1. bookVolume 27 (2019): Issue 4 (December 2019)
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The Design of Forecasting System Used for Prediction of Electro-Motion Spare Parts Demands as an Improving Tool for an Enterprise Management

Published Online: 04 Dec 2019
Page range: 242 - 249
Received: 01 May 2019
Accepted: 01 Aug 2019
Journal Details
License
Format
Journal
First Published
30 Mar 2017
Publication timeframe
4 times per year
Languages
English
Copyright
© 2020 Sciendo

This article describes the design of a simple forecasting system and its practical application to predict the sporadic needs for a spare part. The article shows new approach already implemented in the special servicing and production company in Slovakia and its results during a short period of performance after its implementation. Such a proposed model can be a part of the purchase planning of spare parts within the company’s logistics system. In some companies, the material flow of spare parts is dominant element in terms of logistics costs. Their management is therefore important for cost optimization, customer satisfaction and market sustainability in a competitive environment. The article, in its introductory part, provides an overview of similar practical solutions within the research of this topic, but many models are designed to be applied in a global market environment and predict the amount of spare parts needed in different industries. However, these models are difficult to use for the needs of a small enterprise, because the main problem lies in the time of a spare part demand rather than its quantity. If there is a need for a specific spare part, which costs several hundred or thousands of euros, but the consumption is only a few pieces per year or more than a year, the time prediction of required spare parts is therefore crucial.

Keywords

[1] J. F. Robeson and W. C. Copacino. The Logistics Handbook, New York, NY: The Free Press, 1994.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[9] M. Christopher. Logistics and Supply Chain Management: creating value-added networks. Harlow, UK: Pearson Education Limited, 1998, pp. 83-98.Search in Google Scholar

[10] A. Kelíšek. “Time Series Analysis by Neural Networks”, in Proceedings from the Science and Crisis Situation, 2007.Search in Google Scholar

[11] P. Wang, and G. Vachtsevanos. “Fault Prognosis Using Dynamic Wavelet Neural Networks”, in Proc. AAAI Technical Report, 1999, pp. 99-104.Search in Google Scholar

[12] J. Dyntar and I. Gros. “Spare Parts Distribution System Management”, Transport & Logistics the International Journal vol. 26, 2013, pp. 1-9.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[16] D. Malindžák and J. Takala. Projecting of logistics systems: Theory and practice. Košice, SK: Expres Publicit, 2005.Search in Google Scholar

[17] M. Hart, J. Rašner and X. Lukoszová. “Demand Forecasting Significance for Contemporary Process Management of Logistics Systems”, in Proc. CLC 2014, 2014.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[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.Search in Google Scholar

[23] M. Straka. “System of distribution logistics of enterprise Alfa, a.s.”, Acta Montanistica Slovaca, vol. 15, 2010, pp. 34-43.Search in Google Scholar

[24] J. Seger and R. Hindls. The Statistical Methods in Market Economy, Prague, CZ: Victoria Publishing, 1995, pp. 257-368.Search in Google Scholar

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