Forecasting-Scenario-Heuristic method proposal for assessment of feasibility of steel production scenarios in Poland – Managerial implications for production engineering

• Autorzy: Gajdzik B. , Gawlik R. , Skoczypiec S.

Identyfikatory

DOI

10.1016/j.acme.2018.06.008

• Języki publikacji: EN

Abstrakty

EN

The goal of presented research is to assess the feasibility of environmental scenarios for the Polish metallurgical sector until year 2020. The study employed: (I) Quantitative elaboration of steel production volume forecasts for Poland until year 2020; (II) Qualitative evaluation of factors influencing production processes in the environment of metallurgical companies; (III) Analytic Hierarchy Process for assessment of probability of occurrence of particular environmental scenarios for Polish steel industry: (i) optimistic (steel production volume exceeding the projected average of 8.895 mln tons); (ii) pessimistic (steel production volume lower than the projected average of 8.895 mln tons); (iii) base (steel production volume conform to the projected average of 8.895 mln tons, with a possible 10% deviation). The relevance of decision-making criteria has been assessed by scientists and practitioners with specialization in metallurgy. In result the most probable scenario has been chosen. Practical outcome are managerial conclusions from the perspective of production engineering. Main research limitations originate from the territorial limitation to Poland. Further research should be led in the metallurgical sectors of other European and emerging economies.

Słowa kluczowe

EN

steel production volume; scenario feasibility; multicriteria decision making; AHP (Analytic Hierarchy Process); production engineering

PL

produkcja stali; inżynieria produkcji; metalurgia

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2018
• Tom: Vol. 18, no. 4
• Strony: 1651--1660
• Opis fizyczny: Bibliogr. 43 poz., tab., wykr.

Twórcy

autor

Gajdzik B.

• Department of Production Engineering, Faculty of Materials Engineering and Metallurgy, Silesian University of Technology, 2A Akademicka Street, PL-44100 Gliwice, Poland

autor

Gawlik R.

• International Economics Department, Faculty of Economics and International Relations, Cracow University of Economics, 27 Rakowicka Street,PL-31510 Krakow, Poland

autor

Skoczypiec S.

• Institute of Machine Technology and Automated Production, Faculty of Mechanical Engineering, Cracow University of Technology, 24 Warszawska Street, PL-31155 Krakow, Poland

