Degree Type

Honors Capstone Project

Date of Submission

Spring 5-1-2008

Capstone Advisor

John C. Heydweiller

Honors Reader

George C. Martin

Capstone Major

Biomedical and Chemical Engineering

Capstone College

Engineering and Computer Science

Audio/Visual Component

no

Capstone Prize Winner

no

Won Capstone Funding

no

Honors Categories

Sciences and Engineering

Subject Categories

Chemical Engineering | Other Chemical Engineering

Abstract

The successful design of multipurpose process plants, which are characterized by their flexibility, is accomplished by maximizing the availability of process units and therefore, the profitability of the process. Maximum availability is achieved through the optimization of the design and production scheduling of a process under constraints relating to equipment maintenance and failure. Mathematical models that incorporate the production scheduling, maintenance scheduling, process design and initial reliability aspects of a process can be optimized in order to maximize availability. These mathematical models are solved through the use of computers. Mathematical process models, presented in the literature and containing the aforementioned components, were replicated and analyzed in this research; the simplest was replicated first and additional complexity was added thereafter. The last model replicated from the literature, the one containing the initial reliability component, is revised and improved. Specifically, the mathematics of the model are altered and simplified. Analysis reveals that as the models became more complex the harder it was to replicate the results provided in the literature. However, the revisionist model significantly improved upon the literature initial reliability model; it was solved faster and with greater accuracy. At the beginning of this report, a review of the mathematical and theoretical framework for this type of process optimization research is provided. The models of the multipurpose process plants are formulated as mixed-integer linear programming (MILP) problems in the General Algebraic Modeling System and solved using the XPRESS and CPLEX solvers.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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