Manufacturing Technology 2021, 21(5):605-615 | DOI: 10.21062/mft.2021.076

Weibull’s analysis of the dependability of critical components of selected agricutural machinery

David Fabiánek ORCID..., Václav Legát ORCID..., Zdeněk Aleš ORCID...
Faculty of Engineering, Czech University of Life Sciences Prague, Department for Quality and Dependability of Machines, Kamýcká 129, 165 21 Prague 6 – Suchdol, Czech Republic

The aim of this paper is an analysis of the dependability of critical components of the John Deer 7530 tractor. For this analysis data was used from a database which contains maintenance data of 166 trac-tors during approx 9 years. The first part of this article is devoted to the selection of critical compo-nents based on number of failures of individual machine parts for a given period and their sales pric-es. The next part of article presents data for calculation dependability indicators which contains oper-ating times to failure and operating times without failure. Due to the large size of the data files of the individual components, the data are only given for one machine component. Furthermore, the meth-od of calculation of dependability indicators is described by parametric statistical methods according to ČSN EN 61649:2009 and mean time to operating failure. The results of the analysis are summa-rized in tables and graphs. The method in this article can be used to optimise the maintenance pro-gram.

Keywords: Dependability, Weibull distribution, Agriculture, Tractor

Received: April 4, 2021; Revised: July 2, 2021; Accepted: August 27, 2021; Prepublished online: October 21, 2021; Published: November 25, 2021  Show citation

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Fabiánek D, Legát V, Aleš Z. Weibull’s analysis of the dependability of critical components of selected agricutural machinery. Manufacturing Technology. 2021;21(5):605-615. doi: 10.21062/mft.2021.076.
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    References

    1. ELMOSELHY, S., (2013). Hybrid lean-agile manufacturing system technical facet, in automotive sector. In: Journal of Manufacturing Systems, Vol. 32, No. 4, pp. 598-619. Go to original source...
    2. EGILMEZ, G., ERENAY, B., SÜER, G., (2014). Stochastic skill-based manpower allocation in a cellular manufacturing system. In: Journal of Manufacturing Systems, Vol. 33, No 4, pp. 578-588. https://doi.org/10.1016/j.jmsy.2014.05.005. Go to original source...
    3. LEGAT, V. (2009). Asset management - a modern way to better maintenance and use of property. In: Proceedings of the International Professional Conference Central European Maintenance Forum 2009. ČZU, Prague. ISBN 978-80-213-1999-8.
    4. LEGAT, V. (2013). Management and maintenance engineering. Professional Publishing,
    5. DOMINIK, V., VOTAVA, Z. (2016). Maintenance performance is a source of competitive advantage.
    6. LOGANATHAN, M., GANDHI, K. (2016). Maintenance cost minimization of manufacturing systems using PSO under reliability constraint. In: International Journal of System Assurance Engineering and Management, Vol. 7, No 1, pp. 47-61. doi:10.1007/s13198-015-0374-2. Go to original source...
    7. LEGAT, V., MOSNA, F., CERVENKA, V., JURCA, V. (2002). Optimization of preventive maintenance and information system. In: Maintenance and Reliability, Vol. 4, No. 16, pp. 24-29.
    8. LEGAT, V., ZALUDOVA, A., CERVENKA, V., JURCA, V. (1996). Contribution to optimization of preventive replacement. In: Reliability Engineering and System Safety, Vol. 51, No. 3, pp. 259-266. doi:10.1016/0951-8320(96)00124-X. Go to original source...
    9. SHERIF, Y. (1982) Optimal maintenance schedules of systems subject to stochastic failure. In: Microelectronics Reliability, Vol. 22, No. 1, pp. 15-29. doi:10.1016/0026-2714(82)90047-6. Go to original source...
    10. BARLOW, R., PROSCHAN, F. (1965). Mathematical Theory of Reliability.
    11. BURDUK, A., CHLEBUS, E. (2009). Evaluation of the risk in production systems with a parallel reliability structure. In: Maintenance and Reliability, Vol. 2, pp. 84-95.
    12. JURCA, V., HLADIK, T., ALES Z. (2008). Optimization of preventive maintenance intervals. In: Maintenance and Reliability, Vol. 3, pp. 41-44.
    13. ALES, Z., LEGAT, V. (2016). Determination of parameters Weibull of probability density function in MS Excel. In: Weibull distribution of random variables: Materials from the 64th seminar of the expert group on reliability, pp. 17-28.
    14. GOLMAKANI, H., FATTAHIPOUR, F. (2011). Age-based inspection scheme for condition-based maintenance. In: Journal of Quality in Maintenance Engineering, Vol. 17, No. 1, pp. 93-110. doi:10.1108/13552511111116277. Go to original source...
    15. LI, X., JIA, Y., WANG, P., ZHAO, J. (2015). Renewable warranty policy for multiple-failure-mode product considering different maintenance options. In: Maintenance and Reliability, Vol. 17, No. 4, pp. 551-560. doi:10.17531/ein.2015.4.10. Go to original source...
    16. ZARETALAB, A., HAGHIGHI, S., MANSOUR, S., SAJADIEH, M. (2020) An integrated stochastic model to optimize the machining condition and tool maintenance policy in the multi-pass and multi-stage machining. In: International Journal of Computer Integrated Manufacturing, Vol. 33, No. 3, pp. 211-228. doi:10.1080/0951192X.2020.1718764. Go to original source...
    17. STENSTRÖM, C., NORRBIN, p., PARIDA, A., KUMAR, U. (2016) Preventive and corrective maintenance - cost comparison and cost-benefit analysis. In: Structure and Infrastructure Engineering; Vol. 12, No. 5, pp. 603-61. doi:10.1080/15732479.2015.1032983. Go to original source...
    18. CSN EN 61649 (010653). (2009). Weibull analysis (In Czech).
    19. LEGAT, V., MOSNA, F., ALES, Z., JURCA, V. (2017) Preventive Maintenance Models - Higher Operational Reliability. In: Maintenance and Reliability; Vol. 19, No. 1, pp. 134-141. Go to original source...
    20. MICHALKOVÁ, P., LEGAT, V., ALES, Z. (2018) Dependability analysis of the injection press using Weibull distribution. In: Manufacturing Technology, Vol. 18, No. 4, pp. 625-629. doi:10.21062/ujep/152.2018/a/1213-2489/MT/18/4/625. Go to original source...
    21. LOULOVA, M., SUCHANEK, A., HARUSINEC, J., STRAZOVEC, P. (2018) Analysis of a railway vehicle with unevenness on wheel. In: Manufacturing Technology, Vol. 18, No. 2, pp. 266-272. doi:10.21062/ujep/89.2018/a/1213-2489/MT/18/2/266. Go to original source...

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