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ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU

Yıl 2022, Cilt: 6 Sayı: 2, 236 - 249, 31.08.2022
https://doi.org/10.46519/ij3dptdi.1126200

Öz

3D yazıcılar ile imalat birçok girdi parametresi olmasından dolayı oldukça karmaşık bir süreçtir. Bu durum optimum üretim parametrelerin belirlenmesini zorlaştırmaktadır. Bu çalışmada; ABS malzemelerin 3D yazıcılarda ergiyik yığma modelleme (FDM) ile üretilmesinde doluluk oranı (%50, %70 ve %90), dolgu deseni (doğrusal, sekizgen ve bal peteği) ve katman kalınlığı (0,19 mm, 0,29mm ve 0,39 mm) işlem parametrelerinin; yüzey pürüzlülüğü, çekme dayanımı ve imalat sürelerine etkileri varyans analizi (ANOVA) incelenmiştir. Çıktı parametreleri üzerinde en etkili işlem parametresi katman kalınlığıdır. Azalan katman kalınlığının yüzey pürüzlülüğü ve çekme dayanımı üzerinde olumlu etkisi olurken, imalat süresi üzerinde olumsuz etkisi olmuştur. Taguchi L27 (33) deneysel tasarımına göre geçekleştirilen deneylerde optimazyon işleminde üç farklı çıktı parametresi değerlendiği için çoklu performans optimizasyonunda değerlendirme kriteri olarak gri ilişkisel derece kullanılmıştır. Optimum işlem parametresi doğrusal dolgu deseni, %90 dolgu oranı ve 0,19 mm katman kalınlığı olarak belirlenmiştir.

