| Autor: |
Pudovikov, O. E., Tarasova, V. N., Degtyareva, V. V. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2476 Issue 1, p1-8, 8p |
| Abstrakt: |
The article deals with the essence of the process of predictive diagnosis. Examples are given of existing of the predictive service systems in both industry and rail based on the industrial internet of things. A more detailed study has been made of the predictive diagnostic technologies for the maintenance and repair of traction rolling stock (TPN). A positioning map has been constructed on which existing predictive diagnostic systems for producer characteristics and type of TPNs are drawn. The map makes it possible to decide on a differentiated approach to the implementation of certain predictive diagnostic systems for specific companies. A comparative analysis of the predictive service systems has been carried out on the basis of the eight parameters applied in the process of maintenance and repair of TPNs in motor cars and locomotive depots. Strengths and weaknesses of each system were identified and ranked. The conclusion was reached that there was a need to move from the current maintenance system based on preventive maintenance, which was inefficient, to predictive maintenance and repair of TPNs. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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