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. / Thesis / Master of Applied Science (MASc) / In this work, we propose a decomposition strategy for solving practical complex scheduling problems in the steel-making process within a sufficiently short computation time. While there are various processes involved, such as the Cold-Rolled Steel Sheets mill and Steel Pipe mill, we focus on the steel-making process. The optimal scheduling of this process is crucial for increasing profits, reducing waste, and minimizing costs. However, scheduling optimization for the steel-making part presents significant challenges due to complex constraints and specific process rules. To address these challenges, we suggest a decomposition strategy in Chapter 3 of this thesis. This strategy primarily involves breaking down the large and complex scheduling problems into smaller subproblems. While a basic solution strategy is provided in the work of Harjunkoski and Grossmann (2001), our research introduces several improvements tailored to practical scheduling problems. For example, the original paper suggests grouping products together only if they have the same grade. In practical scheduling, however, it is often necessary to mix products of different grades within the same group to maximize productivity and operate efficiently. Additionally, the original paper considers only a single machine for each downstream process. In reality, there are often multiple machines involved in each downstream process. Therefore, our research addresses this challenge by incorporating two refining machines and two continuous casting processes into the scheduling formulations for the downstream process. As a result, the suggestions presented in this paper contribute to handling more flexible patterns of scheduling problems.
In Chapter 3, the formulation is based on the aforementioned idea, and its validation is confirmed through a case study. While the obtained scheduling results may not be optimal, they are reasonable for each step when compared to the perspective of an experienced person. Furthermore, the computational time required for each step is less than 1 minute. As a result, the proposed scheduling strategy can effectively solve practical scheduling problems within a limited time frame. The strategy is specifically designed to incorporate mixed grade grouping, as well as multiple and flexible structures for downstream processes.
In addition, in the steel industry, fluctuation in process time is inevitable because of the high temperature and high-speed conditions to produce products. To address these problems, in Chapter 4, we propose a strategy to incorporate processing time uncertainty into a decomposition strategy. The strategy is based on the two-stage stochastic scheduling formulation. In practical steel industries, there are many preparations before producing the products such as setting a specific condition and maintaining the facilities, and the preparations are based on the scheduling product's order. Therefore, in this formulation, the variables defining the product's order are regarded as the first decision variables to reflect a practical scheduling problem. The formulation is based on this concept, and its validation is confirmed through application to a practical case study. The results are reasonable by comparing to the knowledge of an experienced person. Furthermore, the computational time required for this strategy is also less than 1 minute. Therefore, the strategies presented in this thesis offer an efficient approach for addressing practical steel-making scheduling problems.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29630 |
| Date | January 2023 |
| Creators | Ryota, Tamura |
| Contributors | Christopher L.E., Swartz, Chemical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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