Kaynakça

  • 1. Mohan, N., Senthil, P., Vinodh, S., Jayanth, N., “A review on composite materials and process parameters optimisation for the fused deposition modelling process”, Virtual and Physical Prototyping, Vol. 12, Issue 1, Pages 47–59, 2017.
  • 2.Rashid, A., “Additive manufacturing technologies. in: The international academy for production engineering” CIRP Encyclopedia of Production Engineering, Pages 20 – 45, Springer, Berlin, 2019.
  • 3. Ngo, T.D., Kashani, A., Imbalzano, G., Nguyen, K.T.Q., Hui, D., “Additive manufacturing (3D printing): A review of materials, methods, applications and challenges”, Composites Part B: Engineering, Vol. 143, Pages 172–196, 2018.
  • 4. ISO/ASTM International, “ISO/ASTM 52900: Additive manufacturing - General principles and Terminology”, International Standard, Pages 1–26, 2015.
  • 5. Walker, J.L., Santoro, M., “Processing production of bioresorbable polymer scaffolds for tissue engineering. In: Bioresorbable polymers for biomedical applications”, Pages 181-203, Woodhead Publishing, United Kingdom, 2017.
  • 6. Agarwal, K.M., Shubham, P., Bhatia, D., Sharma, P., Vaid, H., Vajpeyi, R., “Analyzing the ımpact of print parameters on dimensional variation of abs specimens printed using fused deposition modelling (FDM)”, Sensors International, Vol. 3, Pages 100149 – 100157, 2022.
  • 7. 3D printing market size & share | analysis report (2021-2028), https://www.fortunebusinessinsights.c om/industry-reports/3d-printing-market-101902, March 5, 2022
  • 8. Jaisingh Sheoran, A., Kumar, H., “Fused Deposition modeling process parameters optimization and effect on mechanical properties and part quality: Review and reflection on present research”, Materials Today: Proceedings, Vol. 21, Pages 1659–1672, 2020.
  • 9. Vyavahare, S., Teraiya, S., Panghal, D., Kumar, S., “Fused deposition modelling: a review”, Rapid Prototyping Journal, Vol. 26, Issue 1, Pages 176–201, 2020. 10. Mohamed, O.A., Masood, S.H., Bhowmik, J.L., “Optimization of fused deposition modeling process parameters: a review of current research and future prospects”, Advances in Manufacturing, Vol. 3, Issue 1, Pages 42–53, 2015.
  • 11. Turner, B.N., Strong, R., Gold, S.A., “A review of melt extrusion additive manufacturing processes: I. Process design and modeling”, Rapid Prototyping Journal, Vol. 20, Issue 3, Pages 192–204, 2014. 12.Z-ABS_Technical_Data_Sheet,https://cf.zortrax. com/wpcontent/uploads/2018/06/Z-ABS_Technical _ Data_Sheet_eng-1.pdf, March 10, 2022.
  • 13. Solomon, I.J., Sevvel, P., Gunasekaran, J., “A review on the various processing parameters in FDM”, Materials Today: Proceedings, Vol. 37, Pages 509–514, 2020.
  • 14. Günay, M., Gündüz, S., Yılmaz, H., Yaşar, N., Kaçar, R., “PLA Esaslı Numunelerde Çekme Dayanımı İçin 3D Baskı İşlem Parametrelerinin Optimizasyonu,” Journal of Polytechnic, Cilt 23, Sayı 1, Sayfa 73–79, 2019.
  • 15. Alafaghani, A., Qattawi, A., Alrawi, B., Guzman, A., “Experimental Optimization of Fused Deposition Modelling Processing Parameters: A Design-for-Manufacturing Approach”, Procedia Manufacturing, Vol. 10, Pages 791–803, 2017.
  • 16. Baich, L., Manogharan, G., Marie, H., “Study of infill print design on production cost-time of 3D printed ABS parts”, International Journal of Rapid Manufacturing, Vol. 5, Issue 3/4, Pages 308–319, 2015.
  • 17. Anitha, R., Arunachalam, S., Radhakrishnan, P., “Critical parameters influencing the quality of prototypes in fused deposition modelling”, Journal of Materials Processing Technology, Vol. 118, Issue 1–3, Pages 385–388, 2001.
  • 18. De Toro, E.V., Sobrino, J.C., Martínez, A.M., Eguía, V.M., “Analysis of the influence of the variables of the fused deposition modeling (FDM) process on the mechanical properties of a carbon fiber-reinforced polyamide”, Procedia Manufacturing, Vol. 41, Pages 731–738, 2019.
  • 19. Z-SUITE 2: Print Preparation, https://support.zortrax.com/pdf/create/steps.php?id=27770, March 12, 2022.
  • 20. Christodoulou, I.T., Alexopoulou, V.E., Karkalos, N.E., Papazoglou, E.L. and Markopoulos, A.P., “On the surface roughness of 3d printed parts with fdm by a low-budget commercial printer”, Cutting & Tools in Technological System, Vol. 96, Pages 52–64, 2022.
  • 21. Uzun, G., “Analysis of grey relational method of the effects on machinability performance on austempered vermicular graphite cast irons”, Measurement, Vol. 142, Pages 122–130, 2019.
  • 22. Acır, A., Canlı, M.E., Ata, İ. and Çakıroğlu, R., “Parametric optimization of energy and exergy analyses of a novel solar air heater with grey relational analysis”, Applied Thermal Engineering, Vol. 122, Pages 330–338, 2017.
  • 23. Mia, M., Rifat, A., Tanvir, M.F., Gupta, M.K., Hossain, M.J., Goswami, A., “Multi-objective optimization of chip-tool interaction parameters using Grey-Taguchi method in MQL-assisted turning”, Measurement, Vol. 129, Pages 156–166, 2018.
  • 24.Lin, C.L., “Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics”, Materials and Manufacturing Processes, Vol. 19, Issue 2, Pages 209–220, 2004.
  • 25. Mishra, P.C., Das, D.K., Ukamanal, M., Routara, B.C. and Sahoo, A.K., “Multi-response optimization of process parameters using Taguchi method and grey relational analysis during turning AA 7075/SIC composite in dry and spray cooling environments”, International Journal of Industrial Engineering Computations, Vol. 6, Issue 4, Pages 445–456, 2015.
  • 26. Tzeng, C.-J., Lin, Y.-H., Yang, Y.-K. and Jeng, M.-C., “Optimization of turning operations with multiple performance characteristics using the Taguchi method and Grey relational analysis”, Journal of Materials Processing Technology, Vol. 209, Issue 6, Pages 2753–2759, 2009.
  • 27. Sarikaya, M., Güllü, A., “Multi-response optimization of minimum quantity lubrication parameters using Taguchi-based grey relational analysis in turning of difficult-to-cut alloy Haynes 25”, Journal of Cleaner Production, Vol. 91, Pages 347–357, 2015. 28. Ramesh, K., Baranitharan, P., Sakthivel, R., “Investigation of the stability on boring tool attached with double impact dampers using Taguchi based Grey analysis and cutting tool temperature investigation through FLUKE-Thermal imager”, Measurement, Vol. 131, Pages 143–155, 2019.
  • 29. Mia, M., Rifat, A., Tanvir, M.F., Gupta, M.K., Hossain, M.J., Goswami, A., “Multi-objective optimization of chip-tool interaction parameters using Grey-Taguchi method in MQL-assisted turning”, Measurement, Vol. 129, Pages 156–166, 2018.
  • 30. Zerti, O., Yallese, M.A., Zerti, A., Belhadi, S., Girardin, F., “Simultaneous improvement of surface quality and productivity using grey relational analysis based taguchi design for turning couple (AISI D3 steel/ mixed ceramic tool (Al2O3 + TiC))”, International Journal of Industrial Engineering Computations, Vol. 9, Issue 2, Pages 173–194, 2018.

