Lubricant analysis as the most useful tool in the proactive maintenance philosophies of machinery and its components

• Autorzy: Kučera Marián , Kopčanová Silvia , Sejkorová Marie

Identyfikatory

DOI

10.2478/mspe-2020-0029

• Języki publikacji: EN

Abstrakty

EN

Condition monitoring and fault diagnosis of engineering systems are critical for the stable and reliable operation in various areas as mobile technology (primarily agricultural, forestry, mining and construction machinery), railways, airlines and large fleets. Thus, to achieve a satisfactory level of reliability for the life of a machine, proactive maintenance strategy is the only key. This means that the application of classical reliability methods suitable for components with sudden failures can be complemented by technical diagnostic methods which have the potential to provide the information about the system condition. In this article we focus on the diagnostic signal related to the used oil – tribodiagnostic measures and is an interesting theoretical item related to the evaluation of the quality of lubricants in the aspect of operation. This is because the oil is in direct contact with single parts of the assessed technical systems. Results tests were reviewed and derived from various parameters of lubricants and their limits that highlight the condition and state of the lubricants under varying categories which include, physiochemical, elemental (wear), contamination and additive analysis.

Słowa kluczowe

EN

engineering system; lubricant condition monitoring; proactive maintenance strategy; used oil analysis program

• Wydawca: STE GROUP
• Czasopismo: Management Systems in Production Engineering
• Rocznik: 2020
• Tom: nr 3 (28)
• Strony: 196--201
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Kučera Marián

• Technical University in Zvolen Faculty of Technology Studentska 26, 960 01 Zvolen, Slovak Republic

autor

Kopčanová Silvia

• Technical University in Zvolen Faculty of Technology Studentska 26, 960 01 Zvolen, Slovak Republic

