Development of information technology for supporting the process of adjustment of the food enterprise assortment

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.123383

Keywords:

multiproduct food enterprise, intelligent data analysis

Abstract

The work aims to study the processes of production management at the multiproduct food enterprises. To improve management effectiveness, application of the created information technology to support the process of adjusting the product assortment was proposed. This is achieved by reducing the total product cost price and obtaining an additional profit. The proposed information technology consists of five main stages which provide a deep analysis of production based on the accumulated business information about the company's activities, sales, market demand, quality and quantity indicators of the products, formulations, etc. The stages of the developed information technology include application of the data mining methods such as clustering, decision trees, forecast methods based on time series. Each proposed method of data mining was substantiated and tested for each of the stages of the proposed information technology. The essential feature of the proposed technology is that adoption of the forecast level of cost price and demand are estimated using graphical and analytical methods of break-even calculation. The use of this technology will improve efficiency of economic activity of enterprises. This is achieved by reducing the product cost price. The proposed technology can be used both in the food industry and in other similar industries.

Author Biographies

Olena Kharkianen, National University of Food Technologies Volodymyrska str., 68, Kyiv, Ukraine, 01601

PhD, Associate Professor

Department of Information Systems

Olena Myakshylo, National University of Food Technologies Volodymyrska str., 68, Kyiv, Ukraine, 01601

PhD, Associate Professor

Department of Information Systems

Serhii Hrybkov, National University of Food Technologies Volodymyrska str., 68, Kyiv, Ukraine, 01601

PhD, Associate Professor

Department of Information Systems

Mykola Kostikov, National University of Food Technologies Volodymyrska str., 68, Kyiv, Ukraine, 01601