OPTIMIZATION OF 3D PROCESSING PARAMETERS USED FDM METHOD IN THE PRODUCTION OF ABS BASED SAMPLES

Yıl 2022, Cilt: 6 Sayı: 2, 236 - 249, 31.08.2022
https://doi.org/10.46519/ij3dptdi.1126200

Öz

Manufacturing with 3D printers is a very complex process due to many input parameters. This situation makes it difficult to determine optimum production parameters. In this study; hen the production of ABS materials with the fused deposition method (FDM) in 3D printers, the effects of process parameters, which are infill density (50%, 70%, and 90%), fill pattern (linear, octagonal and honeycomb), and layer thickness (0.19mm, 0.29mm and 0.39mm) were investigated on surface roughness, tensile strength, and manufacturing times by analysis of variance (ANOVA). The most effective process parameter on the output parameters was the layer thickness. While the decreasing layer thickness had a positive effect on the surface roughness and tensile strength, it had a negative effect on the manufacturing time. In the experiments carried out according to the Taguchi L27 (33) experimental design, since three different output parameters were evaluated in the optimization process, the gray relational degree was used as the evaluation criterion in the multiple performance optimizations. The optimum processing parameter was determined as linear fill pattern, 90% infill density and 0.19 mm layer thickness.

Kaynakça

  • 1. Mohan, N., Senthil, P., Vinodh, S., Jayanth, N., “A review on composite materials and process parameters optimisation for the fused deposition modelling process”, Virtual and Physical Prototyping, Vol. 12, Issue 1, Pages 47–59, 2017.
  • 2.Rashid, A., “Additive manufacturing technologies. in: The international academy for production engineering” CIRP Encyclopedia of Production Engineering, Pages 20 – 45, Springer, Berlin, 2019.
  • 3. Ngo, T.D., Kashani, A., Imbalzano, G., Nguyen, K.T.Q., Hui, D., “Additive manufacturing (3D printing): A review of materials, methods, applications and challenges”, Composites Part B: Engineering, Vol. 143, Pages 172–196, 2018.
  • 4. ISO/ASTM International, “ISO/ASTM 52900: Additive manufacturing - General principles and Terminology”, International Standard, Pages 1–26, 2015.
  • 5. Walker, J.L., Santoro, M., “Processing production of bioresorbable polymer scaffolds for tissue engineering. In: Bioresorbable polymers for biomedical applications”, Pages 181-203, Woodhead Publishing, United Kingdom, 2017.
  • 6. Agarwal, K.M., Shubham, P., Bhatia, D., Sharma, P., Vaid, H., Vajpeyi, R., “Analyzing the ımpact of print parameters on dimensional variation of abs specimens printed using fused deposition modelling (FDM)”, Sensors International, Vol. 3, Pages 100149 – 100157, 2022.
  • 7. 3D printing market size & share | analysis report (2021-2028), https://www.fortunebusinessinsights.c om/industry-reports/3d-printing-market-101902, March 5, 2022
  • 8. Jaisingh Sheoran, A., Kumar, H., “Fused Deposition modeling process parameters optimization and effect on mechanical properties and part quality: Review and reflection on present research”, Materials Today: Proceedings, Vol. 21, Pages 1659–1672, 2020.
  • 9. Vyavahare, S., Teraiya, S., Panghal, D., Kumar, S., “Fused deposition modelling: a review”, Rapid Prototyping Journal, Vol. 26, Issue 1, Pages 176–201, 2020. 10. Mohamed, O.A., Masood, S.H., Bhowmik, J.L., “Optimization of fused deposition modeling process parameters: a review of current research and future prospects”, Advances in Manufacturing, Vol. 3, Issue 1, Pages 42–53, 2015.
  • 11. Turner, B.N., Strong, R., Gold, S.A., “A review of melt extrusion additive manufacturing processes: I. Process design and modeling”, Rapid Prototyping Journal, Vol. 20, Issue 3, Pages 192–204, 2014. 12.Z-ABS_Technical_Data_Sheet,https://cf.zortrax. com/wpcontent/uploads/2018/06/Z-ABS_Technical _ Data_Sheet_eng-1.pdf, March 10, 2022.
  • 13. Solomon, I.J., Sevvel, P., Gunasekaran, J., “A review on the various processing parameters in FDM”, Materials Today: Proceedings, Vol. 37, Pages 509–514, 2020.
