The design of forecasting system used for prediction of electro-motion spare parts demands as an improving tool for an enterprise management

• Autorzy: Kačmáry Peter , Malindžák Dušan , Spišák Ján

Identyfikatory

DOI

10.1515/mspe-2019-0038

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

forecast; spare parts; time series; order; model

• Wydawca: STE GROUP
• Czasopismo: Management Systems in Production Engineering
• Rocznik: 2019
• Tom: nr 4 (27)
• Strony: 242--249
• Opis fizyczny: Bibliogr. 24 poz., rys., tab.

Twórcy

autor

Kačmáry Peter

• Technical University of Košice Faculty BERG, Institute of Logistics and Transport Park Komenského 14, 04200 Košice, Slovak Republic

autor

Malindžák Dušan

• Technical University of Košice, Faculty BERG Institute of Logistics and Transport Park Komenského 14, 04200 Košice, Slovak Republic

autor

Spišák Ján

• Technical University of Košice, Faculty BERG Institute of Logistics and Transport Park Komenského 14, 04200 Košice, Slovak Republic

Bibliografia

• [1] J. F. Robeson and W. C. Copacino. The Logistics Handbook, New York, NY: The Free Press, 1994.
• [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.
• [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] 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] 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] 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.
• [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.
• [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.
• [9] M. Christopher. Logistics and Supply Chain Management: creating value-added networks. Harlow, UK: Pearson Education Limited, 1998, pp. 83-98.
• [10] A. Kelíšek. “Time Series Analysis by Neural Networks”, in Proceedings from the Science and Crisis Situation, 2007.
• [11] P. Wang, and G. Vachtsevanos. “Fault Prognosis Using Dynamic Wavelet Neural Networks”, in Proc. AAAI Technical Report, 1999, pp. 99-104.
• [12] J. Dyntar and I. Gros. “Spare Parts Distribution System Management”, Transport & Logistics the International Journal vol. 26, 2013, pp. 1-9.
• [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.
• [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.
• [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.
• [16] D. Malindžák and J. Takala. Projecting of logistics systems: Theory and practice. Košice, SK: Expres Publicit, 2005.
• [17] M. Hart, J. Rašner and X. Lukoszová. “Demand Forecasting Significance for Contemporary Process Management of Logistics Systems”, in Proc. CLC 2014, 2014.
• [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.
• [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.
• [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] 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] 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] M. Straka. “System of distribution logistics of enterprise Alfa, a.s.”, Acta Montanistica Slovaca, vol. 15, 2010, pp. 34-43.
• [24] J. Seger and R. Hindls. The Statistical Methods in Market Economy, Prague, CZ: Victoria Publishing, 1995, pp. 257- 368.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).