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Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method

Year 2024, Volume: 7 Issue: 5, 946 - 953, 15.09.2024
https://doi.org/10.34248/bsengineering.1529803

Abstract

In this study, the optimization of the parameters used in the engraving process of wooden birch plywood material with a CO2 laser machine was investigated using the Taguchi method. An industrial laser machine with a 150W glass tube was used during the experimental examination process. There are basic factors affecting the engraving process of wooden surfaces such as laser power (P), engraving speed (S) and laser head parts (F). The engraving depth (D) and engraving width formed on the surface during the engraving process are the main factors that determine the aesthetics of the product. Taguchi L25 orthogonal array was used in the experiments to determine and optimize the highly important parameters. The optimum combination of parameters in the laser engraving process was then evaluated. The research results showed that the effect of P and S factors played a leading role, and the F parameter had a small effect on the depth of wood scraping. Optimization results found that F:5, S:100 and P:30 gave the best engraving depth optimization, while F:6, S:300 and P:10 gave the lowest engraving depth optimization result.

References

  • Aniszewska M, Maciak A, Zychowicz W, Zowczak W, Mühlke T, Christoph B, Lamrini S, Sujecki S. 2020. Infrared laser application to wood cutting. Mat, 13(22): 5222.
  • Barnekov V, McMillin C, Huber H. 1986. Factors influencing laser cutting of wood. For Prod J, 1: 36.
  • Çakıroğlu EO, Aydın İ, Demir A. 2018. Comparison of mechanical properties of contractplanks produced from birch and local beech tombs imported from coastal countries to the Black Sea. J Black Sea Res Inst, 4(6): 353-359.
  • Çavdar K, Tanrısever T. 2013. Laser cutting of different materials. J Uludag Univ Fac Eng, 18(2): 79-99.
  • Eltawahni H, Olabi AG, Benyounis K. 2011. Investigating the CO2 laser cutting parameters of MDF wood composite material. Opt Laser Technol, 43(3): 648-659.
  • Gabdrakhmanov A, Bobrishev A, Shafigullin L. 2019. Application of the laser cutting of wood-containing materials in construction. In IOP Conference Series: Mat Sci Eng. IOP Publishing. 481(1): 12-45.
  • Gökçe H. Ersin Ç. 2020. Investigation of the loudness and vibrations occurred during the drilling of custom 450 stainless steel in terms of cutting parameters. Elect Lett Sci Eng, 16(2): 171-183.
  • Güneş M, Ersin Ç, Altunok M. 2024. Effect of climate and wood type on elastic modulus of heat-treated wood and its optimisation by the Taguchi method. BioRes, 19(2): 3138-3148.
  • Kubovský I, Krišťák Ľ, Suja J, Gajtanska M, Igaz R, Ružiak I, Réh R. 2020. Optimization of parameters for the cutting of wood-based materials by a CO2 laser. Appl Sci, 10(22), 8113.
  • Kúdela J, Kubovský I, Andrejko M. 2020. Surface properties of beech wood after CO2 laser engraving. Coat, 10(1): 76-77.
  • Kurt R, Can A. 2021. Optimisation of the effect of accelerated weathering conditions on wood surfaces via the Taguchi method. BioRes, 16(1): 1642.
  • McMillin CW, Conners RW, Huber HA. 1984. ALPS-a potential new automated lumber processing system. For Prod J, 34(1): 13-20.
  • Mehat NM. Kamaruddin S. 2012. Quality control and design optimisation of plastic product using Taguchi method: a comprehensive review. Int J Plast Tech, 16: 194-209.
  • Nguyen V, Altarazi F, Tran T. 2022. Optimisation of process parameters for laser cutting process of stainless steel 304: a comparative analysis and estimation with Taguchi method and response surface methodology. Math Probl Eng, 1: 1-14.
  • Oğurlu İ. 2024. Doğal-Ekolojik üç yapi malzemesi taş-kerpiç–ahşap için sürdürebilirlik analiz modeli. Avr Bilim Tekno Der, 53: 150-167.
  • Phadke MS. 1995. Quality engineering using robust design. USA, Prentice Hall PTR, USA, 1st ed., pp: 1-250.
  • Roy R.K. 2010. A primer on the Taguchi method. Society of manufacturing engineers, USA, 2nd ed., pp: 1-10.
  • Ružiak I, Igaz R, Kubovský I, Gajtanska M, Jankech A. 2022. Prediction of the effect of CO2 laser cutting conditions on spruce wood cut characteristics using an artificial neural network. Appl Sci, 12(22): 11355.
  • Shuster JJ. 2007. Design and analysis of experiments. Top Bios, 404: 235-259
  • Sinn G, Chuchała D, Orlowski KA, Taube P. 2020. Cutting model parameters from frame sawing of natural and impregnated Scots pine (Pinus sylvestris L.). Eur J Wood Wood Prod, 78(6): 777-784.
  • Taguchi G, Chowdhury S, Wu Y. 2004. Taguchi's quality engineering handbook. Wiley, New Jersey, USA. 1st ed., pp: 100-125.
  • Tayal M, Barnekov V, Mukherjee K. 1994. Focal point location in laser machining of thick hard wood. J Mater Sci Lett, 13(9): 44-646.
  • Teivonen A. 2016. Laser surgery system. Lahti University of Applied Sciences Degree Programme in Materials Engineering Spring, Lahti, Finland, pp: 23-35.
  • Tunç M. 2015. Investigation of the effects of cutting parameters on surface roughness in CO2 laser cutting machines, MSc Thesis, Karabuk University Institute of Science and Technology, Karabuk, 15-17.
  • Uzungörür M, 2015. Inconel 718 sac malzemelerin lazer ile kesilmesinde işlem parametrelerinin etkilerinin araştırılması. Yüksek Lisans Tezi, Eskişehir Osmangazi Üniversitesi, Fen Bilimleri Enstitüsü, Eskişehir, Türkiye, ss: 61-63
  • Yaka H, Akkuş H, Uğur L. 2016. Optimisation of the effect of cutting parameters on surface roughness in turning of AISI 1040 steel by Taguchi method. Celal Bayar Univ J Sci, 12(2): 283-288.

Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method

Year 2024, Volume: 7 Issue: 5, 946 - 953, 15.09.2024
https://doi.org/10.34248/bsengineering.1529803

Abstract

In this study, the optimization of the parameters used in the engraving process of wooden birch plywood material with a CO2 laser machine was investigated using the Taguchi method. An industrial laser machine with a 150W glass tube was used during the experimental examination process. There are basic factors affecting the engraving process of wooden surfaces such as laser power (P), engraving speed (S) and laser head parts (F). The engraving depth (D) and engraving width formed on the surface during the engraving process are the main factors that determine the aesthetics of the product. Taguchi L25 orthogonal array was used in the experiments to determine and optimize the highly important parameters. The optimum combination of parameters in the laser engraving process was then evaluated. The research results showed that the effect of P and S factors played a leading role, and the F parameter had a small effect on the depth of wood scraping. Optimization results found that F:5, S:100 and P:30 gave the best engraving depth optimization, while F:6, S:300 and P:10 gave the lowest engraving depth optimization result.

References

  • Aniszewska M, Maciak A, Zychowicz W, Zowczak W, Mühlke T, Christoph B, Lamrini S, Sujecki S. 2020. Infrared laser application to wood cutting. Mat, 13(22): 5222.
  • Barnekov V, McMillin C, Huber H. 1986. Factors influencing laser cutting of wood. For Prod J, 1: 36.
  • Çakıroğlu EO, Aydın İ, Demir A. 2018. Comparison of mechanical properties of contractplanks produced from birch and local beech tombs imported from coastal countries to the Black Sea. J Black Sea Res Inst, 4(6): 353-359.
  • Çavdar K, Tanrısever T. 2013. Laser cutting of different materials. J Uludag Univ Fac Eng, 18(2): 79-99.
  • Eltawahni H, Olabi AG, Benyounis K. 2011. Investigating the CO2 laser cutting parameters of MDF wood composite material. Opt Laser Technol, 43(3): 648-659.
  • Gabdrakhmanov A, Bobrishev A, Shafigullin L. 2019. Application of the laser cutting of wood-containing materials in construction. In IOP Conference Series: Mat Sci Eng. IOP Publishing. 481(1): 12-45.
  • Gökçe H. Ersin Ç. 2020. Investigation of the loudness and vibrations occurred during the drilling of custom 450 stainless steel in terms of cutting parameters. Elect Lett Sci Eng, 16(2): 171-183.
  • Güneş M, Ersin Ç, Altunok M. 2024. Effect of climate and wood type on elastic modulus of heat-treated wood and its optimisation by the Taguchi method. BioRes, 19(2): 3138-3148.
  • Kubovský I, Krišťák Ľ, Suja J, Gajtanska M, Igaz R, Ružiak I, Réh R. 2020. Optimization of parameters for the cutting of wood-based materials by a CO2 laser. Appl Sci, 10(22), 8113.
  • Kúdela J, Kubovský I, Andrejko M. 2020. Surface properties of beech wood after CO2 laser engraving. Coat, 10(1): 76-77.
  • Kurt R, Can A. 2021. Optimisation of the effect of accelerated weathering conditions on wood surfaces via the Taguchi method. BioRes, 16(1): 1642.
  • McMillin CW, Conners RW, Huber HA. 1984. ALPS-a potential new automated lumber processing system. For Prod J, 34(1): 13-20.
  • Mehat NM. Kamaruddin S. 2012. Quality control and design optimisation of plastic product using Taguchi method: a comprehensive review. Int J Plast Tech, 16: 194-209.
  • Nguyen V, Altarazi F, Tran T. 2022. Optimisation of process parameters for laser cutting process of stainless steel 304: a comparative analysis and estimation with Taguchi method and response surface methodology. Math Probl Eng, 1: 1-14.
  • Oğurlu İ. 2024. Doğal-Ekolojik üç yapi malzemesi taş-kerpiç–ahşap için sürdürebilirlik analiz modeli. Avr Bilim Tekno Der, 53: 150-167.
  • Phadke MS. 1995. Quality engineering using robust design. USA, Prentice Hall PTR, USA, 1st ed., pp: 1-250.
