Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.How...Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.However,the stability of product quality in seamless steel tube production is often poor,particularly regarding the mechanical properties of intermediate products,which may not meet the required standards.This results in non-conforming products being unable to smoothly proceed to downstream processes.These issues mainly arise from the compactness of the production process,the characteristics of batch production,and the difficulty in managing order insertion.Consequently,optimizing the production process to minimize the impact of non-conforming products on subsequent processes has become a key challenge in seamless steel tube production.An intelligent reorganization production mechanism is proposed based on the full life cycle of seamless steel tubes,aiming at addressing the scheduling problems of tubes with abnormal performance.The mechanism utilizes a performance anomaly prediction model to detect and forecast potential anomalies in steel tubes,and in conjunction with intelligent scheduling strategies,rearranges the production plan for abnormal tubes.Experimental results demonstrate that the proposed mechanism can effectively improve the detection rate of abnormal tubes,significantly reduce time losses and energy consumption during production,and optimize both production cycles and stability.Specifically,the production cycle was shortened by 52 h,and energy consumption was reduced by approximately 12%.Through the intelligent scheduling model,the production plan was successfully optimized,reducing the production cycle and costs while improving production efficiency.The optimized scheduling scheme saved about 12%in production time,while enhancing the stability of the production plan and capacity utilization.展开更多
基金financially supported by Jiangxi Provincial Key R&D ProgrammeProjects(No.20223BBE51032)National Natural Science Foundation of China(No.52305336)the Opening Project of Guangdong Provincial Key Laboratory for Processing and Forming of Advanced Metallic Materials,South China University of Technology(No.GJ202411).
文摘Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.However,the stability of product quality in seamless steel tube production is often poor,particularly regarding the mechanical properties of intermediate products,which may not meet the required standards.This results in non-conforming products being unable to smoothly proceed to downstream processes.These issues mainly arise from the compactness of the production process,the characteristics of batch production,and the difficulty in managing order insertion.Consequently,optimizing the production process to minimize the impact of non-conforming products on subsequent processes has become a key challenge in seamless steel tube production.An intelligent reorganization production mechanism is proposed based on the full life cycle of seamless steel tubes,aiming at addressing the scheduling problems of tubes with abnormal performance.The mechanism utilizes a performance anomaly prediction model to detect and forecast potential anomalies in steel tubes,and in conjunction with intelligent scheduling strategies,rearranges the production plan for abnormal tubes.Experimental results demonstrate that the proposed mechanism can effectively improve the detection rate of abnormal tubes,significantly reduce time losses and energy consumption during production,and optimize both production cycles and stability.Specifically,the production cycle was shortened by 52 h,and energy consumption was reduced by approximately 12%.Through the intelligent scheduling model,the production plan was successfully optimized,reducing the production cycle and costs while improving production efficiency.The optimized scheduling scheme saved about 12%in production time,while enhancing the stability of the production plan and capacity utilization.
