Increasing the efficiency of pre-painting technology of car bodies using the model formation of surface cleaning quality
https://doi.org/10.46973/0201-727X_2024_1_15
Abstract
The results of research on improving the process of pre-painting preparation of car bodies based on modeling the cleaning process and the formation of surface quality are presented. The work carried out a study of the physical and mechanical properties of operational contaminant media located on the body part of the rolling stock that accepted for repair. The results showed that most types of contaminants can be correlated on the Mohs hardness scale with known materials, which greatly facilitates their study. Based on the data obtained, the article proposes a model for cleaning and forming the quality of pre-painting surface preparation, used before applying the paint and varnish coating. The model has practical application in the form of specific technological processing modes given in this paper.
About the Authors
A. A. Kulkov
Russian University of Transport (RUT MIIT)
Russian Federation
Russian Federation
Anatoly Alexandrovich Kulkov, Candidate of Engineering Sciences, Associate Professor
Chair «Technology of Transport Engineering and Repair of Rolling Stock»
Moscow
A. S. Shinkaruk
Russian University of Transport (RUT MIIT)
Russian Federation
Russian Federation
Andrey Sergeyevich Shinkaruk, Candidate of Engineering Sciences
Chair «Technology of Transport Engineering and Repair of Rolling Stock»
Moscow
R. H. Rafikov
Russian University of Transport (RUT MIIT)
Russian Federation
Russian Federation
Rafik Haidarovich Rafikov, Candidate of Engineering Sciences
Chair «Technology of Transport Engineering and Repair of Rolling Stock»
Moscow
References
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Review
For citations:
Kulkov A.A., Shinkaruk A.S., Rafikov R.H. Increasing the efficiency of pre-painting technology of car bodies using the model formation of surface cleaning quality. Vestnik Rostovskogo Gosudarstvennogo Universiteta Putej Soobshcheniya. 2024;(1):15-21. (In Russ.) https://doi.org/10.46973/0201-727X_2024_1_15
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