Energy-Efficient Integration Optimization of Production Scheduling and Ladle Dispatching in Steelmaking Plants

Han, Dayong; Tang, Qiuhua; Cao, Jun

doi:10.1109/access.2020.3027018

Cited by 12 publications

(12 citation statements)

References 43 publications

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“…Wang [74] carried out effective process planning and production scheduling optimization from both process and system stages and applied artificial neural networks to achieve multi-objective optimization, providing an effective sustainable development example for enterprises. Han et al [75] constructed an energy-saving integrated model by combining production scheduling and ladle scheduling in the steel industry. They fully considered the time dependence of the two scheduling decisions and designed an enhanced migrating birds optimization algorithm for a high-quality solution to achieve effective energy saving.…”

Section: Energy-target-based Schedulingmentioning

confidence: 99%

Operation and Maintenance Optimization for Manufacturing Systems with Energy Management

Xia

et al. 2022

Energies

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With the increasing attention paid to sustainable development around the world, improving energy efficiency and applying effective means of energy saving have gradually received worldwide attention. As the largest energy consumers, manufacturing industries are also inevitably facing pressures on energy optimization evolution from both governments and competitors. The rational optimization of energy consumption in industrial operation activities can significantly improve the sustainability level of the company. Among these enterprise activities, operation and maintenance (O&M) of manufacturing systems are considered to have the most prospects for energy optimization. The diversity of O&M activities and system structures also expands the research space for it. However, the energy consumption optimization of manufacturing systems faces several challenges: the dynamics of manufacturing activities, the complexity of system structures, and the diverse interpretation of energy-optimization definitions. To address these issues, we review the existing O&M optimization approaches with energy management and divide them into several operation levels. This paper addresses current research development on O&M optimization with energy-management considerations from single-machine, production-line, factory, and supply-chain levels. Finally, it discusses recent research trends in O&M optimization with energy-management considerations in manufacturing systems.

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Section: Energy-target-based Schedulingmentioning

confidence: 99%

Operation and Maintenance Optimization for Manufacturing Systems with Energy Management

Xia

et al. 2022

Energies

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“…costs for the mixers starts represent the start up energy and wear (7). Safe plant behaviour under failure is ensured by existing plant safety systems.…”

Section: Optimal Scheduling Problemmentioning

confidence: 99%

“…An optimization approach for constraint scheduling in steelmaking processes is shown in [5]. Recent papers [6], [7] present mixed integer programming approaches for scheduling parallel industrial processes. Theoretical work on model predictive control for switching process variables and average dwelltimes mostly bases on [8].…”

Section: Introductionmentioning

confidence: 99%

Application of feedback-corrected Optimal Scheduling for Reducing the Energy Consumption of a Mixing Process in Foundry

Rose¹,

Grotjahn²,

Schild

et al. 2021

2021 25th International Conference on System Theory, Control and Computing (ICSTCC)

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We present a feedback-corrected optimal scheduling approach to reduce the demand of electrical energy of batch processes, exemplified at the sand preparation in foundry. The main energy driver in the exemplary foundry is the idle time of the batch-wise working sand mixers. In this novel approach, we use linear integer programming to minimize the demand of energy of the sand mixers by scheduling the batches in real-time. For the optimization we use a physical model of the sand preparation, which takes dwell-times of the processes as dead-time systems into account. In this paper, we present the steps to make the optimal scheduling approach applicable for the production process. The application at the real production plant proves the performance of the suggested approach. Compared to the conventional control, the feedback-corrected optimal scheduling approach leads to an reduction in energy consumption of approximately 6.5 % without modifying the process or the aggregates.

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“…A steel ladle scheduling system integrated system was established [9]. The impact of ladle on steelmaking scheduling was analysed [10]. The operation of ladle and calculated the number of ladles was considered reasonably [11].…”

Section: Introductionmentioning

confidence: 99%

Ladle intelligent re-scheduling method in steelmaking–refining–continuous casting production process based on BP neural network working condition estimation

Liu

Pang

2022

Int J Adv Manuf Technol

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The ladle re-scheduling of steelmaking and continuous casting production aims at continuously casting many charges with the same cast and avoiding conflicts of adjacent charges on the same machine. It proposes a method of ladle re-scheduling in the production process of steelmaking-refining-continuous casting, including two parts: plan re-scheduling and ladle optimisation scheduling. Firstly, a re-scheduling optimisation model of the steelmaking and continuous casting production is built, which aims at minimising the waiting time of all charges. The re-scheduling strategy of steelmaking and continuous casting production is proposed by interval processing time of charges and scheduling expert experience. The re-scheduling strategy is composed of two parts: re-scheduling charge decision and charge processing machine decision. Then, the first-order rule learning is used to select the optimisation target to establish the ladle optimal scheduling model. The ladle matching rules are extracted by the rule reasoning of the minimum general generalisation. The ladle optimisation scheduling method consisting of the optimal selection of the ladle and the preparation of the optimal path of the ladle is proposed. Ladle selection is based on the production process and adopts rule-based reasoning to select decarburised ladle after choosing dephosphorised ladle. Ladle path preparation, a multi-priority heuristic method, is designed to decide the path of the ladle from the converter to the refining furnace to the continuous casting machine. Finally, it was actually verified based on a large-scale steel company in Shanghai, China. Results showed that the production efficiency of steelmaking-refining-continuous casting was improved.

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Energy-Efficient Integration Optimization of Production Scheduling and Ladle Dispatching in Steelmaking Plants

Cited by 12 publications

References 43 publications

Operation and Maintenance Optimization for Manufacturing Systems with Energy Management

Operation and Maintenance Optimization for Manufacturing Systems with Energy Management

Application of feedback-corrected Optimal Scheduling for Reducing the Energy Consumption of a Mixing Process in Foundry

Ladle intelligent re-scheduling method in steelmaking–refining–continuous casting production process based on BP neural network working condition estimation

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