Research Article
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Year 2022, , 43 - 48, 30.06.2022
https://doi.org/10.36222/ejt.1066472

Abstract

Supporting Institution

Selçuk Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü

Project Number

20111014

Thanks

Selçuk Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü'ne desteklerinden dolayı teşekkür ederiz.

References

  • Kant, G. and Sangwan, K. S., Prediction and optimization of machining parameters for minimizing power consumption and surface roughness in machining, Journal of Cleaner Production, (2014), 83 pp. 151-164.
  • Sangwan, K. S., Development of a multi criteria decision model for justification of green manufacturing systems, Int. J. Green. Econ., (2011), no. 5, pp. 285-305.
  • He, Y., Liu, B., Zhang, X., Gao, H. and Liu, H., A modeling method of task-oriented energy consumption for machining manufacturing system, J. Clean. Prod., 23, (2012), pp. 167-174.
  • Korkmaz, M. E. and Günay, M., Finite Element Modelling of Cutting Forces and Power Consumption, Arabian Journal for Science and Engineering, 43, (2018), pp. 4863-4870.
  • Composeco-Negrete, C., Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA, J. Clean. Prod., 53, (2013), pp. 195-203.
  • Black, J. T. and Kohser, R. A., DeGarmo’s Materials and Processes in Manufacturing, 11th edition, John Wiley&Sons, Hoboken, 2013.
  • Coşkun, M., Çiftçi, İ. and Demir, H., AISI P20S Kalıp Çeliğinin İşlenebilirliğinin İncelenmesi, İmalat Teknolojileri ve Uygulamaları, 2, (2021), 2, pp. 1-9.
  • Uzun, M., Usca, Ü. A., Kuntoğlu, M. and Gupta, M. K., Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel, The International Journal of Advanced Manufacturing Technology, (2022), pp. 1-12.
  • Usca, Ü. A., Uzun, M., Sap, S., Kuntoğlu, M., Giasin, K., Pimenov, D. Y. and Wjciechwski, S., Tool wear, surface roughness, cutting temperature and chips morphology evaluation of Al/TiN coated carbide cutting tools in milling of Cu-B-CrC based ceramic matrix composites, Journal of Materials Research and Technology, 16, (2022), pp. 1243-1259.
  • Haddag, B., Atlati, S., Nouari, M. and Moufki, A., Dry machining aeronautical aluminum alloy AA2024-T351: Analysis of cutting forces, chip segmentation and built-up edge formation, Metals, 6, (2016), 9, p. 197.
  • Aggarwal, A., Singh, H., Kumar, P. and Singh, M., Optimizing power consumption for CNC turned parts using response surface methodology and Taguchi’s techniqueda comparative analysis, J. Mater. Process. Technol., 200, (2008), pp. 373-384.
  • Bhushan, R. H., Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites, J. Clean. Prod., 39, (2013), pp. 242-254.
  • Yan, J. and Li, L., Multi-objective optimization of milling parameters e the trade tradeoffs between energy, production rate and cutting quality, J. Clean. Prod., 52, (2013), pp. 462-471.
  • Campatelli, G., Lorenzini, L. and Scippa, A., Optimization of process parameters using a Response Surface Method for minimizing power consumption in the milling of carbon steel, Journal of Cleaner Production, 66, (2014), pp. 309-316.
  • El-Tamimi, A. M. and El-Hossainy, T. M., Investigating the machinability of AISI 420 stainless steel using factorial design, Mater. Manuf. Process., 23, (2008), 4, pp. 419-426.
  • Valiorgue, F., Rech, J., Hamdi, H., Gilles, P. and Bergheau, J. M., 3D modeling of residual stresses induced in finish turning of an AISI304L stainless steel, Int. J. Mach. Tool. Manuf., 53, (2012), 1, pp. 77-90.
  • Galanis, N. I. and Manolakos, D. E., Finite element analysis of the cutting forces in turning of femoral heads from AISI 316L stainless steel, In: Proceedings of theWorld Congress on Engineering 2014, London, 2014.
  • Johnson, G. J. and Cook, W. H., A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures, In: Proceedings of the Seventh International Symposium on Ballistics, The Hague, 1983.
  • Cadoni, E. and Forni, D., Mechanical behaviour of a very-high strength steel (S960QL) under extreme conditions of high strain rates and elevated temperatures, Fire Safety Journal, (2019), pp. 1-14.
  • Eren, N., Hayat, F. and Günay, M., Sertleştirilmiş 1.2367 Takım Çeliğinin İşlenmesinde Enerji Tüketiminin Analizi ve Modellenmesi, İmalat Teknolojileri ve Uygulamaları, 1, (2020), 3, pp. 41-49.
  • Bouzid, L., Yallase, M. A., Chaoui, K., Mabrouki, T. and Boulanouar, L., “Mathematical modeling for turning on AISI 420 stainless steel using surface response methodology,” Proc. IMechE Part B J. Eng. Manuf., 229, (2015), 1, pp. 45-61.
  • Binali, R., Sıcak iş takkım çeliğinin (TOOLOX 44) işlenebilirliğinin incelenmesi, MSc. Thesis, Karabük Üniversitesi Fen Bilimleri Enstitüsü, Karabük, 2017.
  • Neşeli, S., Tırlama titreşimleri üzerine süreç sönümleme etkisinin analitik olarak araştırılması ve tornalamada kararlı kesme derinliği ile süreç sönümleme değerlerine bağlı parametre optimizasyonu, PhD. Thesis, Selçuk Üniversitesi Fen Bilimleri Enstitüsü, Konya, 2013.
  • Vidal, C., Infante, V. and Vilaca, P., “Assessment of Improvement Techniques Effect on Fatigue Behaviour of Friction Stir Welded Aerospace Aluminium Alloys,” Procedia Engineering, 2, (2010), pp. 1605-1616.

