A Fault Diagnosis and Maintenance Decision System for Production Line Based on Human-machine Multi- Information Fusion

Sun, Poly Z. H.; Liu, Renjun; Ming, Xinguo

doi:10.1145/3299819.3299824

Cited by 9 publications

(8 citation statements)

References 11 publications

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“…As it is only the fusion of two pieces of evidence, it is impossible to judge the quality of the evidence itself by the correlation between the pieces of evidence, so a reasonable probability result should be between these two probability values. However, the probability given by [49] was 0.1285 (see Table 14), which is lower than the two evidences, which we think is unreasonable.…”

Section: Comparative Analysiscontrasting

confidence: 55%

“…In the last decade, the popular AI method has been promoted to provide intelligent methods for the analysis of manufacturing information to improve the effect of decision support. Sun et al [49] presented the machine importance information and machine alarm information of an electronic manufacturing enterprise analyzed by intelligent methods for 10 different machines. Specifically, the objective alarm data were clustered and mapped to the potential failure probability of the machine, and the machine importance was analyzed by the fuzzy method in [49].…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Sun et al [49] presented the machine importance information and machine alarm information of an electronic manufacturing enterprise analyzed by intelligent methods for 10 different machines. Specifically, the objective alarm data were clustered and mapped to the potential failure probability of the machine, and the machine importance was analyzed by the fuzzy method in [49]. Next, we will conduct information fusion for these 10 different machines with our improved D-S evidence and analyze the fusion results.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Moreover, it fully considers the relationship between multiple evidences. In Table 14, we also compare our fusion results with those in [49]. First, the sum of the probabilities of the 10 machines in [49] was not 1, but 0.8631.…”

Section: Comparative Analysismentioning

confidence: 99%

“…In Table 14, we also compare our fusion results with those in [49]. First, the sum of the probabilities of the 10 machines in [49] was not 1, but 0.8631. Therefore, we also give the normalization results of [49].…”

Section: Comparative Analysismentioning

confidence: 99%

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Research on Information Fusion for Machine Potential Fault Operation and Maintenance

Wan

Zuo

et al. 2020

Symmetry

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In recent years, the development of sensor technology in industry has profoundly changed the way of operation and management in manufacturing enterprises. Due to the popularization and promotion of sensors, the maintenance of machines on the production line are also changing from the subjective experience-based machine maintenance to objective data-driven maintenance decision-making. Therefore, more and more data decision model has been developed through AI technology and intelligence algorithms. Equally important, the information fusion between decision results, which got by data decision model, has also received widespread attention. Information fusion is performed on symmetric data structures. The asymmetric data under the symmetric structure leads to the difference in information fusion results. Therefore, fully considering the potential differences of asymmetric data under a symmetric structure is an important content of information fusion. In view of the above, this paper studies how to make information fusion between different decision results through the framework of D-S evidence theory and discusses the deficiency of D-S evidence theory in detail. Based on D-S evidence theory, then a comprehensive evidence method for information fusion is proposed in this paper. We illustrate the rationality and effectiveness of our method through analysis of experiment case. And, this method is applied to a real case from industry. Finally, the irrationality of the traditional D-S method in the comprehensive decision-making results of machine operation and maintenance was solved by our novel method.

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Section: Comparative Analysiscontrasting

confidence: 55%

Section: Problem Descriptionmentioning

confidence: 99%