Additive and Subtractive Manufacturing of Inconel 718 Components - Estimation of Time, Costs and Carbon Dioxide Emission – Case Study

• Autorzy: Zębala Wojciech , Gaweł Anna

Identyfikatory

DOI

10.12913/22998624/176824

• Języki publikacji: EN

Abstrakty

EN

The article presents the cost analysis of three techniques that can be used to produce a cylindrical part from Inconel 718 nickel alloy. First of them allows the part to be shaped by additive manufacturing (AM). In the second technique the shape is obtained by forging. Both techniques require the use of machining to give the final dimensional and shape accuracy of the manufactured part. The third technique is based solely on machining operations. Research has shown that the most expensive technique for high-volume production is SLM/LMF. Based on the case study, it can be concluded that after a year of production using the SLM/LMF, forging and machining methods, the carbon dioxide emission is the biggest in the additive manufacturing. Optimizing the Ra and Fc parameters causes differences in carbon dioxide emissions. The turning process including machining optimization due to Fc characterizes a higher ability to produce parts than optimization due to roughness parameter Ra.

Słowa kluczowe

EN

additive manufacturing; Inconel 718 nickel alloy; SLM; LMF; carbon dioxide emission; year production; subtractive manufacturing

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2024
• Tom: Vol. 18, no 1
• Strony: 98--109
• Opis fizyczny: Bibliogr. 25 poz., fig., tab.

Twórcy

autor

Zębala Wojciech

• Department of Production Engineering, Faculty of Mechanical, Cracow University of Technology

autor

Gaweł Anna

• Department of Production Engineering, Faculty of Mechanical, Cracow University of Technology

• https://orcid.org/0000-0001-7784-4007

Bibliografia

• 1. Mamalis A.G., Grabchenko A.I., Fedorovich V.A., and Kundrak J., Methodology of 3D simulation of processes in technology of diamond-composite materials. Int. J. Adv. Manuf. Technol., 2009, 43(11–12), doi: 10.1007/s00170-008-1802-0.
• 2. Zębala W. and Matras A., Optimization of Free-form surface machining. Production Process in Mechanical Engineering – Research Reports, TU Kosice. 2009, 65–72.
• 3. Özel T. and Karpat Y., Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks, Int. J. Mach. Tools Manuf., 2005, 45(4–5), doi: 10.1016/j.ijmachtools.2004.09.007.
• 4. Thakur B., Ramamoorthy D.G., and Vijayaraghavan L., Machinability investigation of Inconel 718 in high-speed turning, Int. J. Adv. Manuf. Technol., 2009, 45(5–6), doi: 10.1007/s00170-009-1987-x.
• 5. Tansel I.N., et al., Selection of optimal cutting conditions by using GONNS, Int. J. Mach. Tools Manuf., 2006, 46(1), doi: 10.1016/j.ijmachtools.2005.04.012.
• 6. Varotsis A.B., 3D Printing vs. CNC machining. 3D Hubs, 2018.
• 7. Rojek I., Mikołajewski D., Kotlarz P., Macko M., and Kopowski J., Intelligent system supporting technological process planning for machining and 3D printing, Bull. Polish Acad. Sci. Tech. Sci., 2021, 69(2), doi: 10.24425/bpasts.2021.136722.
• 8. Miranda-Molina L., Quinayas-Ortiz A., and Peña-Rodríguez G., Design and simulation of a mechanical system for the machining of parts and printing in 3D (x, y, z), Rev. UIS Ing., 2020,19(4), doi: 10.18273/revuin.v19n4-2020010.
• 9. Layer A., Ten Brinke E., Van Houten F., Kals H., and Haasis S., Recent and future trends in cost estimation, Int. J. Comput. Integr. Manuf., 2002, 15(6), doi: 10.1080/09511920210143372.
• 10. Eliashberg J., Elberse A., and Leenders M.A.A.M., The motion picture industry: Critical issues in practice, current research, and new research directions, Mark. Sci., 2006, 25(6), doi: 10.1287/mksc.1050.0177.
• 11. Aspara J. and Tikkanen H., Creating novel consumer value vs. capturing value: Strategic emphases and financial performance implications, J. Bus. Res., 2013, 66(5), 593–602, doi: 10.1016/j.jbusres.2012.04.004.
• 12. Castrogiovanni G.J. and Bruton G.D., Business turnaround processes following acquisitions: Reconsidering the role of retrenchment, J. Bus. Res., 2000, 48(1), doi: 10.1016/S0148-2963(98)00072-1.
• 13. Finney A., Value chain restructuring in the global film industry. In: The 4th Annual Conference on ‘Cultural Production in a Global Context: The Worldwide Film Industries, Grenoble Ecole de Management, Grenoble, France, June 2010.
• 14. Lange J., Bergs F., Weigert G., and Wolter K.J, Simulation of capacity and cost for the planning of future process chains, in International Journal of Production Research, 2012, 50(21), doi: 10.1080/00207543.2012.661889.
• 15. Sebbe N.P.V., Fernandes F., Sousa V.F.C., and Silva F.J.G., Hybrid Manufacturing Processes Used in the Production of Complex Parts: A Comprehensive Review, Metals, 2022, 12(11), doi: 10.3390/met12111874.
• 16. Bassoli E., Defanti S., Tognoli E., Vincenzi N., and Esposti L.D., Design for additive manufacturing and for machining in the automotive field, Appl. Sci., 2021, 11(16), doi: 10.3390/app11167559.
• 17. Quinsat Y., Sabourin L., and Lartigue C., Surface topography in ball end milling process: Description of a 3D surface roughness parameter, J. Mater. Process. Technol., 2008, 195(1–3), doi: 10.1016/j.jmatprotec.2007.04.129.
• 18. Dong W. P., Sullivan P. J., and Stout K.J., Comprehensive study of parameters for characterizing three-dimensional surface topography II: Statistical properties of parameter variation, Wear, 1993, 167(1), doi: 10.1016/0043-1648(93)90050-V.
• 19. Yang W.H. and Tarng Y.S, Design optimization of cutting parameters for turning operations based on the Taguchi method, J. Mater. Process. Technol., 1998, 84(1–3), doi: 10.1016/S0924-0136(98)00079-X.
• 20. Selvaraj D.P. and Chandramohan P., Optimization of surface roughness of AISI 304 austenitic stainless steel in dry turning operation using Taguchi design method, J. Eng. Sci. Technol., 2010, 5(3).
• 21. Athreya S. and Venkatesh Y.D., Application of taguchi method for optimization of process parameters in improving the surface roughness of lathe facing operation, Int. Ref. J. Eng. Sci., 2012,1(3).
• 22. Kostowski W. and Barzantny M, Efektywność energetyczna i środowiskowa wybranych metod wykorzystania wodoru, Energetyka, 2022, 445–450.
• 23. Cuixia Z., Conghu L., and Xi Z., Optimization control method for carbon footprint of machining process, Int. J. Adv. Manuf. Technol., 2017, 92(5–8), doi: 10.1007/s00170-017-0241-1.
• 24. Garzon-Hernandez S., Arias A., and Garcia-Gonzalez D., A continuum constitutive model for FDM 3D printed thermoplastics, Compos. Part B Eng., 2020, 201, doi: 10.1016/j.compositesb.2020.108373.
• 25. Priarone P.C., Campatelli G., Montevecchi F.,.Venturini G, and Settineri L., A modelling framework for comparing the environmental and economic performance of WAAM-based integrated manufacturing and machining. CIRP Ann., 2019, 68(1), doi: 10.1016/j.cirp.2019.04.005.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).