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Problems on the world market, related to delays in supply chains, have forced enterprises to adopt a more flexible approach in the production processes of the offered products. In order to meet customer needs, companies can often look for alternative supply chains, as well as take over the production of key components necessary to maintain business continuity. Therefore, companies have to make important decisions in the context of management. A simulation model may be a tool helpful in making decisions related to production planning, which, based on the actual data collected from the process, allows for the verification of decisions before entering them into the real system. The motivation to conduct the research was the search for answers: How entrepreneurs, while maintaining profitability, can ensure the continuity of production processes by searching for alternative production methods. The article considers a comparison of two production processes for the production of a shield type product: classic production - on a lathe and hybrid production using the SLM method and machining only technologically significant surfaces on a lathe. The main goal of the research is to compare two production processes: classic and hybrid in terms of efficiency, energy efficiency and production costs. The research takes into account the use of different laser powers and the possibility of incremental production of several products at the same time. In order to achieve the assumed goal, a simulation model was used to carry out the research, which was developed on the basis of preliminary experimental studies. A series of simulations were performed, taking into account the variability criteria, and then the efficiency, energy efficiency and profitability of using alternative production methods were analysed.
Słowa kluczowe
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Rocznik
Tom
Strony
94--107
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
- Department of Production Management, Faculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology in Szczecin, al. Piastów 19, 70-310 Szczecin, Poland
autor
- Department of Production Management, Faculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology in Szczecin, al. Piastów 19, 70-310 Szczecin, Poland
autor
- Department of Production Management, Faculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology in Szczecin, al. Piastów 19, 70-310 Szczecin, Poland
autor
- Department of Production Management, Faculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology in Szczecin, al. Piastów 19, 70-310 Szczecin, Poland
Bibliografia
- 1. Akpan I.J., Shanker M. The confirmed realities and myths about the benefits and costs of 3D visualization and virtual reality in discrete event modeling and simulation: A descriptive meta-analysis of evidence from research and practice, Comput. Ind. Eng., 2017; 112: 197–211.
- 2. Bag S., Gupta S., Kumar S. Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development. Int. J. Prod. Econ., 2021; 231: 107844.
- 3. Da Costa Valente M.L., et al. Analysis of the mechanical and physicochemical properties of Ti-6Al-4 V discs obtained by selective laser melting and subtractive manufacturing method. J. Biomed. Mater. Res. B Appl. Biomater., 2021; 109(3): 420–427.
- 4. Diaz A., Schöggl J.-P., Reyes T., Baumgartner R.J. Sustainable product development in a circular economy: Implications for products, actors, decisionmaking support and lifecycle information management, Sustain. Prod. Consum., 2021; 26: 1031–1045.
- 5. Fredriksson C., Sustainability of metal powder additive manufacturing. Procedia Manuf., 2019; 33: 139–144.
- 6. Giannetti B.F., Agostinho F., Eras J.J.C., Yang Z., Almeida C.M.V.B. Cleaner production for achieving the sustainable development goals. J. Clean. Prod., 2020; 271: 122127.
- 7. Goh M., Goh Y.M. Lean production theory-based simulation of modular construction processes, Autom. Constr.2019; 101: 227–244.
- 8. Grzesiak D., Terelak-Tymczyna A., Bachtiak-Radka E., Filipowicz K. Technical and Economic Implications of the Combination of Machining and Additive Manufacturing in the Production of Metal Parts on the Example of a Disc Type Element, in Industrial Measurements in Machining, G. M. Królczyk, P. Niesłony, and J. Królczyk, Eds. Cham: Springer International Publishing, 2020; 128–137.
- 9. He L. China is facing its worst power shortage in a decade. That’s a problem for the whole world, Business CNN, CNN. https://www.cnn.com/2021/06/30/economy/china-power-shortage-intl-hnk/index.html (accessed Oct. 04, 2021).
- 10. Hulkó G., Belavý C., Ondrejkovič K, Bartalský L., Bartko M. Control of technological and production processes as distributed parameter systems based on advanced numerical modeling. Control Eng. Pract., 2017; 66: 23–38.
- 11. Ingarao G., Priarone P.C., Deng Y., Paraskevas D. Environmental modelling of aluminium based components manufacturing routes: Additive manufacturing versus machining versus forming. J. Clean. Prod., 2018; 176: 261–275.
