Have a personal or library account? Click to login
The Design of Forecasting System Used for Prediction of Electro-Motion Spare Parts Demands as an Improving Tool for an Enterprise Management Cover

The Design of Forecasting System Used for Prediction of Electro-Motion Spare Parts Demands as an Improving Tool for an Enterprise Management

Open Access
|Dec 2019

References

  1. [1] J. F. Robeson and W. C. Copacino. The Logistics Handbook, New York, NY: The Free Press, 1994.
  2. [2] Y. Wang and B. Tomlin. “To Wait or Not to Wait: Optimal Ordering Under Lead Time Uncertainty and Forecast Updating”. Naval Research Logistics. vol. 56, pp. 766-779, 2009.10.1002/nav.20381
  3. [3] A. Wieczorek. “Methods and techniques of prediction of key performance indicators for implementation of changes in maintenance organisation”. Management Systems in Production Engineering, vol. 5, pp. 5-9, 2012.
  4. [4] T. Berlec, P. Potocnik, E. Govekar, et al. “Forecasting Lead Times of Production Orders in SME’s”. Iranian Journal of Science and Technology Transaction B-Engineering, vol. 34, pp. 521-538, 2010.
  5. [5] D.J. Bowersox and R.E. Murray. “Logistic Strategic Planning for the 1990’s”, in Fall 1987 Annual Conference Proceedings, 1987, pp. 231-243.
  6. [6] H.R. Keyno-Sadeghi, F. Ghaderi, A. Azade, et al. “Forecasting Electricity Consumption by Clustering Data in Order to Decline the Periodic Variable’s Affects and Simplification the Pattern”. Energy Conversion and Management, vol. 50, pp. 829-836, 2009.10.1016/j.enconman.2008.09.036
  7. [7] X. Zhang and R.Q. Chen. “Forecast-driven or Customer-order-driven? An Empirical Analysis of the Chinese Automotive Industry”. International Journal of Operations & Production Management, vol. 26, pp. 668-688, 2006.10.1108/01443570610666993
  8. [8] S. Giove. “Fuzzy Methods for Complex Systems: Forecasting, Filtering and Control”, in Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), 1997, pp. 162-169.10.1117/12.284210
  9. [9] M. Christopher. Logistics and Supply Chain Management: creating value-added networks. Harlow, UK: Pearson Education Limited, 1998, pp. 83-98.
  10. [10] A. Kelíšek. “Time Series Analysis by Neural Networks”, in Proceedings from the Science and Crisis Situation, 2007.
  11. [11] P. Wang, and G. Vachtsevanos. “Fault Prognosis Using Dynamic Wavelet Neural Networks”, in Proc. AAAI Technical Report, 1999, pp. 99-104.
  12. [12] J. Dyntar and I. Gros. “Spare Parts Distribution System Management”, Transport & Logistics the International Journal vol. 26, 2013, pp. 1-9.
  13. [13] J. Wang, X. Pan, L. Wang and W. Wei. “Method of Spare Parts Prediction Models Evaluation Based on Grey Comprehensive Correlation Degree and Association Rules Mining: A Case Study in Aviation”. Mathematical Problems in Engineering, vol. 18, 2018, pp. 1-10.10.1155/2018/2643405
  14. [14] C.A. Vargas and M.E. Cortes. “Automobile spare-parts forecasting: A comparative study of time series methods”. International Journal of Automotive and Mechanical Engineering, vol. 14, 2017, pp. 3898-3912.10.15282/ijame.14.1.2017.7.0317
  15. [15] Z. Qian, L. Shenyang, H. Zhijie and Z. Chen. “Prediction Model of Spare Parts Consumption Based on Engineering Analysis Method”, in Proc. GCMM 2016, 2017, pp. 706-710.10.1016/j.proeng.2017.01.208
  16. [16] D. Malindžák and J. Takala. Projecting of logistics systems: Theory and practice. Košice, SK: Expres Publicit, 2005.
  17. [17] M. Hart, J. Rašner and X. Lukoszová. “Demand Forecasting Significance for Contemporary Process Management of Logistics Systems”, in Proc. CLC 2014, 2014.
  18. [18] M. Hasni, M.S. Aguir, M.Z. Babai and Z. Jemai. “Spare parts demand forecasting: a review on bootstrapping methods”, International Journal of Production Research, vol. 57, 2019, pp. 4791-4804.10.1080/00207543.2018.1424375
  19. [19] S. Van der Auweraer, R.N. Boute and A.A. Syntetos. “Forecasting spare part demand with installed base information: A review”. International Journal of Forecasting, vol. 35, 2019, pp. 181-196.10.1016/j.ijforecast.2018.09.002
  20. [20] P. Kačmáry and D. Malindžák. The forecast methods of sale and production in dynamically changing market economy, Ostrava, CZ: TU Ostrava, 2013, pp. 41-55.
  21. [21] A. Rosová. “The system of indicators of distribution logistics, transport logistics and material flow as a tool of controlling in logistics enterprise”. Acta Montanistica Slovaca, vol. 15, 2010, pp. 67-72.
  22. [22] M. Futej. “Design of the Prediction Model of Inventory Levels for Malfunction Parts of Electric Drive Units”. M.A. thesis, Technical University of Košice, Slovakia, 2018.
  23. [23] M. Straka. “System of distribution logistics of enterprise Alfa, a.s.”, Acta Montanistica Slovaca, vol. 15, 2010, pp. 34-43.
  24. [24] J. Seger and R. Hindls. The Statistical Methods in Market Economy, Prague, CZ: Victoria Publishing, 1995, pp. 257-368.
DOI: https://doi.org/10.1515/mspe-2019-0038 | Journal eISSN: 2450-5781 | Journal ISSN: 2299-0461
Language: English
Page range: 242 - 249
Submitted on: May 1, 2019
|
Accepted on: Aug 1, 2019
|
Published on: Dec 4, 2019
Published by: STE Group sp. z.o.o.
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Peter Kačmáry, Dušan Malindžák, Ján Spišák, published by STE Group sp. z.o.o.
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.