently are presented with opportunities to participate on or lead interdisciplinary teams, where how well their contributions are received is a function of their effectiveness as collaborators. We outline six fundamentals for effective collaboration: respect, shared common goals, trust, commitment, intercommunication, and execution. We focus on how these core aspects of a successful collaboration can be encouraged by statisticians. Through an example, we illustrate how problems can arise when some of the key components are missing and what strategies can be used to mitigate problems. Finally, we describe how early career statisticians can work to improve their collaboration skills to improve their impact on teams with diverse backgrounds.
Week 3: Friday, November 20, 1:00 eastern (STAT – Nelson)
Speaker: Nathaniel Stevens, University of Waterloo
Title: Design and Analysis of Confirmation Experiments
Abstract: The statistical literature and practitioners have long advocated for the use of confirmation experiments as the final stage of a sequence of designed experiments to verify that the optimal operating conditions identified as part of a response surface methodology strategy are attainable and able to achieve the value of the response desired. However, until recently there has been a gap between this recommendation and details about how to perform an analysis to quantitatively assess if the confirmation runs are adequate. Similarly, there has been little in the way of specific recommendations for the number and nature of the confirmation runs that should be performed. In this talk, we propose analysis methods to assess agreement between the mean response from previous experiments and the confirmation experiment, as well as suggest a strategy for the design of confirmation experiments that more fully explores the region around the optimum.
Week 4: Friday, December 4 1:00 eastern (CPID – Wilcoxon)
Speaker: Qingyu Yang, Wayne State University
Title: From micro to macro: material degradation modeling and failure prediction using microstructure images
Abstract: The microstructure of materials determines its behavior and critical failure and quality characteristics in various systems such as manufacturing systems for automotive structures, aircraft engine components, bio-devices, and artificial organs. However, in conventional reliability and quality research area, reliability analysis and product quality control usually start from the macroscopic level without considering material microstructures. This problem becomes more critical in lightweight autobody manufacturing, where ultra-high-strength steels (at 1~1.8GPa strength) are used or under development. This presentation will focus on statistical modeling to efficiently extract material microstructure information and further incorporate it to enable accurate failure/reliability prediction and efficient product quality control. Simulation studies and a real-world case study of the dual-phase advanced high strength steel are conducted to verify the developed methodology.
Week 5: Thursday, December 10, 3:00 eastern (Shewell)
Speaker: Peter Goos, KU Leuven
Title: OMARS Designs: Bridging the Gap between Definitive Screening Designs and Standard Response Surface Designs
Abstract: Response surface designs are a core component of the response surface methodology, which is widely used in the context of product and process optimization. In this contribution, we present a new class of 3-level response surface designs, which can be viewed as matrices with entries equal to −1, 0 and +1. Because the new designs are orthogonal for the main effects and exhibit no aliasing between the main effects and the second-order effects (two-factor interactions and quadratic effects), we call them orthogonal minimally aliased response surface designs or OMARS designs. We constructed a catalog of 55,531 OMARS design for 3 to 7 factors using integer programming techniques. Also, we characterized each design in the catalog extensively in terms of estimation and prediction efficiency, power, fourth-order correlations, and projection capabilities, and we identified interesting designs and investigated trade-offs between the different design evaluation criteria. Finally, we developed a multi-attribute decision algorithm to select designs from the catalog. Important results of our study are that we discovered some novel designs that challenge standard response surface designs and that our catalog offers much more flexibility than the standard designs currently used.
Week 6: Friday, December 18 1:00 eastern (Q&P – Hahn)
Speaker: Martha Gardner, GE