- 12. Malega P., Daneshjo N., Rudy V., Rehák R. Simulation and Optimization of Saw Blade Production in Plant Simulation. Advances in Science and Technology Research Journal. 2022;16(3):67-77. DOI:10.12913/22998624/148013.
- 13. Mikušová N.H., Badiarová S., Jeřábek K. Optimization of Welding Pliers Production for the Automotive Industry – Case Study. Advances in Science and Technology Research Journal. 2020;14(4):240-249. DOI:10.12913/22998624/128105.
- 14. Kline K.L., Dale V.H., Rose E., Tonn B. Effects of Production of Woody Pellets in the Southeastern United States on the Sustainable Development Goals. Sustainability, 2021; 13(2): 821.
- 15. Liu Z. Economic comparison of selective laser melting and conventional subtractive manufacturing processes, Northeastern University, 2017.
- 16. Lugaresi G., Matta A. Real-time simulation in manufacturing systems: challenges and research directions, in 2018 Winter Simulation Conference (WSC), Gothenburg, Sweden, Dec., 2018; 3319–3330.107 Advances in Science and Technology Research Journal 2023, 17(1), 94–107.
- 17. Lugaresi G., Aglio G., Folgheraiter F., Matta A. Real-time Validation of Digital Models for Manufacturing Systems: a Novel Signal-processing-based Approach, in 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), Vancouver, BC, Canada, Aug. 2019; 450–455.
- 18. Martinez-Hernandez E., Leung Pah Hang M.Y., Leach M., Yang A. A Framework for Modeling Local Production Systems with Techno-Ecological Interactions: Modeling Local Techno-Ecological Interactions. J. Ind. Ecol., 2017;21(4): 815–828.
- 19. Melao N. E-business processes and e-Business Process Modelling: a state-of-the-art overview, IJSTM, 2009; 11: 293–322.
- 20. Nagasawa T., Pillay C., Beier G., Fritzsche K., Pougel F., Takama T., The K., Bobashev I. Accelerating clean energy through Industry 4.0 Manufacturing the next revolution, the United Nations Industrial Development Organization, Vienna, Austria, 2017. Available: https://www.unido.org/sites/default/files/2017-08/REPORT_Accelerating_clean_energy_through_Industry_4.0.Final_0.pdf.
- 21. Nicholls E., Ely A., Birkin L., Basu P., Goulson D. The contribution of small-scale food production in urban areas to the sustainable development goals: a review and case study. Sustain. Sci., 2020; 15(6): 1585–1599.
- 22. Strnad D., Fedorko G., Molnár V., Fialek P. Simulations as an Assessment Tool for the Feasibility of Logistics Innovations Motivated by the Emergence of Supply Chain Risk. Adv. Sci. Technol. Res. J., 2021; 15: 66–75.
- 23. Tayyab M., Jemai J., Lim H., And Sarkar B., A sustainable development framework for a cleaner multi-item multi-stage textile production system with a process improvement initiative. J. Clean. Prod., 2020; 246: 119055.
- 24. Terelak-Tymczyna A., Bachtiak-Radka E., Jardzioch A. Comparative Analysis of the Production Process of a Flange-Type Product by the Hybrid and Traditional Method with the Use of Simulation Methods, Adv. Sci. Technol. Res. J., 2022; 16(1).
- 25. Tsagkani C., Tsalgatidou A. Process model abstraction for rapid comprehension of complex business processes, Inf. Syst., 2022;103: 101818.
- 26. UNITED NATIONS, Transforming our world: the 2030 agenda for sustainable development, A/RES/70/1. [Online]. Available: https://sdgs.un.org/sites/default/files/publications/21252030%20Agenda%20for%20Sustainable%20Development%20web.pdf.
- 27. Watson J.K., Taminger K.M.B.A decision-support model for selecting additive manufacturing versus subtractive manufacturing based on energy consumption, J. Clean. Prod.,2015; 176: 1316–1322.
- 28. Zhang L., Zhou L., Ren L., Laili Y. Modeling and simulation in intelligent manufacturing, Comput. Ind., 2019; 112: 103123.
- 29. Report available on page https://zarobki.pracuj.pl/.
- 30. Report available on page https://www.rachuneo.pl/prad-dla-firm?subpage=energy-offers-list.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c8fb682d-32bd-4b6a-8d8f-225139ce41f4