  • 14. Günay, M., Gündüz, S., Yılmaz, H., Yaşar, N., Kaçar, R., “PLA Esaslı Numunelerde Çekme Dayanımı İçin 3D Baskı İşlem Parametrelerinin Optimizasyonu,” Journal of Polytechnic, Cilt 23, Sayı 1, Sayfa 73–79, 2019.
  • 15. Alafaghani, A., Qattawi, A., Alrawi, B., Guzman, A., “Experimental Optimization of Fused Deposition Modelling Processing Parameters: A Design-for-Manufacturing Approach”, Procedia Manufacturing, Vol. 10, Pages 791–803, 2017.
  • 16. Baich, L., Manogharan, G., Marie, H., “Study of infill print design on production cost-time of 3D printed ABS parts”, International Journal of Rapid Manufacturing, Vol. 5, Issue 3/4, Pages 308–319, 2015.
  • 17. Anitha, R., Arunachalam, S., Radhakrishnan, P., “Critical parameters influencing the quality of prototypes in fused deposition modelling”, Journal of Materials Processing Technology, Vol. 118, Issue 1–3, Pages 385–388, 2001.
  • 18. De Toro, E.V., Sobrino, J.C., Martínez, A.M., Eguía, V.M., “Analysis of the influence of the variables of the fused deposition modeling (FDM) process on the mechanical properties of a carbon fiber-reinforced polyamide”, Procedia Manufacturing, Vol. 41, Pages 731–738, 2019.
  • 19. Z-SUITE 2: Print Preparation, https://support.zortrax.com/pdf/create/steps.php?id=27770, March 12, 2022.
  • 20. Christodoulou, I.T., Alexopoulou, V.E., Karkalos, N.E., Papazoglou, E.L. and Markopoulos, A.P., “On the surface roughness of 3d printed parts with fdm by a low-budget commercial printer”, Cutting & Tools in Technological System, Vol. 96, Pages 52–64, 2022.
  • 21. Uzun, G., “Analysis of grey relational method of the effects on machinability performance on austempered vermicular graphite cast irons”, Measurement, Vol. 142, Pages 122–130, 2019.
  • 22. Acır, A., Canlı, M.E., Ata, İ. and Çakıroğlu, R., “Parametric optimization of energy and exergy analyses of a novel solar air heater with grey relational analysis”, Applied Thermal Engineering, Vol. 122, Pages 330–338, 2017.
  • 23. Mia, M., Rifat, A., Tanvir, M.F., Gupta, M.K., Hossain, M.J., Goswami, A., “Multi-objective optimization of chip-tool interaction parameters using Grey-Taguchi method in MQL-assisted turning”, Measurement, Vol. 129, Pages 156–166, 2018.
  • 24.Lin, C.L., “Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics”, Materials and Manufacturing Processes, Vol. 19, Issue 2, Pages 209–220, 2004.
  • 25. Mishra, P.C., Das, D.K., Ukamanal, M., Routara, B.C. and Sahoo, A.K., “Multi-response optimization of process parameters using Taguchi method and grey relational analysis during turning AA 7075/SIC composite in dry and spray cooling environments”, International Journal of Industrial Engineering Computations, Vol. 6, Issue 4, Pages 445–456, 2015.
  • 26. Tzeng, C.-J., Lin, Y.-H., Yang, Y.-K. and Jeng, M.-C., “Optimization of turning operations with multiple performance characteristics using the Taguchi method and Grey relational analysis”, Journal of Materials Processing Technology, Vol. 209, Issue 6, Pages 2753–2759, 2009.
  • 27. Sarikaya, M., Güllü, A., “Multi-response optimization of minimum quantity lubrication parameters using Taguchi-based grey relational analysis in turning of difficult-to-cut alloy Haynes 25”, Journal of Cleaner Production, Vol. 91, Pages 347–357, 2015. 28. Ramesh, K., Baranitharan, P., Sakthivel, R., “Investigation of the stability on boring tool attached with double impact dampers using Taguchi based Grey analysis and cutting tool temperature investigation through FLUKE-Thermal imager”, Measurement, Vol. 131, Pages 143–155, 2019.
  • 29. Mia, M., Rifat, A., Tanvir, M.F., Gupta, M.K., Hossain, M.J., Goswami, A., “Multi-objective optimization of chip-tool interaction parameters using Grey-Taguchi method in MQL-assisted turning”, Measurement, Vol. 129, Pages 156–166, 2018.
  • 30. Zerti, O., Yallese, M.A., Zerti, A., Belhadi, S., Girardin, F., “Simultaneous improvement of surface quality and productivity using grey relational analysis based taguchi design for turning couple (AISI D3 steel/ mixed ceramic tool (Al2O3 + TiC))”, International Journal of Industrial Engineering Computations, Vol. 9, Issue 2, Pages 173–194, 2018.
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Musa Bilgin 0000-0001-8482-8291

