A Disturbance Dynamic Evaluation Method for Steelmaking-continuous Casting Scheduling Based on Converter Processing Time Prediction and Disturbance Influence Process Analysis

Abstract

Converter completion time delay caused by uncertain events is one of the most frequent disturbances in the steelmaking-continuous casting process (SCCP) with a significant negative impact on the SCCP scheduling. Existing rescheduling methods fall short in providing a comprehensive analysis and evaluation for the production status and disturbance levels, resulting in the scheduling scheme with limited adaptability to on-site environments. This paper addresses this challenge by proposing a dynamic evaluation method for converter scheduling disturbance based on processing time prediction and disturbance influence process analysis. The proposed method consists of three steps that solve the disturbance evaluation problem by predicting the converter processing time, analysing the delay impact of the converter completion time, and solving the real-time procedure buffer capacity. This enables the dynamic scheduling of the SCCP to accurately judge the current operating rhythm and production status, and to achieve precise decision-making for scheduling. Computational experiments based on the actual case from the Chinese steelmaking plants demonstrate the accuracy and effectiveness of the proposed method in large-scale SCCP dynamic scheduling processes. Compared with other methods, the proposed method can effectively reduce the number of rescheduling in production and the deviation of the production process from the initial scheduling scheme by reasonably selecting the scheduling repair strategy, which improves the adaptability of the scheduling scheme to the actual production environment.