Research on the TRF model for states observing and feedback of process production systems
For very long period, most of the research activities in the community have always focused on methods for multiple leveled decisions and optimizations. The aimed issues of these methods ranged from a single process to SCM, as well as goals under EWO that is now catching more and more attentions. Concretely, at the production section, these researches usually pay great efforts for mathematic modeling and/or computing methods for complex operations, such as multi-product and/or multi-purpose planning, scheduling and control optimization. However, few researches have pay attentions at and uncover the important issues about states observing, feedback as well as tracing at plant-wide and/or enterprise-wide, where some real difficult problems have been perplexing the effectiveness and practicability of P-MES (MES for process industry) hitherto. With the guidance under thoughts from EWO, the research presented here is aiming at this nearly neglected challenge that including great practical meanings. In this paper, the complex structure and characteristics of production systems as well as decomposition and aggregation relationships between the production system and computer integrated manufacturing systems (CIMS) are analyzed with the view-angle of multi-scale method. With important concepts employed in this paper, including key feedback parameters (KFP) as well as the fusing and the tracing aggregation of the feedback data/information, a kind of innovative model called TRF(tracking, representing and tracing) model and its key theoretical methods are promoted for production states observing and feedback. Analysis upon these key methods and their modeling mechanisms show that TRF model could effectively response to structural dynamics of the complex production material flows, which is essentially difficult for P-MES using the general model. Based on this proposal, TRF model could construct states observing and feedback mechanism of production systems effectively and efficiently for P-MES in the future.
Extended PSE CIMS P-MES TRF dynamic model modeling methods
ZHU Wei ZHU Feng RONG Gang
State Key Laboratory of Industrial Control Technology, Institute of Cyber-System and Control,Zhejian State Key Laboratory of Industrial Control Technology, Institute of Cyber-System and Control, Zhejia
国内会议
厦门
英文
1-12
2012-08-01（万方平台首次上网日期，不代表论文的发表时间）