Multiscale modeling and collaborative manufacturing for steelmaking plants
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Abstract
With the recent, rapid developments of metallurgical theory and intelligent steelmaking technology, the intelligent upgrading of iron and steel enterprises has attracted increased attention and become a topic of discussion in the steel industry. Collaborative manufacturing is an important feature of intelligent manufacturing in steel enterprises, and it plays an important role in improving the production efficiency and reducing the carbon emissions of iron and steel enterprises. This study elaborated the structure and the contents of multiscale modeling and the collaborative manufacturing of steelmaking plants in detail. The collaborative control of steelmaking plants was studied from the scales of individual processes, workshop sections, and the operation of steelmaking plants. Systematic modeling studies had been conducted from the process control system of processes/devices to the manufacturing execution system (MES). The process control models, including the converter steelmaking process, secondary metallurgy process, and continuous casting process, and mass flow operation optimization models with the production planning and scheduling model as the core were established. In addition, the high-efficiency operation of multi processes/devices was realized through the dynamic coordination of process control and production planning and scheduling in the steelmaking plants. The data interface between process control models, production planning and scheduling models, and MES had been developed to realize the comprehensive integration of MES, production process control, process operation control, production planning, and scheduling system. It had formed the steelmaking-continuous casting process integrated manufacturing technology supported by the precise process control co-driven by mechanism and data models, collaborative process operation, and production planning and scheduling based on “rules + algorithms.” Through multilevel vertical coordination and multiprocess horizontal coordination, the coordinated operation and the control of steelmaking plants were realized. The study results demonstrated a beneficial exploration and the practice of intelligent manufacturing in the steelmaking-continuous casting process, which had strong reference value for intelligent manufacturing enterprises in the process industry, and had a demonstration effect for the green and the intelligent development of the metallurgical industry. After the application, the collaborative manufacturing level of the steelmaking plant had been considerably improved, and significant economic and social benefits had been achieved.
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