Науковий вісник НГУ

Pipe production cost management model based on graph theory

• 
• 

User Rating:  / 1

PoorBest 

Details

Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

Hits: 801

Authors:

O.A.Toporkova, orcid.org/0000-0003-0956-3638, Dnipro Institute of Infrastructure and Transport, Ukrainian State University of Science and Technologies, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

L.I.Lozovska*, orcid.org/0000-0003-2119-6703, Institute of Industrial and Business Technologies, Ukrainian State University of Science and Technologies, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

L.M.Savchuk, orcid.org/0000-0003-2603-7218, Institute of Industrial and Business Technologies, Ukrainian State University of Science and Technologies, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

A.H.Monia, orcid.org/0000-0003-4642-2519, Institute of Industrial and Business Technologies, Ukrainian State University of Science and Technologies, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

L.M.Bandorina, orcid.org/0000-0003-1383-3098, Institute of Industrial and Business Technologies, Ukrainian State University of Science and Technologies, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 123 - 129

https://doi.org/10.33271/nvngu/2024-5/123

Abstract:

The pipe production process is a complex dynamical system with a significant number of production operations and interconnected cost localization centres.

Purpose. To develop a mathematical model of the process of handling analytical information of a pipe enterprise using graph theory for the needs of cost management at each production stage.

Methodology. Technological flow charts of the production job, where the list of mandatory activities and routing of the operating process are indicated, were used to organize cost accounting by operational centres of their localization with the help of computer modelling elements, namely the graph theory. The work used a complex of research methods, including analysis and scientific synthesis of scientific and technical information; theoretical studies; methods of mathematical and computer modelling, engineering developments.

Findings. The cost accounting process is represented by a directed hypergraph. Each production operation is associated with a graph vertex. Each vertex is assigned to a series of interrelated marks: type of technological operation; weight factor; the value of direct costs for the operation; the value of indirect costs for the operation; the expense factor. The initial state of the hypergraph is specified by means of its initial marking, which corresponds to the set cipher of the batch of pipes and its weight. Further execution of the marked hypergraph is performed by running the allowed vertices. Marking of the graph ends if all the information from the technological flow charts of pipe products has been used.

Originality. A model of cost management by operational centres is proposed which will allow dividing the prime cost of pipes which differ according to the production technology. It is recommended to rank pipe products within each technologically similar group for an economically feasible allocation of costs between batches of pipes. The proposed process model of processing analytical information of the pipe enterprise using graph theory will allow providing data governance as for the prime cost of each individual batch of pipe products, will contribute to the improvement in the order generation procedure taking into account the acquired information, and will allow making the appropriate adjustments when making management decisions.

Practical value. Calculation of expenses for production operations allows one to identify the most cost-intensive of them. Relying on the results of the calculation, the enterprise management has the opportunity to manage costs at any stage of the production process. Moreover, the model allows determining the amount of consumed metal for each production operation, which is relevant for pipe enterprises. It is appropriate to focus further scientific developments in this direction on the possibility of managing non-manufacturing cost with the help of mathematical models in economics to optimize the supply and sales activities of the enterprise.

Keywords: pipe products, cost centre, localization of costs, prime cost, hypergraph, model

References.

1. Stetsiuk, P. A., & Lushchevska, O. V. (2020). Organization and implementation of the enterprise planning system. Economy. Management. Business, 3(33), 2631. https://doi.org/10.31673/2415-8089.2020.033237.

2. Marusiak, N. (2021). Financial mechanism of the enterprise and directions of its improvement in the modern economic environment. Ekonomika ta derzhava, (12), 9497. https://doi.org/10.32702/2306-6806.2021.12.94.

3. Tsyplitska, O., & Deineko, O. (2023). Adaptability of the industrial development strategic planning in terms of global instability. Ekonomika ta suspilstvo, (56). https://doi.org/10.32782/2524-0072/2023-56-140.

4. Karpushenko, M., Momot, T., Mizik, Y., Shapoval, G., & Karpushenko, O. (2023). Accounting and analytical provision of enterprise risk management in the conditions of the state of war: identification, assessment, measurement and display of risks. Eastern-European Journal of Enterprise Technologies, 3(13(123)), 42-51. https://doi.org/10.15587/1729-4061.2023.282644.

5. Kurmanov, S. (2022). Importance of the integrated manufacturing execution system for a metallurgical enterprise. Eastern-European Journal of Enterprise Technologies, 6(13(120)), 52-58. https://doi.org/10.15587/1729-4061.2022.265378.

6. Voloshyna, S. V., & Kostakova, L. D. (2016). Risk factors in the formation of current costs of mining and metallurgical enterprises. Visnyk Donetskoho derzhavnoho universytetu upravlinnia, (4), 32-38.

