Date on Master's Thesis/Doctoral Dissertation

5-2024

Document Type

Doctoral Dissertation

Degree Name

Ph. D.

Department

Civil and Environmental Engineering

Degree Program

Civil Engineering, PhD

Committee Chair

McGinley, William Mark

Committee Co-Chair (if applicable)

Druffel, Thad

Committee Member

Druffel, Thad

Committee Member

Sun, Zhihui

Committee Member

Kim, Young

Author's Keywords

Smart manufacturing of cement; rotary kiln; energy and process optimization; COMSOL multiphysics simulation; clinker quality predictive models; cement and clinker

Abstract

Cement kilns are controlled by experienced process operators who follow experience-based industry guidelines using data collected and fundamental knowledge. The manufacturing process, which is equipped with sensors and equipment, transfers data/information to the operators to aid standardized decision-making operations. In contrast, companies have used such data to develop and implement digital solutions for predictive control systems; in effect, FLSmidth and Rockwell Automation. However, despite the availability of automated control systems and investigation in automation for process monitoring and optimization, opportunities to radically optimize cement manufacturing are still abundant and in need of implementation. Therefore, this research developed simulation models and designed and built a lab-scale rotary kiln, to better understand the kilning process and provide easier access to testing. In addition, a digital integrated smart manufacturing solution was developed to reduce energy demand and CO2 emissions, while preserving or improving clinker quality. This work integrated academic and industry research in an effort to optimize energy consumption in the clinker-making process. It comprises three main components: (I) development of multiphysics simulations of cement rotary kilns, (II) design, construction, validation, and testing of laboratory-scale rotary kiln, and (III) development and deployment of predictive models and a Smart Manufacturing Tool in a cement plant. Key deliverables of this research consisted of (a) simulations of laboratory and full-scale rotary kilns, (b) a lab-scale rotary kiln, (c) a Smart Manufacturing (SM) tool to predict energy consumption and clinker quality in the cement kilning process as well as to advice on kiln operation for optimized energy consumption.

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