  • Roy R.K. 2010. A primer on the Taguchi method. Society of manufacturing engineers, USA, 2nd ed., pp: 1-10.
  • Ružiak I, Igaz R, Kubovský I, Gajtanska M, Jankech A. 2022. Prediction of the effect of CO2 laser cutting conditions on spruce wood cut characteristics using an artificial neural network. Appl Sci, 12(22): 11355.
  • Shuster JJ. 2007. Design and analysis of experiments. Top Bios, 404: 235-259
  • Sinn G, Chuchała D, Orlowski KA, Taube P. 2020. Cutting model parameters from frame sawing of natural and impregnated Scots pine (Pinus sylvestris L.). Eur J Wood Wood Prod, 78(6): 777-784.
  • Taguchi G, Chowdhury S, Wu Y. 2004. Taguchi's quality engineering handbook. Wiley, New Jersey, USA. 1st ed., pp: 100-125.
  • Tayal M, Barnekov V, Mukherjee K. 1994. Focal point location in laser machining of thick hard wood. J Mater Sci Lett, 13(9): 44-646.
  • Teivonen A. 2016. Laser surgery system. Lahti University of Applied Sciences Degree Programme in Materials Engineering Spring, Lahti, Finland, pp: 23-35.
  • Tunç M. 2015. Investigation of the effects of cutting parameters on surface roughness in CO2 laser cutting machines, MSc Thesis, Karabuk University Institute of Science and Technology, Karabuk, 15-17.
  • Uzungörür M, 2015. Inconel 718 sac malzemelerin lazer ile kesilmesinde işlem parametrelerinin etkilerinin araştırılması. Yüksek Lisans Tezi, Eskişehir Osmangazi Üniversitesi, Fen Bilimleri Enstitüsü, Eskişehir, Türkiye, ss: 61-63
  • Yaka H, Akkuş H, Uğur L. 2016. Optimisation of the effect of cutting parameters on surface roughness in turning of AISI 1040 steel by Taguchi method. Celal Bayar Univ J Sci, 12(2): 283-288.
There are 26 citations in total.

Details

Primary Language English
Subjects Optimization Techniques in Mechanical Engineering, Optimization in Manufacturing
Journal Section Research Articles
Authors

Mehmet Güneş 0000-0002-1222-7590

Çağatay Ersin 0000-0001-5018-9313

Early Pub Date September 3, 2024
Publication Date September 15, 2024
Submission Date August 7, 2024
Acceptance Date September 2, 2024
Published in Issue Year 2024 Volume: 7 Issue: 5

Cite

APA Güneş, M., & Ersin, Ç. (2024). Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method. Black Sea Journal of Engineering and Science, 7(5), 946-953. https://doi.org/10.34248/bsengineering.1529803
AMA Güneş M, Ersin Ç. Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method. BSJ Eng. Sci. September 2024;7(5):946-953. doi:10.34248/bsengineering.1529803
Chicago Güneş, Mehmet, and Çağatay Ersin. “Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters With Taguchi Method”. Black Sea Journal of Engineering and Science 7, no. 5 (September 2024): 946-53. https://doi.org/10.34248/bsengineering.1529803.
EndNote Güneş M, Ersin Ç (September 1, 2024) Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method. Black Sea Journal of Engineering and Science 7 5 946–953.
IEEE M. Güneş and Ç. Ersin, “Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method”, BSJ Eng. Sci., vol. 7, no. 5, pp. 946–953, 2024, doi: 10.34248/bsengineering.1529803.
ISNAD Güneş, Mehmet - Ersin, Çağatay. “Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters With Taguchi Method”. Black Sea Journal of Engineering and Science 7/5 (September 2024), 946-953. https://doi.org/10.34248/bsengineering.1529803.
JAMA Güneş M, Ersin Ç. Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method. BSJ Eng. Sci. 2024;7:946–953.
MLA Güneş, Mehmet and Çağatay Ersin. “Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters With Taguchi Method”. Black Sea Journal of Engineering and Science, vol. 7, no. 5, 2024, pp. 946-53, doi:10.34248/bsengineering.1529803.
Vancouver Güneş M, Ersin Ç. Optimization of Wood-Based Birch Plywood CO2 Laser Engraving Process Parameters with Taguchi Method. BSJ Eng. Sci. 2024;7(5):946-53.

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