Elaboration of the equipment replacement terms taking into account wear and tear and obsolescence

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.133690

Keywords:

equipment replacement, equipment performance indicators optimization, equivalent annual cost, multi-criteria evaluation

Abstract

The optimum terms of replacement of equipment subject to wear and tear and obsolescence with more advanced equipment with similar performance are investigated. To this end, the methodology of multi-criteria evaluation of equipment performance indicators when switching to a new type of equipment is proposed. The values of EAC (Equivalent Annual Cost), calculated for several equipment replacement cycles and for an infinite number of cycles are investigated. Estimates of the dispersion degree of EAC values depending on the service life of old and new equipment under conditions when the dynamics of operating costs is subject to random fluctuations are obtained. For this, covariance functions of random processes that describe the dynamics of the operating costs of old and new equipment were used. On the basis of covariance functions, estimates of the functions of standard deviations of EAC values are obtained. Using the obtained estimate of the degree of dispersion of equipment performance indicators, the multi-criteria optimization problem was investigated. This approach is of great practical interest, because for many enterprises, not only the average expected level of equipment performance indicators, but also the dispersion degree of the values of these indicators is of great importance. As a result of the research, the technique for planning the equipment replacement terms was developed. The proposed methodology allows justifying the terms of replacement of old equipment with new equipment, taking into account both the average expected EAC values and their level of fluctuations. The studies have shown that due to choosing the equipment renewal terms, it is possible to significantly reduce the degree of dispersion of equipment performance indicators, slightly sacrificing the average expected value.

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. Adkins, R., Paxson, D. (2017). Replacement decisions with multiple stochastic values and depreciation. European Journal of Operational Research, 257 (1), 174–184. doi: 10.1016/j.ejor.2016.07.006
  2. 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. doi: 10.15587/1729-4061.2018.123367
  3. Nahorny, V. V. (2017). Automated control cutting based prediction of individual life of the cutting tool. Radio Electronics, Computer Science, Control, 3, 183–191. doi: 10.15588/1607-3274-2017-3-20
  4. Zaloga, V. A., Nagorniy, V. M., Nagorniy, V. V. (2016). Kontrol' dinamicheskogo sostoyaniya metalloobrabatyvayushchey tekhnologicheskoy sistemy i prognozirovanie ee resursa. Sumy: Sumskiy gosudarstvenniy universitet, 242.
  5. Stutzman, S., Weiland, B., Preckel, P., Wetzstein, M. (2017). Optimal replacement policies for an uncertain rejuvenated asset. International Journal of Production Economics, 185, 21–33. doi: 10.1016/j.ijpe.2016.12.018
  6. Malaksiano, N. A. (2012). On the stability of economic indicators of complex port equipment usage. Actual Problems of Economics, 12, 226–233.
  7. Mihaylov, V. V. (1973). Nadezhnost' elektrosnabzheniya promyshlennyh predpriyatiy. Moscow: Energiya, 168.
  8. Zambujal-Oliveira, J., Duque, J. (2011). Operational asset replacement strategy: A real options approach. European Journal of Operational Research, 210 (2), 318–325. doi: 10.1016/j.ejor.2010.09.011
  9. Liu, B., Wu, J., Xie, M. (2015). Cost analysis for multi-component system with failure interaction under renewing free-replacement warranty. European Journal of Operational Research, 243 (3), 874–882. doi: 10.1016/j.ejor.2015.01.030
  10. 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.
  11. 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.
  12. Hagspiel, V., Huisman, K. J. M., Nunes, C. (2015). Optimal technology adoption when the arrival rate of new technologies changes. European Journal of Operational Research, 243 (3), 897–911. doi: 10.1016/j.ejor.2014.12.024
  13. Adkins, R., Paxson, D. (2013). Deterministic models for premature and postponed replacement. Omega, 41 (6), 1008–1019. doi: 10.1016/j.omega.2013.01.002
  14. Chronopoulos, M., Siddiqui, A. (2014). When is it Better to Wait for a New Version? Optimal Replacement of an Emerging Technology under Uncertainty. Norwegian School of Economics, Department of Business and Management Science. Available at: https://brage.bibsys.no/xmlui/bitstream/handle/11250/217638/1/DiscussionPaper.pdf
  15. Nguyen, T. P. K., Yeung, T. G., Castanier, B. (2013). Optimal maintenance and replacement decisions under technological change with consideration of spare parts inventories. International Journal of Production Economics, 143 (2), 472–477. doi: 10.1016/j.ijpe.2012.12.003
  16. Jones, T. W., Smith, D. (1982). An historical perspective of net present value and equivalent annual cost. Accounting Historians Journal, 9 (1), 103–110. doi: 10.2308/0148-4184.9.1.103
  17. Anderson, B. D. O., Bitmead, R. R., Johnson, C. R., Kokotovic, Jr., P. Y., Kosut, R. L., Mareels, I. M. V., Praly, L., Riedle, B. D. (1986). Stability of adaptive systems: passivity and averaging analysis. MIT Press, 326.
  18. Lutsenko, I. (2016). Definition of efficiency indicator and study of its main function as an optimization criterion. Eastern-European Journal of Enterprise Technologies, 6 (2 (84)), 24–32. doi: 10.15587/1729-4061.2016.85453
  19. Jardine, A., Tsang, A. (2013). Maintenance, Replacement, and Reliability. Theory and Applications. CRC Press, 364. doi: 10.1201/b14937
  20. Volkov, I. K., Zuyev, S. M., Tsvetkova, G. M. (1999). Sluchaynye protsessy. Moscow: Izd-vo MGTU, 448.
  21. Podinovskiy, V. V., Nogin, V. D. (1982). Pareto-optimal'nye resheniya mnogokriterial'nyh zadach. Moscow: Nauka, 256.

Downloads

Published

2018-06-14

How to Cite

Lapkina, I., & Malaksiano, M. (2018). Elaboration of the equipment replacement terms taking into account wear and tear and obsolescence. Eastern-European Journal of Enterprise Technologies, 3(3 (93), 30–39. https://doi.org/10.15587/1729-4061.2018.133690

Issue

Vol. 3 No. 3 (93) (2018): Control processes

Section

Control processes

License

Copyright (c) 2018 Inna Lapkina, Mykola Malaksiano

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.