Chemical and Biological Engineering ETDs

Publication Date

Spring 5-16-2026

Abstract

To meet the stewardship and modernization initiatives set by the Department of Energy new technologies must enter the manufacturing facilities within the nuclear deterrent complex. Predictive solutions begin with collecting data. An equipment health monitoring device was created to streamline data collection and organization for equipment and processes. A predictive and process performance dashboard was developed for a deionized water system. The dashboard used Western Electric statistical process rules and a machine learning regression algorithm to predict when the resistivity would fall out of specification. Lastly, a remaining useful life calculation was developed for all equipment related to nuclear deterrent production. Its development led to an organized dataset for future procurement prioritization for production related equipment. These studies help lay foundational knowledge in modernizing the production capabilities of the nuclear deterrent complex.

Keywords

Smart Factory, Process Performance, Predictive Maintenance

Document Type

Dissertation

Language

English

Degree Name

Chemical Engineering

Level of Degree

Doctoral

Department Name

Chemical and Biological Engineering

First Committee Member (Chair)

Heather Canavan

Second Committee Member

Steven Woodall

Third Committee Member

Trilce Estrada

Fourth Committee Member

Darryl Dickerson

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