Quality and Productivity
JSM Sessions Represent Variety of Topics
J.D. Williams, GE Global Research
T
he 2008 Joint Statistical Meetings will be held in Denver from August 3–7. The Quality and Productivity Section is sponsoring the
following three contributed sessions that represent a broad range of topics to many Q&P members:
Recent Developments in Control Charts and
a Method for Calculating Control Limits for Multiple
Profile Monitoring
Characteristics that are Skewed and/or detection
Monday, August 4, 8:30 a.m.–10:20 a.m.
Limit–Censored, by Robert Brill, ICL Performance
Chair: Willis Jensen, W. L. Gore & Associates
Products, and Thomas J. Bzik, Air Products and
a distribution-Free, Shewhart-type Quality Control
Chemicals Inc.
Chart for detecting a General Change in a Process, by
nonparametric test Families for Highly Censored
Saad T. Bakir, Alabama State University
and/or Skewed data, by Thomas J. Bzik, Air Products
Profile Monitoring for attributes data, by Arthur Yeh,
and Chemicals Inc., and Robert Brill, ICL Performance
Bowling Green State University
Products
Monitoring Profile data: a Likelihood Ratio test
Sequential design for analyses Involving Several
approach, by Junjia Zhu, Pennsylvania State University
types of data, by Christine Anderson-Cook, Todd
Graves, and Michael Hamada, Los Alamos National
diagnostics after a Signal from Control Charts in a
Laboratory
normal Process, by Jianying Lou, Marion R. Reynolds Jr.,
and Dong-Yun Kim, Virginia Tech
Inspection, Capability, and Classification Analysis
CUSUM Charts with Censored Ordinal Categorical
Thursday, August 7, 10:30 a.m.–12:20 p.m.
Chair: Michael Joner, Procter & Gamble
data, by Denisa A. Olteanu, Virginia Tech
deploying Statistical Process Capability approaches for
Control Charts with Missing Observations, by Sara R.
assessing Health Care Revenue-Cycle Management, by
Wilson and Marion R. Reynolds Jr., Virginia Tech
Jason Gillikin, Spectrum Health Hospitals
a Residual-Based Hotelling’s t
2
Chart, by Søren
assessing a Manufacturing Customer’s Complaint
Bisgaard and Xuan Huang, University of Massachusetts
Using Supplier Process data, by Jon M. Lindenauer,
Amherst
Weyerhaeuser
Reliability and Censored Data Analysis Identification and Classification of Intermittent
Wednesday, August 6, 8:30 a.m.–10:20 a.m. demand Patterns, by Jing Chen, Pallavi Chitturi, and
Chair: Huaiyu Ma, GE Global Research Mark Gershon, Temple University
Weekday dependence in Reliability analysis of
Sequential analysis for a Binomial Proportion Using
Repairable Systems, by Alexandre Zolotovitski and
an Imprecise Prior distribution, by Dennis Oberhelman
David C. Trindade, Sun Microsystems Inc.
and Kathleen Whitcomb, University of South Carolina
estimation of Percentage of defective Items in Quality
Supervised texture Classification Using Vector
Control, by Shui-Ching Chang, Overseas Chinese
autoregressive Models, by Martin Heller, North
Institute of Technology, and Tze Fen Li, Ming Dao
Carolina State University
University
effective Choice of test Boundaries for Sequential
Mean Residual of Some discrete distributions, by Syed
testing Based on theory of Continued Fractions,
A. Hossain and Mohammad Ahsanullah, Rider University,
by Yefim H. Michlin, Technion - Israel Institute of
and Syed N. Kirmani, University of Northern Iowa
Technology, and Genady Y. Grabarnik, IBM T. J. Watson
Research Center
estimating Performance degradation Using Intervals
Between Upcrossings of a threshold, by Brock E.
an alternative tolerance Limit for the One-Way
Osborn, GE Global Research; Thomas R. Willemain and
normal Random effects Model, by Shun-Yi Chen,
Pasquale Sullo, Rensselaer Polytechnic Institute; and Hui
Tamkang University n
Fan, Moody’s Investors Services
JUNE 2008 AMSTAT NEWS 43
Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76