55th Annual Fall Technical ConferenceASQP.O. Box 3005Milwaukee, WI 53201-3005

Quality AND Statistics: GETTING UP TO DATE

55th AnnualFall Technical ConferenceQuality & Statistics - Getting up to Date

October 13-­14, 2011Kansas City Marriott Country Club PlazaKansas City, MOhttp://cba.ua.edu/ftc2011

SECTION ON PHYSICAL AND ENGINEERING SCIENCES

QUALITY AND PRODUCTIVITY SECTION

Co-­sponsored by:

You are invited to attend the 55th Annual Fall Technical Conference held this year in Kansas City, MO. This conference is the premier forum to discuss topics at the interface of statistics and quality. The theme of this year’s conference is “Quality and Statistics: Getting up to Date.” The goal is to engage researchers and practitioners in a dia-­logue that leads to more effective use of statistics to improve quality. The conference will serve to bring innovations in statistical method-­ologies and quality tools to the forefront. You will have the opportunity to meet informally and exchange views with speakers and colleagues during breaks and in the hospitality suite.

Council MeetingsThree of the sponsoring organizations (Chemical & Process Indus-­tries & Statistics Divisions of ASQ and the Quality & Productivity Sec-­tion of ASA) will also hold council meetings during the conference (days and times TBA). The council meetings are an opportunity for those who wish to become involved in the activities of the societ-­ies to become better informed. Please check the conference web-­site (http://cba.ua.edu/ftc2011) for more information on dates, times, room locations, and other meetings of interest.

Hospitality Suite-­

soring organizations host a hospitality suite each year. This plays a vital role in the strategic operations of the divisions. We welcome new faces and new perspectives on division operations as well as share technical insights with colleagues in a friendly, informal atmosphere. Check at the registration desk for hospitality suite location and hours of operation. Please come to meet us in Kansas City.

AccommodationsA block of rooms is available at the Kansas City Marriott Country Club Plaza through October 1, 2011. Conference delux room rates are $135/night (single/double/triple/quad rate), plus taxes. A link for registration is available on the conference website (http://cba.ua.edu\ftc2011). REGISTER EARLY!

Travel ArrangementsTravel arrangements from the airport to the hotel are the responsibility of the attendee. More information on options is available on the conference website.

Cancellations and RefundsA complete refund of conference registration fees will be given if you cancel prior to September 23, 2011. Cancellations received on or after September 23, 2011 will incur a $125 cancellation fee.

Short Courses will be offered on Wednesday, October 12 and on Saturday, October 15 from 8:30 a.m. to 5:30 p.m. The fee for each course includes coffee breaks and lunch. Registration is limited.

Experimental Design when there are Hard-­to-­Change and Easy-­to-­Change Factors by Jim LucasSponsored by ASQ-­CPIDWednesday, October 12, 2011 | $250

have hard-­to-­change (HTC) and easy-­to change (ETC) factors. -­

ment such as production machinery. We show how to carry out the best experiments when there are HTC and ETC factors. Our

(computer generated) Designs” are often the (current state of the art) designs of choice when there are HTC and ETC factors. We discuss the newest research on experimental designs and show that “optimum designs” are not necessarily good designs for many experimental situations. We discuss situations when optimum (computer generated) designs should be used and alternative situ-­ations when they should not be used. We discuss the role of ran-­domization, show when it is better not to randomize and tell when randomization is essential. This course is designed for people who have run experiments or who have taken a course on Experimental Design. All course participants are requested to e-­mail a descrip-­tion of a current experimental design problem to JMLucas@aya.yale.edu;; the course examples will be built on the problems of the participants.

