AISTech 2024, Columbus, Ohio (USA)
Optimizing Supply Chain Scheduling in Steel Mills: An Algorithm Leveraging Digital Twin Technology
A heuristic algorithm inside a digital twin that schedules steelmaking and continuous casting, increasing monthly production by 1% with no infrastructure investment.
Industrial application (Integrated scheduling of the steelmaking chain)
In a complex mill, scheduling one stage runs into the technical, technological and financial limits of the others. The paper schedules the mill with a Digital Twin that anticipates bottlenecks.
From the mathematical concept to the business gain
- Nonlinear constraints
- Real process limits enter the model as they are, without simplifications that would produce plans the operation cannot run.
- Heuristic inside the Digital Twin
- The twin anticipates bottlenecks, and the algorithm schedules production to work around them.
- Resource allocation across the chain
- The same plan seeks more steel output, fewer delays and better use of supply chain resources.
Result: In a real mill: 1% more monthly output, with no infrastructure investment.
Enacom executive summary, based on the paper and the related projects.
Abstract
This paper presents a heuristic algorithm developed within a digital twin system to optimize scheduling in a complex steelmaking plant. The digital twin provides insights and anticipates bottlenecks, contributing to efficient scheduling. The algorithm addresses non-linear constraints arising from technical, technological, and financial limitations, ensuring a customized approach to production planning. The optimized scheduling aims to enhance steel production, minimize delays, and maximize resource allocation within the supply chain. By leveraging mathematical optimization and digital twin technology, this innovative solution achieved significant gains in a real steel mill industry, increasing monthly production by 1% without the need for infrastructure investment.
Original abstract, published in English.
Keywords
Steel productionDigital twinOptimizationScheduling
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