Erken Görünüm Tarihi 22 Temmuz 2022
Yayımlanma Tarihi 31 Ağustos 2022
Gönderilme Tarihi 4 Haziran 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 6 Sayı: 2

Kaynak Göster

APA Bilgin, M. (2022). ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU. International Journal of 3D Printing Technologies and Digital Industry, 6(2), 236-249. https://doi.org/10.46519/ij3dptdi.1126200
AMA Bilgin M. ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU. IJ3DPTDI. Ağustos 2022;6(2):236-249. doi:10.46519/ij3dptdi.1126200
Chicago Bilgin, Musa. “ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU”. International Journal of 3D Printing Technologies and Digital Industry 6, sy. 2 (Ağustos 2022): 236-49. https://doi.org/10.46519/ij3dptdi.1126200.
EndNote Bilgin M (01 Ağustos 2022) ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU. International Journal of 3D Printing Technologies and Digital Industry 6 2 236–249.
IEEE M. Bilgin, “ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU”, IJ3DPTDI, c. 6, sy. 2, ss. 236–249, 2022, doi: 10.46519/ij3dptdi.1126200.
ISNAD Bilgin, Musa. “ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU”. International Journal of 3D Printing Technologies and Digital Industry 6/2 (Ağustos 2022), 236-249. https://doi.org/10.46519/ij3dptdi.1126200.
JAMA Bilgin M. ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU. IJ3DPTDI. 2022;6:236–249.
MLA Bilgin, Musa. “ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU”. International Journal of 3D Printing Technologies and Digital Industry, c. 6, sy. 2, 2022, ss. 236-49, doi:10.46519/ij3dptdi.1126200.
Vancouver Bilgin M. ABS ESASLI NUMUNELERİN 3D YAZICI İLE ÜRETİLMESİNDE İŞLEM PARAMETRELERİNİN OPTİMİZASYONU. IJ3DPTDI. 2022;6(2):236-49.

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