Using Statistical Engineering to Solve Large, Unstructured Problemsby Ron Snee and Roger HoerlSponsored by ASQ-­STATWednesday, October 12, 2011 | $250

This workshop is designed to enhance the skills of statisticians in using Statistical Engineering to solve large, complex, unstructured problems encountered in business, industry and government. Several case studies of the use of Statistical Engineering in a variety

what Statistical Engineering is, why it is important and how to use it. The difference between Statistical Engineering and the classic application of statistics will also be discussed. The participants will be introduced to the critical leadership skills needed for the successful use of Statistical Engineering. Each participant will develop a personal action plan for using Statistical Engineering in their work environment. The workshop participants will gain insight regarding how to increase the impact of their work and how to transition from being viewed as passive consultants to being viewed as proactive leaders within their organizations. The workshop will use an integration of presentation and discussion of material from articles on Statistical Engineering, the sharing of personal experiences (participants and workshop leaders) in solving large, unstructured

problems, and the development of action plans. The session will be highly interactive enabling extensive participation by all.

Reliability Growthby Jim WisnowskiSponsored by ASA-­SPESSaturday, October 15, 2011 | $250

Reliability growth is the improvement in the reliability of a product (component, subsystem or system) over a period of time due to changes in the product’s design and/or the manufacturing process. Generally, early prototypes produced during the development of a new complex system will contain design, manufacturing and/or engineering

dedicated to reliability or integrated into existing engineering and development tests. To properly manage this reliability improvement process a variety of factors must be considered such as the management strategy toward taking corrective actions, effectiveness

funding and competitive factors. The reliability currently achieved and the projected reliability impact of proposed future corrective actions must be appropriately measured and analyzed. This tutorial presents reliability growth analysis -­ the process of collecting, modeling, analyzing and interpreting data from the reliability growth test program. Depending on the metric(s) of interest, the data collection method, and the corrective action strategy, different models can be utilized (or developed) to analyze the growth processes. The models and methods presented in this tutorial are designed for real world applications and are useful to reliability engineering and program management. This hands-­on workshop will feature software demonstrations and exercises to illustrate basic reliability concepts in addition to reliability growth methods. **Participants should bring their own laptop to load a trial version of software.

Introduction to Rby Garrett GrolemundSponsored by ASA-­Q&PSaturday, October 15, 2011 | $250

This course will teach you the basics of R, as well as how to clean, visualize, and model data with R. No prior R experience is assumed. The course will introduce three popular R packages: reshape2, plyr, and ggplot2. Through these packages, you will learn a powerful

data. A beginner can proceed rapidly by mastering the consistent grammars of these packages without waiting to obtain a broad vocabulary of function names. You will also learn basic R tasks such

will end by examining how to perform common types of statistical modelling with R and overview the many help resources available to R users. R is a very adaptable computer language. The course builds mastery in common data handling and analysis tasks and prepares you to explore more specialized ways of using R. There will be hands on exercises, so please bring your laptop with R installed. R can be downloaded for free from http://cran.r-­project.org/.

ASA-­SPES (Chair): Scott D. Grimshaw, Brigham Young Univ.ASA-­Q&P: Theresa L. Utlaut, Intel Corporation

ASQ-­CPID: David Edwards, Virginia Commonwealth Univ. ASQ-­STAT: Bradley Jones, SAS Institute, JMP Division

Program Committee

Publicity Chair Marcus B. Perry, The University of Alabama

Local Chair Diana Fiddick, University of Kansas

General Conference Chair Tim Reardon, ELFCU

Short Course Chair Shari Kraber, Stat-­Ease, Inc.

55th Annual Fall Technical Conference Registration

ASQ Customer Care

PO Box 3005

Milwaukee, WI 53201-­3005

Complete this form and mail to the address above (you may wish to keep a copy for

your records) or fax to 414-­272-­1734, Attn: ASQ Customer Care. Your registration will

ua.edu/ftc2011. Contact ASQ Customer Care at asq@asq.org, with any questions or

changes related to registration.

PERSONAL INFORMATION

SPECIAL NEEDS

Please list any special needs, disabilities, and/or dietary restrictions that we may

address to make your participation more enjoyable:

CONFERENCE REGISTRATION

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PAYMENT

HOTEL REGISTRATION

Reservations for the Marriott Country Club Plaza may be made on the conference

website (http://cba.ua.edu/ftc2011) or by calling the hotel at (800) 810-­3708.

