Estimation of fluctuations in the performance indicators of equipment that operates under conditions of unstable loading

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.123367

Keywords:

wear of equipment, equipment replacement, efficiency of equipment operation, stability of performance indicators

Abstract

Abstracts

The dynamic model of change in the performance indicators of sophisticated equipment was proposed. The proposed model consists of two parts. The first part concerns modeling of a random process of changes in the level of equipment loading and is described by the stochastic equation in the form of Ito (5). The second part concerns modeling of dynamics of equipment wear depending on changing in the levels of its loading and is described by the differential equation. As a result, the stochastic dynamic model of changes in performance indicators of sophisticated equipment, which takes into account random fluctuations of equipment loading, was obtained. Using the proposed model, we analyzed dynamics of average total specific costs of equipment in the case when a degree of equipment loading is subject to random changes. Quantitative ratios of average total specific costs of equipment, level of fluctuations of these costs during possible random changes in loading and terms of equipment replacement were established. Studies have demonstrated that changes in average total specific costs of equipment can be insignificant for a certain time. In this case, the spread range of the level of costs of equipment within the same time range can increase significantly. That is why it makes sense to reduce the service term of equipment. This would lead to an insignificant increase in the mean values of equipment performance indicators, however, their stability level will improve considerably.

Author Biographies

Inna Lapkina, Odessa National Maritime University Mechnikova str., 34, Odessa, Ukraine, 65029

Doctor of Economic Sciences, Professor, Head of Department

Department of management of logistics systems and projects

Mykola Malaksiano, Odessa National Maritime University Mechnikova str., 34, Odessa, Ukraine, 65029

PhD, Associate Professor

Department of management of logistics systems and projects

References

  1. Marston, A., Winfrey, R., Hempstead, J. C. (1975). Engineering valuation and depreciation. Iowa State University Press, 508.
  2. Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139 (3), 469–489. doi: 10.1016/s0377-2217(01)00197-7
  3. Kamien, M. I., Schwartz, N. L. (1971). Optimal Maintenance and Sale Age for a Machine Subject to Failure. Management Science, 17 (8), B–495–B–504. doi: 10.1287/mnsc.17.8.b495
  4. Zhao, X., Qian, C., Nakagawa, T. (2017). Comparisons of replacement policies with periodic times and repair numbers. Reliability Engineering & System Safety, 168, 161–170. doi: 10.1016/j.ress.2017.05.015
  5. Tsang, A. H. C., Yeung, W. K., Jardine, A. K. S., Leung, B. P. K. (2006). Data management for CBM optimization. Journal of Quality in Maintenance Engineering, 12 (1), 37–51. doi: 10.1108/13552510610654529
  6. Malaksiano, N. A. (2012). On the stability of economic indicators of complex port equipment usage. Actual Problems of Economics, 12, 226–233.
  7. Dogramaci, A., Fraiman, N. M. (2004). Replacement Decisions with Maintenance Under Uncertainty: An Imbedded Optimal Control Model. Operations Research, 52 (5), 785–794. doi: 10.1287/opre.1040.0133
  8. Bensoussan, A., Feng, Q., Sethi, S. P. (2015). Integrating equipment investment strategy with maintenance operations under uncertain failures. Annals of Operations Research, 1–34. doi: 10.1007/s10479-015-1862-0
  9. Bensoussan, A., Sethi, S. P. (2007). The Machine Maintenance and Sale Age Model of Kamien and Schwartz Revisited. Management Science, 53 (12), 1964–1976. doi: 10.1287/mnsc.1060.0666
  10. Yatsenko, Y., Hritonenko, N. (2008). Properties of optimal service life under technological change. International Journal of Production Economics, 114 (1), 230–238. doi: 10.1016/j.ijpe.2008.02.008
  11. Lapkina, I. O., Malaksiano, M. O., Malaksiano, M. O. (2016). Optimization of the structure of sea port equipment fleet under unbalanced load. Actual Problems of Economics, 9, 364–371.
  12. Lapkina, I. O., Malaksiano, M. O. (2016). Modelling and optimization of perishable cargo delivery system through Odesa port. Actual Problems of Economics, 3, 353–365.
  13. Apeland, S., Scarf, P. A. (2003). A fully subjective approach to capital equipment replacement. Journal of the Operational Research Society, 54 (4), 371–378. doi: 10.1057/palgrave.jors.2601505
  14. Øksendal, B. (2014). Stochastic Differential Equations: An Introduction with Applications. Springer, 379.
  15. Malaksiano, M. O. (2012). On the optimal repairs and retirement terms planning for complex port equipment when forecast level of employment is uncertain. Economic Cybernetics, 4-6 (76-78), 49–56.
  16. Volkov, I. K., Zuyev, S. M., Tsvetkova, G. M. (2006). Sluchaynye processy. Moscow: MGTU im. N. E. Baumana, 448.
  17. Jardine, A., Tsang, A. (2013). Maintenance, Replacement, and Reliability, Theory and Applications. CRC Press, 364.

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Published

2018-02-13

How to Cite

Lapkina, I., & Malaksiano, M. (2018). Estimation of fluctuations in the performance indicators of equipment that operates under conditions of unstable loading. Eastern-European Journal of Enterprise Technologies, 1(3 (91), 22–29. https://doi.org/10.15587/1729-4061.2018.123367

Issue

Section

Control processes