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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/29630
Title: A PRACTICAL SCHEDULING APPROACH FOR THE STEEL-MAKING PROCESS
Authors: Ryota, Tamura
Advisor: Christopher L.E., Swartz
Department: Chemical Engineering
Keywords: Optimal scheduling for steel-making process
Publication Date: 2023
Abstract: This thesis presents a review of optimal production scheduling in the steel industry. Steel production encompasses various processes, such as the ‘’Blast Furnace’’ and ‘’Hot-Rolled Steel Sheets Mill’’. However, this thesis specifically focuses on the steel making process due to its intermediate nature and substantial influence on profits and costs. \\\\This paper presents a MILP scheduling method to tackle practical steel scheduling problems. The scheduling of steel process poses a significant challenge due to complicated constraints and machine rules, making it a time-consuming task to obtain an optimal solution. To address this problem, a strategy has been proposed to break down the huge and complex problem into smaller sub-problems. The foundational concept behind this approach was initially introduced by Harjunkoski and Grossmann (2001). However, further improvements are proposed in this thesis by introducing a more flexible model for process and grading selections, tailored to practical steel scheduling problems. The thesis presents a strategy to obtain optimal steel making process scheduling by using a MILP approach. In addition, this thesis shows an optimal steel making process scheduling under processing time uncertainty. Uncertain processing time can have great impact the schedule accuracy. To tackle with this problem, a stochastic scheduling model is represented. Moreover, this thesis illustrates an improvement to generate a practical scheduling of steel making process by making use of real processing time data. To validate the effectiveness of our proposed methods, we provide a small example for each step of the scheduling process. The results demonstrate that our approach yields reasonable scheduling solutions.
URI: http://hdl.handle.net/11375/29630
Appears in Collections:Open Access Dissertations and Theses

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