*denotes required information

Session 6

1:30 -3:00

JQT Invited Session

A Class of Three-Level Designsfor De!nitive Screening in the

Presence of Second-Order E"ects

Bradley JonesSAS Institute, JMP Division

Christopher J. NachtsheimUniversity of Minnesota

Uncertainty & Agreement

Measuring Agreement ofManufacturing and Customer

Testing

Jon M. LindenauerWeyerhaeuser Company

Healthcare Quality

Measuring Process-Level E!ciency in Nursing Homes:

A Bayesian Approach

Robert H. LeeByron J. Gajewski

University of Kansas Medical Center

The Prediction Properties ofClassical and Inverse Regressionfor the Simple Linear Calibration

Problem

G. Geoffrey ViningJohn L. Szarka IIINels G. JohnsonVirginia Tech

Peter ParkerSarah R. Wilson

NASA

Managing Uncertainty inDesign Space

Shari KraberPat WhitcombStat-­Ease, Inc.

Bayesian Data Envelopment Analysisin the Presence of Measurement

Error: A Case Study from theNational Database of Nursing

Quality Indicators

Byron J. GajewskiRobert H. LeeNancy Dunton

University of Kansas Medical Center

11:45 - 1:15

L U N C H E O NSpeaker:

Nancy L. GellerASA President

Session 5

10:00 -11:30

9:30 - 10:00 B R E A K

Session 4

8:00 -9:30

SPES Invited Session

Estimating Single-Insult FailureProbabilities from Multiple-Insult

Accelerated Tests

Scott Vander WielBrian Weaver

Los Alamos National Laboratory

Robustness & Optimization in DOE

Candidate-List-Free ExchangeAlgorithms for Two-Level Model

Robust Designs

Byran SmuckerMiami University, Ohio

Predictive Analytics

Integrating CART and GeneralizedLinear Models for Improved Process

Understanding

Dana KruegerKansas State University

Douglas C. MontgomeryArizona State University

A Matrix-T Approach to theSequential Design of Optimization

Experiments

Eduardo SantiagoMinitab, Inc.

Applications of Machine Learningin the Semiconductor Industry

Theresa L. UtlautKevin C. Anderson Intel Corporation

Friday, October 14, 2011

55th AnnualFall Technical ConferenceQuality & Statistics - Getting up to Date

REGISTRATION DESK OPENS7:30

CPID Invited Session

I-Optimal Designs for MixtureExperiments with Linear

Inequality Constraints

Christopher M. GotwaltLaura C. LancasterSAS Institute, JMP Division

Technometrics Invited Session

Design and Modeling Strategiesfor Mixture of Mixture

Experiments

William A. BrennemanProctor & Gamble Company

Lulu KangV. Roshan Joseph

Georgia Institute of Technology

SPC Training

Web-Based, Active LearningLaboratories for Teaching

Control Charts

Doug TimmerMiguel Gonzalez

University of Texas -­ Pan American

Connie BorrorDouglas C. MontgomeryArizona State University

Is Your Process REALLYOut-of-Control? Issues withTraditional Control Charting

and Process Capability Statements and their

Resolution

Forrest W. Breyfogle IIISmarter Solutions, Inc.

Simulated Annealing Model Searchfor Subset Selection in Screening

Experiments

Mark A. WoltersUniversity of Western Ontario

Derek BinghamSimon Fraser University

Analysis of High-Frequency Measures of Lateral Vehicular

Control in Healthy andImpaired Populations

Jeffrey D. DawsonUniversity of Iowa

Component-Amount and Mixture-Amount Approaches to

Optiumal Tolerance Allocation

Greg PiepelPacific Northwest National Lab

Cenk OzlerAli Kemal SehirliogluDokuz Eylul University

A Case Study with Mixture-ProcessVariable Models in a Nonlinear

Function

Kevin O’MalleyAnn Giovannitti-­Jensen

Dan HasmanJohn Mullay

Lubrizol Corporation

Moderators

Moderators

Moderators

Paula ReardonElanco/Eli Lilly

Scott GrimshawBrigham Young Univ

David EdwardsVirginia Commonwealth Univ

Brenda BishopUnisys

Brad JonesSAS Institute

Jim SimpsonUS Air Force

Dan ApleyNorthwestern Univ

Fred FaltinThe Faltin Group

Ben AhlstromAmgen

Presentation of WILLIAM G. HUNTER AWARDW. J. YOUDEN MEMORIAL ADDRESS

Speaker: William I. NotzThe Ohio State University

Title of Presentation: “A Tale of Two Cities”

4:00 -­5:00

Session 3

2:00 -­3:30

Design of Experiments for Defect Reduction

Andy SleeperSuccessful Statistics, LLC.

