The Role of Statistics in Quality Engineering
Jointly sponsored by:
The Philadelphia Section of ASQ
&
The Engineering Division of the
Penn State Great Valley
School of Graduate Professional Studies
With generous support from the Statistics Division of ASQ
In Celebration of National Quality Month
October 17, 2014
National Quality Month Statistics Symposium
Welcome:
8:45 - 9:00 A.M.
Room 126/127 Main
James Nemes, D.Sc.
Director of Academic Affairs
Penn State Great Valley
Carl Vogel, Chair
Philadelphia Section ASQ
Keynote Address:
9:00 - 10:00 A.M.
Room 126/127 Main
The History of a Research Project
James M. Lucas
Principal, J.M. Lucas and Associates,
Statistics and Quality Management Consultants
I describe how a single observation led to a long term research project studying experiments
with Hard-to-Change and Easy-to-Change Factors.
The observation was that most experiments I had been involved in were not randomized even
though the experimental runs were conducted in a random run order. Randomization requires
that each experimental unit be treated the same way. So for a randomized experiment, a
random run order is necessary, but it is not sufficient to achieve randomization. Resetting of all
experimental factors is also required before randomization is achieved.
I will give an overview of experiments with Hard-to-Change and Easy-to-Change Factors, and
describe recent research and practical applications. I will discuss the contributions of my
students and me, describe personal interactions that occurred with other researchers and journal
editors during this project, and show how they advanced or slowed down scientific progress. I
will discuss the problems and advantages of early disclosure of research results including the
disadvantage of preemption by others and the advantage of faster dissemination of scientific
results. I will describe current research efforts and current applications in this very active area
and tell what problems need to be solved to best help experimenters.
Session I:
Interpreting Experiments
Room 126/127 Main
10:30 - 11:15 A.M.
Are You Crazy?
A 13 Factor Response Surface Experiment on a Production Asset!?!
Jennifer H. Van Mullekom
Senior Consulting Statistician
DuPont’s Applied Statistics Group
Are You Crazy? A 13 Factor Response Surface Experiment on a Production Asset!?! That was
the reaction when a statistical approach was proposed during the product development portion
of the Tyvek® Medical Packaging Transition Project (MPTP). However, the team completed
that experiment and many more at multiple sites.
So, what is the Tyvek® MPTP? DuPont™ Tyvek® Medical Packaging is used to protect sterile
medical devices across the globe. The two highest volume products have been manufactured on
production lines built in the 1960’s since their introduction. The purpose of the Tyvek®
Medical Packaging Transition Project is to create functionally equivalent products on
modernized or “new” production lines that exhibit the same end user properties as the “old”
product made on the lines built in the 1960s.
In order to develop functionally equivalent products, split and strip plot experiments including
9-13 factors were designed across multiple stages of production. This talk will focus on many
aspects of this project including the statistical challenges, the practical challenges, the key
results, and the culture change in the context of the MPTP. Learn more about the Tyvek®
Medical Packaging Transition at www.transition.tyvek.com.
11:30 A.M. - 12:15 P.M.
Process-Oriented Basis Representations for Multivariate SPC
Russell Barton
Professor of Supply Chain and Information Systems and Professor of
Industrial Engineering at the Pennsylvania State University
Senior Associate Dean for research and faculty for the
Smeal College of Business
Many products consist of multiple similar measurements, such as temperatures at multiple
locations or registration errors at multiple locations. Modern process sensors are capable of
making repeated measurements of this sort. Under such conditions, it is possible to produce
process diagnostics analyzing the multivariate process quality vector using a process-oriented
basis. The assumption is that many potential production problems have characteristic
signatures that can be detected in the multivariate quality vector. The representation of the
quality vector using this process-oriented basis is what is known as POBREP. The regressionbased POBREP methodology is presented, along with some examples.
Session II:
Quality Basics
Room 125 Main
10:30 - 11:15 A.M.
Is Your Process Capable of Meeting Specifications?
Michelle Paret
Product Manager
Minitab Inc.
Assessing whether or not a process is capable of meeting internal or customer specifications is
like trying to park your car in a garage: drive too far to the right or the left, and you can say
goodbye to your side-view mirror (or worse). And what if your garage is too narrow to
accommodate your car in the first place?