Bibliografia

• [1] I. Durlik, Restrukturyzacja procesów gospodarczych: reengineering – teoria i praktyka [Restructuring of Economic Processes: Reengineering – Theory and Practice], Placet, Warsaw, 1998.
• [2] World Steel Association, Steel Statistical Yearbook 2017. Available from: www.worldsteel.org/internet-2017/steel-by-topic/statistics/steel-statistical-yearbook-html (accessed 05.12.17).
• [3] Nowa Stal, Produkcja stali w 2017 r. wzrosła o 5,3 proc [Steel production in 2017 up by 5,3%]. Available from: www. nowastal.com.pl/332/produkcja-stali-w-2017-r-wzrosla-o-53-proc (accessed 12.02.18).
• [4] Z. Martyniak, Założenia systemu Shigeo Shingo [Assumptions of Shigeo Shingo system], Organizacja i Kierowanie 2 (88) (1997) 49–63.
• [5] E. Pelikán, Principles of forecasting — a short overview, in: J. Pavelka, G. Tel, M. Bartosek (Eds.), Lecture Notes in Computer Science 1725, Springer, Berlin, 1999 311–327.
• [6] C. Pierdzioch, J.-C. Rülke, A note on forecasting the rate of change of the price of oil: asymmetric loss and forecast rationality, Economies 1 (2013) 6–13.
• [7] P.-H. Kuo, C.-J. Huang, A high precision artificial neural networks model for short-term energy load forecasting, Energies 11 (2018) 213.
• [8] Polish Steel Association, Polish Steel Industry 2017. Available from: http://www.hiph.org/ANALIZY_RAPORTY/pliki/PPS-2017.pdf (accessed 03.03.18).
• [9] B. Gajdzik, Analysis of the size of steel production in Polish steel industry, in: Proc. METAL 2016 Conf. on Metallurgy and Materials, 2016.
• [10] B. Gajdzik, Prognostic modelling of total steel production and according to production technology in Poland, Metalurgija 56 (1–2) (2017) 241–244.
• [11] B. Gajdzik, The predictive scenario analysis in a business model: variants of possible steel production trajectories and efficiency in Poland, in: M. Jabłoński (Ed.), Strategic Performance Management, New Concepts and Contemporary Trends, Nova Science Publishers, Inc, Hauppauge, NY, 2017 235–252.
• [12] A. Manikowski, A.Z. Tarapata, Prognozowanie i Symulacja Rozwoju Przedsiębiorstw [Foresight and Simulation of Development of Enterprises], Druktur, Warsaw, 2002.
• [13] R.G. Brown, Smoothing, Forecasting and Prediction of Discrete Time Series, Prentice Hall, Englewood Cliffs, NY, 1963.
• [14] F.S. Hillier, G.J. Lieberman, Introduction to Operations Research, ninth ed., McGraw-Hill, New York, NY, 2015.
• [15] S. Krawiec, Adaptacyjne modele wygładzania wykładniczego jako instrumenty prognozowania krótkoterminowego zjawisk ilościowych [Adaptive Models of Exponential Smoothing as Instruments of Short-time Foresight of Quantitative occurrences], Wydawnictwo Politechniki Śląskiej, Gliwice, 2014.
• [16] J.S. Armstrong (Ed.), Principles of Forecasting – A Handbook for Researchers and Practitioners,, Springer, Boston, MA, 2001.
• [17] S.W. Malone, R.B. Gramacy, E. Horst, Timing foreign exchange markets, Econometrics 4 (1) (2016) 15.
• [18] B. Gajdzik, Prognozowanie zmian wielkości produkcji stali w Polsce metodą analizy pola sił [Force-field forecasting in steel production changes in Poland], in: R. Knosala (Ed.), Innowacje w zarządzaniu i inżynierii produkcji [Innovations in Production Engineering], vol. 2, Oficyna Wydawnicza Polskiego Towarzystwa Zarządzania Produkcją, Opole, 2018 596–607.
• [19] T.L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, NY, 1980.
• [20] V. Belton, A.E. Gear, On a shortcoming of Saaty's method of analytic hierarchies, Omega 11 (3) (1983) 228–230.
• [21] J.S. Dyer, Remarks on the analytic hierarchy process, Manage. Sci. 36 (3) (1990) 249–258.
• [22] J. Barzilai, Notes on the analytic hierarchy process, in: Proc. NSF Design, Service & Manufacturing Grantees & Research Conf., 2001.
• [23] T.L. Saaty, L. Vargas, R. Whitaker, Addressing with brevity criticism of the Analytic Hierarchy Process, Int. J. Anal. Hierar. Process 1 (2) (2009) 121–134.
• [24] U. Jung, S. Yim, S. Lim, Ch. Kim, Bringing Kano's perspective to AHP: the 2D-AHP decision model, Manage. Prod. Eng. Rev. 7 (4) (2016) 16–26.
• [25] B. Gajdzik, R. Gawlik, Choosing the production function model for an optimal measurement of the restructuring efficiency of the polish metallurgical sector in years 2000–2015, Metals 8 (1) (2018) 23.
• [26] R. Gawlik, Encompassing the work-life balance into early career decision-making of future employees through the analytic hierarchy process, in: J. Kantola, T. Barath, S. Nazir (Eds.), Advances in Intelligent Systems and Computing Series 594, Springer International, Cham,, 2018, 137–147.
• [27] R. Gawlik, M. Głuszak, A. Małkowska, The measurement of housing preferences in the analytic hierarchy process, Folia Oeconomica Stetinensia 17 (1) (2017) 31–43.
• [28] R. Gawlik, G. Jacobsen, Work-life balance decision-making of norwegian students: implications for human resources management, Entrep. Bus. Econ. Rev. 4 (4) (2016) 153–170.
• [29] B. Marona, A. Wilk, Tenant mix structure in shopping centres: some empirical analyses from Poland, Entrep. Bus. Econ. Rev. 4 (2) (2016) 51–65.
• [30] M. Medineckiene, E.K. Zavadskas, F. Björk, Z. Turskis, Multicriteria decision-making system for sustainable building assessment/certification, Arch. Civil Mech. Eng. 15 (1) (2015) 11–18.
• [31] V. Kutut, E.K. Zavadskas, M. Lazauskas, Assessment of priority alternatives for preservation of historic buildings using model based on ARAS and AHP methods, Arch. Civil Mech. Eng. 14 (2) (2014) 287–294.
• [32] S. Kłos, P. Trebuna, Using the AHP method to select an ERP system for an SME manufacturing company, Manage. Prod. Eng. Rev. 5 (3) (2014) 14–22.
• [33] S. Ierace, S. Cavalieri, An analytic hierarchy process based model for the selection of decision categories in maintenance systems, Manage. Prod. Eng. Rev. 4 (2) (2013) 37–49.
• [34] E.K. Zavadskas, Z. Turskis, J. Tamosaitiene, Selection of construction enterprises management strategy based on the SWOT and multi-criteria analysis, Arch. Civil Mech. Eng. 11 (4) (2011) 1063–1082.
• [35] T.L. Saaty, Decision making with the analytic hierarchy process, Int. J. Serv. Sci. 1 (1) (2008) 83–98.
• [36] T.L. Saaty, Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World, third rev. ed., RWS Publications, Pittsburgh, PA, 2012.
• [37] P. Grošelj, S. Zadnik, Acceptable consistency of aggregated comparison matrices in analytic hierarchy process, Eur. J. Oper. Res. 223 (2) (2012) 417–420.
• [38] R. Remeikiene, L. Gaspareniene, Evaluation of the impact of the EU structural support on the competitiveness of Lithuanian economics, Cent. Eur. J. Public Policy 10 (1) (2016) 1–11.
• [39] B. Gajdzik, World class manufacturing in metallurgical enterprise, Metalurgija 52 (1) (2013) 131–134.
• [40] B. Gajdzik, A. Wyciślik, Assessment of environmental aspects in a metallurgical enterprises, Metalurgija 51 (4) (2012) 537–540.
• [41] B. Gajdzik, The road of Polish steelworks towards market success – changes after restructuring process, Metalurgija 52 (3) (2013) 421–424.
• [42] B. Gajdzik, Wpływ czynników scenariuszy stanów otoczenia na prognozowaną wielkość produkcji stali w Polsce [The influence of environmental scenarios' factors on forecasted steel production volume in Poland], Hutnik – Wiadomości Hutnicze 85 (2) (2018) 48–53.
• [43] Deloite CIS Research Center, Overview of steel and iron market 2017. Available from: www2.deloitte.com/content/dam/Deloitte/ru/Documents/manufacturing/ru-iron-and-steel-industry-report-eng.pdf (accessed 06.04.18).

Uwagi

PL

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