Investigation of Power Consumption in the Machining of S960QL Steel by Finite Elements Method

Year 2022, , 43 - 48, 30.06.2022
https://doi.org/10.36222/ejt.1066472

Abstract

Armor steels have good strength and corrosion resistance; however, due to their difficult machinability, high power consumption occurs. High power consumption increases the cost in machinability studies. Therefore, minimizing power consumption is important for sustainable and cleaner production. In order to minimize power consumption during machining, factors such as workpiece material, cutting tool material and geometry, machining conditions and cutting parameters must be compatible with each other. For this reason, power consumption modeling was carried out in the milling of S960QL structural steel material according to the finite elements method, depending on the cutting parameters. In this context, simulation processes were carried out at three levels for each factor: cutting speed, lateral depth, axial depth and feed rate. The most effective parameter in power consumption was the axial deep of cut. There was a 476% change between the highest and lowest power consumption. It is concluded that finite element modeling is feasible in order to determine the effect of processing parameters on power consumption.

Project Number

20111014

References

  • Kant, G. and Sangwan, K. S., Prediction and optimization of machining parameters for minimizing power consumption and surface roughness in machining, Journal of Cleaner Production, (2014), 83 pp. 151-164.
  • Sangwan, K. S., Development of a multi criteria decision model for justification of green manufacturing systems, Int. J. Green. Econ., (2011), no. 5, pp. 285-305.
  • He, Y., Liu, B., Zhang, X., Gao, H. and Liu, H., A modeling method of task-oriented energy consumption for machining manufacturing system, J. Clean. Prod., 23, (2012), pp. 167-174.
  • Korkmaz, M. E. and Günay, M., Finite Element Modelling of Cutting Forces and Power Consumption, Arabian Journal for Science and Engineering, 43, (2018), pp. 4863-4870.
  • Composeco-Negrete, C., Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA, J. Clean. Prod., 53, (2013), pp. 195-203.
  • Black, J. T. and Kohser, R. A., DeGarmo’s Materials and Processes in Manufacturing, 11th edition, John Wiley&Sons, Hoboken, 2013.
  • Coşkun, M., Çiftçi, İ. and Demir, H., AISI P20S Kalıp Çeliğinin İşlenebilirliğinin İncelenmesi, İmalat Teknolojileri ve Uygulamaları, 2, (2021), 2, pp. 1-9.
  • Uzun, M., Usca, Ü. A., Kuntoğlu, M. and Gupta, M. K., Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel, The International Journal of Advanced Manufacturing Technology, (2022), pp. 1-12.
  • Usca, Ü. A., Uzun, M., Sap, S., Kuntoğlu, M., Giasin, K., Pimenov, D. Y. and Wjciechwski, S., Tool wear, surface roughness, cutting temperature and chips morphology evaluation of Al/TiN coated carbide cutting tools in milling of Cu-B-CrC based ceramic matrix composites, Journal of Materials Research and Technology, 16, (2022), pp. 1243-1259.
  • Haddag, B., Atlati, S., Nouari, M. and Moufki, A., Dry machining aeronautical aluminum alloy AA2024-T351: Analysis of cutting forces, chip segmentation and built-up edge formation, Metals, 6, (2016), 9, p. 197.
  • Aggarwal, A., Singh, H., Kumar, P. and Singh, M., Optimizing power consumption for CNC turned parts using response surface methodology and Taguchi’s techniqueda comparative analysis, J. Mater. Process. Technol., 200, (2008), pp. 373-384.