Lou JohnsonMinitab, Inc.

STAT Invited Session

Data Mining for Quality

Richard D. DeVeauxWilliams College

Defect Reduction

Failure Analysis of .50 CaliberM20 API-­T Bullet Burst

David W. StublerTimothy Spears

ATK Lake City Army Ammunition Plant

Space-­Filling Designs& CUSUM

Non-­collapsing Space-­Filling Designs for Bounded Polynomial Regions

Angela DeanSouthamptonUniversity

Danel DraguljicBattelle Memorial Institute

Thomas SantnerThe Ohio State Univ.

12:15 -­ 1:45L U N C H E O N

Speaker:David Hawley

Arabia Steamboat Museum

Session 2

10:30 -­12:00

Q&P Invited Session

The Cautious Use of BayesianMethods in Reliability Analysis

William Q. MeekerIowa State University

Split-­Plot Design

Multiple Objective ParetoFrontier Optimization forSplit-­Plot Exzperiments

Christine M. Anderson-­CookLu Lu

Los Alamos National Laboratory

Timothy J. RobinsonUniversity of Wyoming

Using One-­Factor-­At-­A-­Time LikeExperiments to Build Effective Consulting Relationships

Michael C. MorrowEastman Chemical Company

A Bayesian Hierarchical Power LawProcess Model for Multiple Repairable Systems with

an Application to Supercomputer Reliability

Kenneth J. RyanBowling Green State University

Michael S. HamadaLos Alamos National Laboratory

C. Shane ReeseBrigham Young University

Construction of Balanced Equivalent-­Estimation Second-­Order Split-­Split-­

Plot Designs

Marcus B. PerryFsng Yusn

University of Alabama

10:00 -­ 10:30 B R E A K

WELCOME / PLENARY SESSION“DOE: Is the Future Optimal?”Christopher J. NachtsheimUniversity of Minnesota

8:00 -­9:00

Session 1

9:15 -­10:00

Case Studies

It’s Not Only the Mean ThatMatters in Designed Experiments

Scott C. Sterbenz Ford Motor Company

Split-­Plot Analysis Objective Bayesian Inference ofFixed Effects and Variance

Components in Industrial Split-­Plot ExperimentsShaun S. Wulff University of Wyoming

John F. Brewster University of Manitoba

Profile Monitoring

A Framework of ImplementingStatistical Process Controlon Multiple Profiles

Shing I. ChangShih-­Hsiung Chou

Kansas State University

Thursday, October 13, 2011

55th AnnualFall Technical ConferenceQuality & Statistics -­ Getting up to Date

REGISTRATION DESK OPENS7:00

Effective Consulting

The Future of Statistical Thinking, Statistics, and Statisticians -­-­

Through the Lens of the Deming Philosophy

Jim ClausonBreakthrough Systems

Yuri AdlerVladimir Shper

Moscow Institute of Steel & Alloys

Should you use a CUSUM for Counts and Automatic Design of CUSUMs for

CountsDarwin J. DavisErwin M. Saniga

University of Delaware

Thomas P. McWilliamsDrexel University

James M. LucasJ.M. Lucas and Assoc.

Bayesian Regression Trees

Edward GeorgeUniversity of Pennsylvania

Moderators

Moderators

Moderators Julia O’NeillMerck

Jeff LunarBoeing

Jim LucasJM Lucas & Assoc.

Theresa UtlautIntel Corp.

Dean NeubauerCorning

Ananda JayawardhanaPittsburg State Univ.

Brad JonesSAS Institute

Scott GrimshawBrighsm Young Univ.

Don McCormackSAS Institute