JSM 2004 - Toronto

Abstract #301261

This is the preliminary program for the 2004 Joint Statistical Meetings in Toronto, Canada. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2004); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2004 Program page
Activity Number: 314
Type: Contributed
Date/Time: Wednesday, August 11, 2004 : 9:00 AM to 10:50 AM
Sponsor: Section on Quality and Productivity
Abstract - #301261
Title: Monitoring Industrial Generation of Electricity Using Multivariate Statistical Procedures
Author(s): Robert L. Mason and Joe H. Sullivan and Zachary G. Stoumbos and John C. Young*+
Companies: Southwest Research Institute and Mississippi State University and Rutgers University and McNeese State University
Address: , Lake Charles, LA, 70609,
Keywords: autocorrelation ; Hotelling's T-Square ; multivariate statistical process control ; regression analysis
Abstract:

Large industrial operations often use several forms of energy, such as electricity and steam, in their production processes. The most popular unit systems for the internal powerhouse generation of electricity are the steam turbine, the gas turbine, and a cogeneration combine cycle configuration using both steam and gas turbines. We present a case study for the problem of monitoring the overall powerhouse performance, including monitoring the energy conversion efficiency of a turbine unit. We also statistically assign the load among the various units in such a way as to minimize the fuel usages. The statistical procedures used in this case study include multivariate statistical process control methods based on the application of Hotelling's T-Square statistic, multivariable techniques such as regression analysis, and time-series modeling of a nonlinear mean response with autocorrelation.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2004 program

JSM 2004 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2004