7. Khmeliuk, A., & Nezhumyria, V. (2023). Models of cost behaviour: a managerial perspective. Economic bulletin of the Dniprovsk state technical university, 2(7), 99-106. https://doi.org/10.31319/2709-2879.2023iss2(7).293775pp99-106.

8. Arefieva, O., Tytykalo, V., & Arefiev, S. (2023). Enterprise development based on complex value in the context of digital marketing. Adaptive Management Theory and Practice Economics, 15(30). https://doi.org/10.33296/2707-0654-15(30)-07.

9. Alventosa, A., Pires, C. P., Jorge, S. F., Pinho, J., & Catalao-Lo­pes, M. (2023). How does firms’ cost structure affect their quality–price mix? An experimental analysis. Journal of Behavioral and Experimental Economics, 107, 102-109. https://doi.org/10.1016/j.socec.2023.102109.

10. Kostetska, N. (2021). Cost management at enterprises in conditions of risk. Ekonomika ta suspilstvo, (34). https://doi.org/10.32782/2524-0072/2021-34-67.

11. Stetsiv, I. S. (2019). Three-dimensional matrix classification model of expenses of economic entities as a means of adapting a scientifically grounded approach to automation of managerial processes. Scientific Bulletin of UNFU, 29(4), 75-81. https://doi.org/10.15421/40290416.

12. Syrotenko, A. L., Balakin, V. F., & Zinchenko, S. M. (2023). Analysis of the production of cold-formed pipes with increased physical and mechanical characteristics (titanium alloys and stainless steels). Collection of Scientific Papers “SCIENTIA”, (pp. 111-116), March 24, 2023. Zagreb, Croatia. Retrieved from https://previous.scientia.report/index.php/archive/article/view/824.

13. Toporkova, O. A., Savchuk, L. M., & Sokyrynska, I. H. (2015). Formation of an integrated system of energy cost management at the pipe enterprise. Economics Bulletin, 3(51), 101-109. ISSN 2073-9982.

14. Ladaniuk, A., Lutska, N., & Vlasenko, L. (2021). Classification of graph models in the tasks of development for intellectual automated control systems. Scientific Works of National University of Food Technologies, 27(6), 7-10. https://doi.org/10.24263/2225-2924-2021-27-6-3.

15. Zrafi, R., Ghedira, S., & Besbes, K. (2018). A Bond Graph Approach for the Modeling and Simulation of a Buck Converter. Journal of Low Power Electronics and Applications, 8(1). https://doi.org/10.3390/jlpea8010002.

16. Mathai, J., Mathai, P. P., & Babu, I. (2017). A Survey on Role of Graph Theory in Various Approaches. Journal of Computer and Mathematical Sciences, 8(6), 261-268. ISSN 0976-5727 (Print). ISSN 2319-8133 (Online).

17. Boinik, A., Progonnij, O., Kameniev, O., Lapko, A., Kustov, V., Kuzmenko, D., & Shcheblykina, O. (2018). Development and investigation of methods of graphic-functional modeling of distributed systems. Eastern-European Journal of Enterprise Technologies, 4(4(94)), 59-69. https://doi.org/10.15587/1729-4061.2018.140636.

18. Bazrafshan, P., On, T., Basereh, S., Okumus, P., & Ebrahimkhanlou, A. (2023). A graph-based method for quantifying crack patterns on reinforced concrete shear walls. Computer-Aided Civil and Infrastructure Engineering. https://doi.org/10.1111/mice.13009.

19. Rabbani, M., Monshi, M., & Rafiei, H. (2014). A new AATP model with considering supply chain lead-times and resources and scheduling of the orders in flowshop production systems: A graph-theoretic view. Applied Mathematical Modelling, 38(24), 6098-6107. https://doi.org/10.1016/j.apm.2014.05.011.

20. Xiao, K., Li, D., Wang, X., & Guo, P. (2022). Modeling and application of marketing and distribution data based on graph computing. Global Energy Interconnection, 5(4), 448-460. https://doi.org/10.1016/j.gloei.2022.08.010.

21. Voznenko, N. I. (2015). Theoretical aspects of formation of the organizational and economic mechanism of adaptive management of the enterprise logistics system. BiznesInform, 12, 206-214.

22. Prokhorova, V., & Mushnykova, S. (2020). Alternative strategic scenarios for managing metallurgical enterprises security development based on cognitive modelling. Bulletin of the Kyiv National University of Technologies and Design. Series: Economic sciences, 143(1), 59-68. https://doi.org/10.30857/2413-0117.2020.1.6.

23. Application of Graph Theory in real world [PowerPoint slides]. (n.d.). Retrieved from http://prezi.com/tseh1wvpves-/application-of-graph-theory-in-real-world.

• < Prev
• Next >