In this discussion, we will look at how to use capability analysis to calculate relevant statistics
such as Cpk, Ppk and DPMO and evaluate a process relative to specifications to determine if it
fits within the proverbial “garage.” We will also talk about the critical assumptions that must
hold true for the results of a capability analysis to be valid and reliable.
11:30 A.M. - 12:15 P.M.
Beyond the Catapult: Bringing DOE to Life for Service Quality
Professionals
Chris Connors
Lean Six Sigma Master Black Belt, PricewaterhouseCoopers
&
Carl K. Vogel
Quality Systems Engineer & ISO Management Representative,
Johnson Matthey
When it comes to mastering Design of Experiments (DOE), many quality professionals
experience a steep learning curve. DOE can be complex, and to fully understand and apply it,
professionals need to learn when to use it, how to set up the experimental design, and how to
interpret their results.
Service quality professionals face an even greater challenge because they often cannot relate to
the methods many instructors use to teach DOE. Six Sigma trainers typically ask students to
work through non-service related scenarios such using a catapult or a balsa wood airplane,
which can take up to a full training day to execute. Because many of the students believe they
will never apply DOE, they don’t want to spend the class time to learn it, and instructors are
reluctant to make them.
In this workshop attendees will gain a firsthand experience working through a designed
experiment that addresses a relevant quality improvement problem that can be executed fairly
quickly. Using a macro created for Minitab Statistical Software we will follow Montgomery’s
[1] outline for designing an experiment:
1.
2.
3.
4.
5.
6.
7.
Recognition of and statement of the problem.
Choice of factors, levels, and ranges.
Selection of the response variable.
Choice of experimental design.
Performing the experiment.
Statistical analysis of the data.
Conclusions and recommendations
The presentation will cover essential DOE topics such as the scientific method, one factor at a
time experimental approach, DOE terminology (e.g. factors, levels, and response variables),
screening designs, resolution, randomization, replication, ANOVA, residuals, F tests, main
effects and interaction plots.
Speaker Biographies
James M. Lucas
James M. Lucas is the principal at J. M. Lucas and Associates, a
consulting firm in Statistics and Quality Management. This firm
implements business systems with statistical aspects. Before starting
his own consulting firm Lucas was a Senior Consultant at DuPont’s
Quality Management and Technology Center for over twenty years.
He has been an Adjunct Professor at the University of Delaware and at
Drexel University and he has directed six PhD dissertations. He is a
Fellow of the American Statistical Association (ASA) and of the
American Society for Quality (ASQ), an Associate Editor of the
Journal of Quality Technology, and a past Associate Editor of
Chemometrics and Intelligent Laboratory Systems and of Technonetrics.
Lucas is a Past President of the Delaware Chapter of the ASA, a Past Chair of the Chemical and
Process Industries Division of the ASQ. He has been a team leader for the Delaware Quality
Award and a past Chair of the Gordon Research Conference. He has over 60 publications and
many are cited frequently. He authored the most cited paper in two volumes of Technometrics
and in two volumes of the Journal of Quality Technology. He has won many awards including
the Shewhart Medal, the Brumbaugh Award, the H. O. Hartley Award, the Ellis R. Ott
Foundation Award, the Don Owen Award, the Shewell Award, and the Youden Prize.
He has a PhD in Statistics from Texas A&M University, a MS in Statistics from Yale
University, and a BS in Engineering from The Pennsylvania State University.
He can be reached at:
J. M. Lucas and Associates
5120 New Kent Road
Wilmington, DE 19808
Phone: (302) 368-1214
E-mail: JamesM.Lucas@verizon.net
Jennifer H. Van Mullekom
Jennifer H. Van Mullekom is a Senior Consulting Statistician in
DuPont's Applied Statistics Group. She supports the DuPont Protection
Technologies business. She currently provides statistical leadership to
the Tyvek® Medical Packaging Transition Project in the areas of product
development, commercialization, and regulatory. Jen is also a Six Sigma
Master Black Belt and teaches various Six Sigma courses corporately.
She has been actively involved in the ASA's Section on Physical and
Engineering Sciences (SPES) since 1998 and has held various positions
including Publicity Chair and Marquardt Speaker Chair. In 2014 she was
elected Section Chair. She has co-developed the ASA's course on
"Effective Presentations for Statisticians" as a member of past ASA
President Bob Rodriguez's Career Success Factors Task Group. Other contributions to ASA
include JSM presentations and conference committee memberships including the Conference on
Statistical Practice. Jen is a DuPont Associate Fellow. She holds three US Patents and has
worked at Lubrizol and Capital One in addition to DuPont. Her statistical areas of interest
include equivalence testing, regression modeling, response surface designs, and mixed models.
