Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)

An Auto-Modeling Method for Industrial Systems

Zhong Han, Guicheng Zhang, Lixing Yuan, Shengdun Zhao
Corresponding author
Modeling, Systems engineering, Data structure, Classification set
It is a difficult and valuable research to automatically generate the system model according to some rulers desired. So, a new auto-modeling method for industrial systems is presented. In the research, the industrial system is divided into many individual units, and some mathematical expressions are introduced for building the system model. A series of numbering rules for model nodes are defined in the light of individual unit coupling relationships. A data structure is designed to save the model information, and the saved data information is classified into many groups according to certain ruler and mapped to many classification sets. Next, these classification data in sets is continuously updated and done with by search operation and function calculation again and again. Further, each model elements are all assigned to relevant the layer and the column, and the industrial system model is gotten eventually. Finally, a real example is provided to verify the presented algorithm is feasible and can satisfy purpose requirements of availability, efficiency and accuracy. A layer-column type idea is shown in this algorithm realization, and this entire model is gradually generation. In addition, this algorithm also has a good universality, and can be widely applied into other large-scale manufacturing systems.
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