Smriti Neogi

Graduation Semester and Year

2014

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Industrial Engineering

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Li Zeng

Abstract

This research develops statistical methods for quality monitoring in complex systems. Quality monitoring typically consists of two phases called Phase I analysis (or offline monitoring) and Phase II analysis (or online monitoring). This research is focused on Phase I monitoring. Two application areas are considered, complex manufacturing processes and healthcare delivery processes. In the first application, a robust strategy for Phase I analysis of optical profiles in low-E glass manufacturing is developed. The proposed approach aims to solve the problems such as violation of normality, high dimensionality, detection of multiple change points, etc. It will provide a convenient process monitoring tool for practitioners in the low-E glass industry. In the second application, a systematic methodology for Phase I monitoring of patient readmission is developed. Patient readmission is a critical contributor to the rising health care costs and has become an important performance indicator for assessing and monitoring quality of care. This work consists of two parts: construction of readmission model and change detection based on the constructed model. The proposed approach is demonstrated using real data from chronic obstructive pulmonary diseases (COPD) patients.

Disciplines

Engineering | Operations Research, Systems Engineering and Industrial Engineering

Comments

Degree granted by The University of Texas at Arlington

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