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Virginia Tech

Statistical Methods for Non-Linear Profile Monitoring

Abstract

dc:description.abstract

We have seen an increased interest and extensive research in the monitoring of a process over time whose characteristics are represented mathematically in functional forms such as profiles. Most of the current techniques require all of the data for each profile to determine the state of the process. Thus, quality engineers from industrial processes such as agricultural, aquacultural, and chemical cannot make process corrections to the current profile that are essential for correcting their processes at an early stage. In addition, the focus of most of the current techniques is on the statistical significance of the parameters or features of the model instead of the practical significance, which often relates to the actual quality characteristic. The goal of this research is to provide alternatives to address these two main concerns. First, we study the use of a Shewhart type control chart to monitor within profiles, where the central line is the predictive mean profile and the control limits are formed based on the prediction band. Second, we study a statistic based on a non-linear mixed model recognizing that the model leads to correlations among the estimated parameters.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Statistics
Department dc:contributor.department
Statistics
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Quevedo Candela, Ana Valeria
Chair dc:contributor.committeechair
  • Vining, G. Geoffrey
Committee members dc:contributor.committeemember
  • Woodall, William H.
  • Gramacy, Robert B.
  • Parker, Peter A.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:23309
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/96265

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Quevedo Candela, Ana Valeria. Statistical Methods for Non-Linear Profile Monitoring. doctoral thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/96265