Online Monitoring of Manufacturing Process Based on autoCEP

Authors

  • Qu Jing Lei Chengdu Inst. of Computer Applications Chinese Academy of Sciences
  • Li Shao bo School of Mechanical Engineering Guizhou University
  • Chen Jing kun School of Computer Science and Technology Guizhou University

DOI:

https://doi.org/10.3991/ijoe.v13i06.6812

Keywords:

Complex Event Processing, Online Monitoring, Manufacturing Process, Association Rule

Abstract


Complex Event Processing (CEP), which can identify patterns of interest from a large number of continuous data steam, is becoming more and more popular in manufacturing process monitoring. CEP rules are specified manually by domain expert, which is a limiting factor for its application in manufacturing enterprises. How to analysis historical data and automatically generate CEP rules is becoming a challenge research. This paper proposed a model of autoCEP for online monitoring in product manufacturing, which can automatically generate CEP rules based on association rules mining in key processes. First, the key quality factors in manufacturing process were extracted by grey entropy correlation analysis. Then, association rules mining method based on product process constraints was used to find the association rules between key factors and product quality. At last, the extracted rules are algorithmically transformed into CEP rules. The experimental results show the effectiveness and practicability of the proposed method.

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Published

2017-06-19

How to Cite

Lei, Q. J., bo, L. S., & kun, C. J. (2017). Online Monitoring of Manufacturing Process Based on autoCEP. International Journal of Online and Biomedical Engineering (iJOE), 13(06), pp. 22–34. https://doi.org/10.3991/ijoe.v13i06.6812

Issue

Vol. 13 No. 06 (2017)

Section

Papers

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