  • Bhushan, R. H., Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites, J. Clean. Prod., 39, (2013), pp. 242-254.
  • Yan, J. and Li, L., Multi-objective optimization of milling parameters e the trade tradeoffs between energy, production rate and cutting quality, J. Clean. Prod., 52, (2013), pp. 462-471.
  • Campatelli, G., Lorenzini, L. and Scippa, A., Optimization of process parameters using a Response Surface Method for minimizing power consumption in the milling of carbon steel, Journal of Cleaner Production, 66, (2014), pp. 309-316.
  • El-Tamimi, A. M. and El-Hossainy, T. M., Investigating the machinability of AISI 420 stainless steel using factorial design, Mater. Manuf. Process., 23, (2008), 4, pp. 419-426.
  • Valiorgue, F., Rech, J., Hamdi, H., Gilles, P. and Bergheau, J. M., 3D modeling of residual stresses induced in finish turning of an AISI304L stainless steel, Int. J. Mach. Tool. Manuf., 53, (2012), 1, pp. 77-90.
  • Galanis, N. I. and Manolakos, D. E., Finite element analysis of the cutting forces in turning of femoral heads from AISI 316L stainless steel, In: Proceedings of theWorld Congress on Engineering 2014, London, 2014.
  • Johnson, G. J. and Cook, W. H., A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures, In: Proceedings of the Seventh International Symposium on Ballistics, The Hague, 1983.
  • Cadoni, E. and Forni, D., Mechanical behaviour of a very-high strength steel (S960QL) under extreme conditions of high strain rates and elevated temperatures, Fire Safety Journal, (2019), pp. 1-14.
  • Eren, N., Hayat, F. and Günay, M., Sertleştirilmiş 1.2367 Takım Çeliğinin İşlenmesinde Enerji Tüketiminin Analizi ve Modellenmesi, İmalat Teknolojileri ve Uygulamaları, 1, (2020), 3, pp. 41-49.
  • Bouzid, L., Yallase, M. A., Chaoui, K., Mabrouki, T. and Boulanouar, L., “Mathematical modeling for turning on AISI 420 stainless steel using surface response methodology,” Proc. IMechE Part B J. Eng. Manuf., 229, (2015), 1, pp. 45-61.
  • Binali, R., Sıcak iş takkım çeliğinin (TOOLOX 44) işlenebilirliğinin incelenmesi, MSc. Thesis, Karabük Üniversitesi Fen Bilimleri Enstitüsü, Karabük, 2017.
  • Neşeli, S., Tırlama titreşimleri üzerine süreç sönümleme etkisinin analitik olarak araştırılması ve tornalamada kararlı kesme derinliği ile süreç sönümleme değerlerine bağlı parametre optimizasyonu, PhD. Thesis, Selçuk Üniversitesi Fen Bilimleri Enstitüsü, Konya, 2013.
  • Vidal, C., Infante, V. and Vilaca, P., “Assessment of Improvement Techniques Effect on Fatigue Behaviour of Friction Stir Welded Aerospace Aluminium Alloys,” Procedia Engineering, 2, (2010), pp. 1605-1616.
There are 24 citations in total.

Details

Primary Language English
Subjects Mechanical Engineering
Journal Section Research Article
Authors

Rüstem Binali 0000-0003-0775-3817

Süleyman Yaldız 0000-0003-0931-9643

Süleyman Neşeli 0000-0003-1553-581X

Project Number 20111014
Publication Date June 30, 2022
Published in Issue Year 2022

Cite

APA Binali, R., Yaldız, S., & Neşeli, S. (2022). Investigation of Power Consumption in the Machining of S960QL Steel by Finite Elements Method. European Journal of Technique (EJT), 12(1), 43-48. https://doi.org/10.36222/ejt.1066472

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