PhD, Senior Lecturer

Department of Information Systems

References

  1. Tsymbaliuk, L. H., Antoshkina, L. I., Skryhun, N. P. (2014). Planuvannia diyalnosti pidpryiemstv kharchovoi promyslovosti. Donetsk: Yuho-Vostok, 340.
  2. Tsymbaliuk, L. H., Skryhun, N. P., Antoshkina, L. I. (2013). Formuvannia ta upravlinnia vytratamy vyrobnytstva. Donetsk: Yuho-Vostok, 240.
  3. Onyeocha, C. E., Wang, J., Khoury, J., Geraghty, J. (2015). A comparison of HK-CONWIP and BK-CONWIP control strategies in a multi-product manufacturing system. Operations Research Perspectives, 2, 137–149. doi: 10.1016/j.orp.2015.07.001
  4. Ajorlou, S., Shams, I. (2012). Artificial bee colony algorithm for CONWIP production control system in a multi-product multi-machine manufacturing environment. Journal of Intelligent Manufacturing, 24 (6), 1145–1156. doi: 10.1007/s10845-012-0646-5
  5. Onyeocha, C. E., Khoury, J., Geraghty, J. (2013). Evaluation of the Effect of Erratic Demand on a Multi-Product Basestock Kanban-CONWIP Control Strategy. Proc. of the 9th conf. on stochastic models of manufacturing and service operations (SMMSO 2013). Kloster Seeon, 147–155.
  6. Baynat, B., Buzacott, J. A., Dallery, Y. (2002). Multiproduct Kanban-like Control Systems. International Journal of Production Research, 40 (16), 4225–4255. doi: 10.1080/00207540210146198
  7. Onyeocha, C. E., Geraghty, J. (2012). A Modification of the Hybrid Kanban-CONWIP Production Control Strategy for Multi-Product Manufacturing Systems. Proc. of the 29th International Manufacturing Conference (IMC29). University of Ulster, Belfast (UK).
  8. Shorikov, A. F., Rassadina, E. S. (2012). Dinamicheskaya optimizaciya kompleksnogo programmnogo upravleniya strukturoy tovarnogo assortimenta predpriyatiya. Ekonomika regiona, 3, 261–271.
  9. Tseng, T.-L., Nadackal, A. J., Kwon, Y., Zhang, J., Yao, T. (2007). Modeling complex manufacturing process activities using data mining approach. IIE Annual Conference and Expo 2007 – Industrial Engineering’s Critical Role in a Flat World: Conference Proceedings, 560–565.
  10. Holimchayachotikul, P., Phanruangrong, N. (2010). A Framework for Modeling Efficient Demand Forecasting Using Data Mining in Supply Chain of Food Products Export Industry. Proceedings of the 6th CIRP-Sponsored International Conference on Digital Enterprise Technology, 1387–1397. doi: 10.1007/978-3-642-10430-5_106
  11. Miakshylo, O. M., Kharkianen, O. V. (2011). Planuvannia sobivartosti produktsiyi kharchovoho pidpryiemstva na osnovi analitychnykh modelei OLAP-kubiv. Kharchova promyslovist, 10-11, 332–337.
  12. Barsegyan, A. A., Kupriyanov, M. S., Stepanenko, V. V., Holod, I. (2004). Metody i modeli analiza dannyh: OLAP i Data Mining. Sankt-Peterburg: BHV-Peterburg, 336.
  13. Barsegyan, A. A., Kupriyanov, M. S., Holod, I. I., Tess, M. D., Elizarov, S. I. (2009). Analiz dannyh i processov. Sankt-Peterburg: BHV-Peterburg, 512.
  14. Dyuran, B., Odell, P. (1977). Klasterniy analiz. Moscow: Statistika, 128.
  15. Kim, Dzh.-O., M'yuller, Ch. U., Klekka, U. R. et. al.; Enyukov, I. S. (Ed.) (1989). Faktorniy, diskriminantnyy i klasternyy analiz. Moscow: Finansy i statistika, 215.
  16. Miakshylo, O. M., Kharkianen, O. V. (2014). Doslidzhennia i rozrobka metodiv upravlinnia ryzykamy v diyalnosti kharchovoho pidpryiemstva. Naukovi pratsi Natsionalnoho universytetu kharchovykh tekhnolohiyi, 20 (5), 105–114.
  17. Hajduová, Z., Weiss, E., Mixtaj, L. (2009). Application of Statistical Methods at Copper Wire Manufacturing. Metalurgiya, 48 (1), 55–58.
  18. Perzyk, M., Krawiec, K., Kozłowski, J. (2009). Application of time-series analysis in foundry production. Archives of Foundry Engineering, 9 (3), 109–114.
  19. Suciu, G. et al. (2014). Cloud Computing and Big Data as Convergent Technologies for Retail Pricing Strategies of SMEs. Proc. of the 8th International Conf. „Challenges of the Knowledge Society” (CKS 2014). Bucharest (Romania), 1044–1052.
  20. Bubeník, P., Horák, F. (2014). Proactive Approach to Manufacturing Planning. Quality Innovation Prosperity, 18 (1), 23–32. doi: 10.12776/qip.v18i1.208
  21. Tumanov, V. E., Maklakov, S. V. (2007). Proektirovanie relyacionnyh hranilishch dannyh. Moscow: Dialog-MIFI, 333.
  22. Maklakov, S. V. (2008). Modelirovanie biznes-processov s AllFusion PM. Moscow: Dialog-MIFI, 224.
  23. Koch, R. (2014). Living the 80/20 Way: Work Less, Worry Less, Succeed More, Enjoy More. London: Nicholas Brealey Publishing, 196.
  24. Davydov, A. A. (2001). Ubyvayushchie chislovye posledovatel'nosti v sociologii: fakty, ob'yasneniya, prognozy. Sociologicheskie issledovaniya, 7, 113–119.
  25. Târnăveanu, D. (2012). Pentaho Business Analytics: a Business Intelligence Open Source Alternative. Database Systems Journal, 3 (3), 23–34.

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Published

2018-02-13

How to Cite

Kharkianen, O., Myakshylo, O., Hrybkov, S., & Kostikov, M. (2018). Development of information technology for supporting the process of adjustment of the food enterprise assortment. Eastern-European Journal of Enterprise Technologies, 1(3 (91), 77–87. https://doi.org/10.15587/1729-4061.2018.123383

Issue

Vol. 1 No. 3 (91) (2018): Control processes

Section

Control processes

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Copyright (c) 2018 Olena Kharkianen, Olena Myakshylo, Serhii Hrybkov, Mykola Kostikov

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