Production Optimization and Scheduling in a Steel Plant: Hot Rolling Mill

Biondi, Matteo; Saliba, Sleman; Harjunkoski, Iiro

doi:10.3182/20110828-6-it-1002.01157

Cited by 7 publications

(6 citation statements)

References 4 publications

(4 reference statements)

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“…The Hot rolling production and scheduling problem has been studied for several years [2][3][4][5][6][7][8][9][10]. In this section, we conclude the hot rolling planning problem from the aspects of model constraints, optimization objectives and solving algorithms.…”

Section: The Description Of Hot Rolling Planning Problemmentioning

confidence: 99%

Hot-Rolling Planning Based on the Modified Vehicle Routing Problem

Jin

2022

J. Phys.: Conf. Ser.

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With fierce market competition and diversification of customer demand, steel industries are currently facing the challenge of a multi-variety, small-batch, and high-quality production mode. In this study, different constraints, optimization objectives and solving algorithms in hot rolling planning (HRP) are summarized. Considering the particularity of the HRP problem, the vehicle routing problem model was modified, and a corresponding algorithm based on the actual hardness and thickness constraints was designed to solve it. The HRP problem is analysed in detail and solved by Python with an actual production dataset. The developed model has been implemented in a large steel plant, and experimental results show the effectiveness of the proposed model.

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Section: The Description Of Hot Rolling Planning Problemmentioning

confidence: 99%

Hot-Rolling Planning Based on the Modified Vehicle Routing Problem

Jin

2022

J. Phys.: Conf. Ser.

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“…In the last stage (cold casting), the dimensions and the desired mechanical properties are achieved. Biondi et al [114], studied the scheduling problem of a hot rolling mill in a steel plant. Strict production constraints related to metallurgic production were taken into account.…”

Section: Steel Plantsmentioning

confidence: 99%

Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications

2019

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Scheduling is a major component for the efficient operation of the process industries. Especially in the current competitive globalized market, scheduling is of vital importance to most industries, since profit margins are miniscule. Prof. Sargent was one of the first to acknowledge this. His breakthrough contributions paved the way to other researchers to develop optimization-based methods that can address a plethora of process scheduling problems. Despite the plethora of works published by the scientific community, the practical implementation of optimization-based scheduling in industrial real-life applications is limited. In most industries, the optimization of production scheduling is seen as an extremely complex task and most schedulers prefer the use of a simulation-based software or manual decision, which result to suboptimal solutions. This work presents a comprehensive review of the theoretical concepts that emerged in the last 30 years. Moreover, an overview of the contributions that address real-life industrial case studies of process scheduling is illustrated. Finally, the major reasons that impede the application of optimization-based scheduling are critically analyzed and possible remedies are discussed.

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“…Based on simple information regarding the geometry and depending plant parameters, the resulting eddy currents can be determined. The occurring resistance heating leads to a heat flux inside of the object, which can be used to calculate the cross-sectional temperature with the already developed model of Equation (2).…”

Section: Induction-heating System Optimizationmentioning

confidence: 99%

“…Within the steel industry improved through process optimization has been proposed by coupling several processes on a basic (IT) level [2]. This approach has been mainly focused on developing optimization algorithms in detail.…”

Section: Introductionmentioning

confidence: 99%

A CPS-Based Simulation Platform for Long Production Factories

Iannino

Colla

Denker³

et al. 2019

Metals

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Production technology in European steel industry has reached such a level, that significant improvements can only be reached by through process optimization strategies instead of separately improving each process step. Therefore, the connection of suitable technological models to describe process and product behavior, methods to find solutions for typical multi-criterial decisions, and a strong communication between involved plants is necessary. In this work, a virtual simulation platform for the design of cyber-physical production optimization systems for long production facilities focusing on thermal evolution and related material quality is presented. Models for describing physical processes, computers, software and networks as well as methods and algorithms for through process optimization were implemented and merged into a new and comprehensive model-based software architecture. Object-oriented languages are addressed and used because they provide modularity, a high-level of abstraction and constructs that allow direct implementation and usage of the cyber-physical production systems concepts. Simulation results show how the proper connection between models, communication, and optimization methods allows feasibility, safety and benefits of cyber-physical production systems to be established. Furthermore, the software architecture is flexible and general and thus, can be transferred to any steel production line as well as outside the steel industry.

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Production Optimization and Scheduling in a Steel Plant: Hot Rolling Mill

Cited by 7 publications

References 4 publications

Hot-Rolling Planning Based on the Modified Vehicle Routing Problem

Hot-Rolling Planning Based on the Modified Vehicle Routing Problem

Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications

A CPS-Based Simulation Platform for Long Production Factories

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