Jennifer received her PhD and MS from Virginia Tech in 1998 and 1995 respectively. She holds
undergraduate degrees from Concord University in Mathematics (1993) and Mathematics
Education (1994).
Russell Barton
Russell Barton is a professor of Supply Chain and Information Systems
and professor of Industrial Engineering at the Pennsylvania State
University. He currently serves as senior associate dean for research and
faculty for the Smeal College of Business. In this role he oversees the
Ph.D. program, research funding and budgets, faculty development, all
academic departments and research centers, and the Office of
International Business. He serves as chair of the advisory board for the
INFORMS Quality, Statistics and Reliability section and as the
INFORMS Simulation Society representative on the INFORMS
Subdivisions Council. He is a senior member of IIE and IEEE. His
research interests include applications of statistical and simulation
methods to system design and to product design, manufacturing and delivery. Russell received a
B.S. degree in Electrical Engineering from Princeton University and M.S. and Ph.D. degrees in
Operations Research from Cornell University, and is a Certified Analytics Professional. Before
entering academia, he spent twelve years in consulting and industry, with over eight years at the
RCA David Sarnoff Research Center.
Michelle Paret
Michelle Paret is a product manager at Minitab Inc., the world’s leading
provider of software and services for quality improvement and statistics
education. Paret is responsible for providing go-to-market strategy, sales
readiness, and marketing readiness for the Minitab Statistical Software
product lines. Paret joined Minitab in 2000 as a member of Minitab’s
highly regarded technical support team, providing statistical support and
guidance to quality practitioners in both manufacturing and service
industries. Paret also served Minitab as a technical training specialist for
four years, working with numerous companies including Boston
Scientific, Pfizer, Nissan, Siemens and Motorola, and was then named
product manager in 2007. Paret earned her B.S and M.S. degrees in
Statistics from The Pennsylvania State University.
Chris Connors
Dr. Chris Connors is Lean Six Sigma Master Black Belt at
PricewaterhouseCoopers (PwC.). He also has an ASQ Six-Sigma Black
Belt certification as well as the ASQ Quality Manager/Organizational
Effectiveness certification. He has a Ph.D. in Industrial/Organizational
Psychology from Temple University. His skills and interests include
Lean Six Sigma, Design of Experiments, Design for Six Sigma, Lean
Manufacturing, Kaizen, Corporate Metrics and Dashboards, Balanced
Scorecards, Leadership Reasoning and Survey Design and Analysis.
Carl K. Vogel, CQSE, CQE
Carl is currently employed by Johnson Matthey Noble Metals, NA as
their Quality Systems Engineer and ISO Management Representative at
the West Whiteland facility. Along with resolving customer issues, he is
assisting in implementing SharePoint throughout Noble Metals multiple
manufacturing sites.His career has gone full circle, from his first job as
an Industrial Engineer on a manufacturing floor, to management, then
software quality and finally, back to working in a manufacturing facility.
The medical components they provide help save people’s lives. Carl’s
undergraduate degree is from Penn State. He is a Senior Member of the
ASQ, and Section Chair of the Philadelphia Section.
Penn State Great Valley
Did you know that U.S. News & World Report’s “America’s Best Engineering Graduate
Schools 2014” ranks Penn State’s College of Engineering 25th in quality among the top
universities—higher than Lehigh University and Drexel University? The Engineering Division
at Penn State Great Valley offers graduate programs in systems engineering, software
engineering, engineering management, and information science. Courses are taught by
distinguished faculty members, who are scholars, consultants, researchers, and practitioners.
The programs are geared toward working professionals and are offered in the evenings in
Malvern and in The Philadelphia Navy Yard. Additionally, Penn State offers 100% online
programs in systems engineering, software engineering, and engineering management. U.S.
News & World Report’s “America’s Best Online Engineering Programs 2014” ranks Penn State
5th in quality nationally. Become part of the Penn State family, where 1 out of 50 engineers in
the United States is a Penn State graduate.
For more information about earning a graduate degree at Penn State Great Valley, please call
610-648-3243, email gvengin@psu.edu or visit http://www.sgps.psu.edu