autor

Sejkorová Marie

• University of Pardubice Studentská 95, 532 10 Pardubice II, Czech Republic

Bibliografia

• [1] Z. Aleš, J. Pavlů, V. Legát, F. Mošna, V. Jurča. “Methodology of overall equipment effectiveness calculation in the context of industry 4.0 environment”. Maintenence and Reliability, vol. 21, no. 3, pp. 411-418, 2019.
• [2] E. Ciulli. “Tribology and Industry: From the Origins to 4.0“. Frontiers in Mechanical Engineering, vol. 5, no. 55, 2019, doi: 10.3389/fmech.2019.00055.
• [3] Y. Du, T. Wu, S. Zhou, V. Makis. Remaining useful life prediction of lubricating oil with dynamic principal component analysis and proportional hazard model. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol. 0, no. 0, pp. 1-8, 2019.
• [4] L. Huang, Y. Chen, S. Chen, H. Jiang. ”Application of RCM analysis based predictive maintenance in nuclear power plants”. In Proc. International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), USA: IEEE, pp.1015-1021, 2012.
• [5] M. Idzior, K. Wichtowska. “Badanie wpływu przebiegu pojazdów na zmiany właściwości olejów silnikowych”. Autobusy – Technika, Eksploatacja, Systemy Transportowe, vol. 17, no. 6, pp. 900-904, 2016.
• [6] A.K.S. Jardine, D. Lin, D. Banjevic. “A review on machinery diagnostics and prognostics implementing conditionbased maintenance“. Mechanical Systems and Signal Processing, vol. 20, pp. 1483-1510, 2006.
• [7] P. Klouda, V. Moni, M. Řehoř, J. Blata, F. Helebrant. ”The Evaluation of a Risk Degree for the Process of a Brown Coal Spontaneuos Ignition on Dumps with Using of Modern Numeric Methods”. Management Systems in Production Engineering, vol. 26, no. 2, pp. 71-75, 2018.
• [8] J. Kral Jr., B. Konecny, J. Kral, K. Madac, G. Fedorko, V. Molnar. “Degradation and chemical change of longlife oils following intensive use in automobile engines”. Measurement, vol. 50, pp. 34-42, 2014.
• [9] A. Kumar, S.K. Ghosh. “Size distribution analysis of wear particles in the transmission system of mining equipment”. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol. 232, no. 8, pp. 921-926, 2018.
• [10] U. Kumar, D. Galar, A. Parida, Ch. Stenström, L. Berges.“ Maintenance performance metrics: a state-of-the-art review“. Journal of Quality in Maintenance Engineering, vol. 19, no. 3, pp. 233-277, 2013.
• [11] J. Lee, F. Wu, W. Zhao, M. Ghaffari, L. Liao, D. Siegel. “Prognostics and health management design for rotary machinery systems – Reviews, methodology and applications“. Mechanical Systems and Signal Processing, vol. 42, pp. 314-334, 2014.
• [12] R. Majdan, R. Abrahám, D. Uhrinová, J. Nosian. “Contamination of transmission and hydraulic oils in agricultural tractors and proposal of by-pass filtration system“. Agronomy research, vol. 17(S1), pp. 1107-1122, 2019.
• [13] L.V. Markova. ”Intelligent method for monitoring the state of lubricating oil”. Journal Friction and Wear, vol. 37, no. 4, pp. 308-314, 2016.
• [14] Y. Peng, M. Dong, M.J. Zuo. “Current status of machine prognostics in condition-based maintenance: a review“. International Journal of Advanced Manufacturing Technology, vol. 50, pp. 297-313, 2010.
• [15] M. Rakyta, M. Fusko, J. Herčko, Ľ. Závodská, N. Zrnić. “Proactive approach to smart maintenance and logistics as a auxiliary and service processes in a company”. Journal of Applied Engineering Science, vol.14, no. 4, pp. 433-442, 2016.
• [16] H. Raposo, J. T. Farinha, I. Fonseca, D. Galar. “ Predicting condition based on oil analysis – A case study“. Tribology International, vol. 135, pp. 65-74, 2019.
• [17] M. Sejkorová, B. Šarkan, J. Caban, A. Marczuk. “O zależności widm w podczerwieni zużytych olejów silnikowych od ich lepkości kinematycznej”. Przemysł Chemiczny, vol. 97, no. 1, pp. 49-54, 2018.
• [18] J. Turis, P. Beňo, W. Biały. ”The Optimal Tribotechnical Factors in the Design of Machines – Environmental Element in the Production Systems”. Management Systems in Production Engineering, vol. 26, no. 4, pp. 207-211, 2018.
• [19] G.E. Totten. Handbook of Lubrication and Tribology. Volume I: Application and Maintenance, 2nd Edition, Taylor & Francis Group, pp. 1224, 2006.
• [20] P. Ťavoda, J. Kováč, Z. Łukaszczyk. ”Reliability Analysis of Forest Machines due to FMEA Method”. Management Systems in Production Engineering, vol. 26, no. 4, pp. 200-206, 2018.
• [21] D. Vališ, O. Pokora, J. Koláček. ”System failure estimation based on field data and semi-parametric modeling”. Engineering Failure Analysis, vol. 101, pp. 473-484, 2019.
• [22] D. Vališ, L. Žák, O. Pokora, P. Lánský. “Perspective analysis outcomes of selected tribodiagnostic data used as input for condition based maintenance”. Reliability Engineering & System Safety, vol. 145, pp. 231-242, 2016.
• [23] J.M. Wakiru, L. Pintelon, P.N. Muchiri, P.K. Chemweno. “A review on lubricant condition monitoring information analysis for maintenance decision support”. Mechanical Systems and Signal Processing, vol. 118, pp. 108-132, 2019.
• [24] A. Wolak, G. Zajac. ”Changes in the operating characteristics of engine oils: a comparison of the results obtained with the use of two automatic devices”. Measurement, vol. 113, pp. 53-61, 2018.
• [25] J. Zhu, D. He, E. Bechhoefer. “Survey of lubrication oil condition monitoring, diagnostics, and prognostics techniques and systems“. Journal of Chemical Science and Technology, vol. 2, no. 3, pp. 100-115, 2013.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).