Mobilya Endüstrisinde Kullanılan Tropik Kökenli Bazı Ağaç Türlerinin En İyi Yüzey Pürüzlüğü, Islanabilirlik ve Enerji Tüketimi için CNC Parametrelerinin Belirlenmesi

Yıl 2024, Cilt: 9 Sayı: 4, 806 - 815, 31.12.2024

Evren Osman Çakıroğlu , Ümit Büyüksarı , Taner Taşdemir

https://doi.org/10.35229/jaes.1583056

Öz

Bu çalışmada, en iyi ahşap yüzey kalitesi, ıslanabilirliği, enerji tasarrufu için CNC kesim koşullarının belirlenmesi amaçlanmıştır. Ahşap malzeme olarak iroko (Chlorophora excelsa) ve sapelli (Entandrophragma cylindricum Sprague) kullanılmış olup ayrı üç bıçak çapı 3-6-8 (mm), devir hızı 12000-15000-18000 (devir/dk) ve kesme hızı 3000-6000-9000 (mm/dk) belirlenmiştir. CNC makinesi ile kesim işlemleri tamamlandıktan sonra tüm gruplar için enerji tüketimi belirlenmiştir. Yüzey pürüzlülüğü ve ıslanabilirlik testleri yapılarak yüzey kaliteleri değerlendirilmiştir. Elde edilen veriler istatistiksel olarak analiz edilerek optimum kesme koşulları oluşturulmuştur. İroko en az yüzey pürüzlülüğüne (3,41 µm) sahiptir. En düzgün yüzeyler iroko ve sapelli örnekleri için sırasıyla kesici takım çapı 8-3 (mm), devir hızı 18000-12000 (devir/dk), kesme hızı ise her iki türde de 3000 mm/dk olarak ölçülmüştür. Islanabilme konusunda iroko daha kötü sonuçlar vermektedir. Elde edilen değerler iroko (98,85º) ve sapelli (82,44º) olarak ölçülmüştür. En iyi ıslanabilme durumu sırasıyla kesici takım çapı, devir hızı ve kesme hızına göre iroko da; 3mm-12000 devir/dk- 9000 mm/dk, 6mm-18000 devir/dk- 9000 mm/dk, 8mm-15000 devir/dk- 9000 mm/dk’dır. Sapelli de; 3mm-18000 devir/dk- 9000 mm/dk, 6mm-12000 devir/dk- 3000 mm/dk, 8mm-12000 devir/dk- 6000 mm/dk’dır. Ayrıca, en düşük elektrik tüketimi yüksek kesme hızlarında ölçülmüştür.

Anahtar Kelimeler

Ahşap, CNC, Yüzey pürüzlülüğü, Islanabilirlik.

Determination of CNC Parameters for the Best Surface Roughness, Wettability, Energy Consumption of Some Wood Species of Tropical Origin Used in the Furniture Industry

Öz

The aim of this study is to determine the CNC cutting conditions for the best wood surface quality, wettability and energy saving. Iroko (Chlorophora excelsa) and sapele (Entandrophragma cylindricum Sprague) were used as wood materials and three separate blade diameters were determined as 3-6-8 (mm), rotation speed as 12000-15000-18000 (revolution/min) and cutting speed as 3000-6000-9000 (mm/min). After the cutting processes were completed with the CNC machine, energy consumption was determined for all groups. Surface roughness and wettability tests were performed and surface qualities were evaluated. The obtained data were analyzed statistically and optimum cutting conditions were established. Iroko has the least surface roughness (3.41 µm). The smoothest surfaces for iroko and sapelli samples were measured as cutting tool diameter 8-3 (mm), rotation speed 18000-12000 (rev/min) and cutting speed 3000 mm/min for both types, respectively. Iroko gives worse results in terms of wettability. The values obtained were measured as iroko (98.85º) and sapelli (82.44º). The best wettability status according to cutting tool diameter, rotation speed and cutting speed is 3mm-12000 rev/min- 9000 mm/min, 6mm-18000 rev/min- 9000 mm/min, 8mm-15000 rev/min- 9000 mm/min for iroko, respectively. In sapelli; 3mm-18000 rpm- 9000 mm/min, 6mm-12000 rpm- 3000 mm/min, 8mm-12000 rpm- 6000 mm/min. Also, the lowest electricity consumption was measured at high cutting speeds.

Anahtar Kelimeler

Wood, CNC, surface roughness, wettability.

Kaynakça

• Aguilera, A., Meausoone, P. J. & Martin P. (2000). Wood material influence in routing operations: the MDF case. European Journal of Wood and Wood Products, 58, 278-283. DOI: 10.1007/s001070050425
• Bajić, D., Lela, B., & Živković, D. (2008). Modeling of machined surface roughness and optimization of cutting parameters in face milling. Metalurgija, 47(4), 331-334.
• Bekhta, P. & Krystofiak, T. (2016). The influence of short- term thermo-mechanical densification on the surface wettability of wood veneers, Maderas. Ciencia y Tecnología 18(1), 79-90. DOI: 10.4067/S0718- 221X2016005000008
• Çakıroğlu, E.O., Demir, A., Aydın, İ. & Büyüksarı, Ü. (2022). Prediction of optimum CNC cutting conditions using artificial neural network models for the best wood surface quality, low energy consumption, and time Savings. BioResources, 17(2), 2501. DOI: 10.15376/biores.17.2.2501-2524
• Davim, J.P., Clemente, V.C. & Silva, S. (2009). Surface roughness aspects in milling MDF (medium density fibreboard). International Journal of Advanced Manufacturing Technology, 40(1-2), 49-55. DOI: 10.1007/s00170-007-1318-z
• De Deus, P.R., de Sampaio Alves, M.C. & Vieira, F.H. A.(2015). The quality of MDF workpieces machined in CNC milling machine in cutting speeds, feedrate, and depth of cut. Meccanica, 50(12), 2899-2906. DOI: 10.1007/s11012-015-0187-z
• De Meijer, M., Haemers, S., Cobben, W. & Militz, H. (2000). Surface energy determinations of wood: Comparison of Methods and Wood Species Langmuir, 16 (2000), 9352-9359. DOI: 10.1021/la001080n
• Demir, A., Cakiroglu, E.O. & Aydin, (2022). I Determination of CNC processing parameters for the best wood surface quality via artificial neural network. Wood Material Science & Engineering, 17(6), 685-692. DOI: 10.1080/17480272.2021.1929466
• Dumanoğlu, F. & Bal, B.C.(2022). Cnc Makinesi ile İşlenmiş Lif Levhalarin Yüzey Pürüzlülüğü ve İşlem Süresi Üzerine İşleme Parametrelerinin Etkileri. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 25(4), 615-621. DOI: 10.17780/ksujes.1144224
• Fang, Q., Cui, H.W. & Du, G.B. (2016). Surface wettability, surface free energy, and surface adhesion of microwave plasma-treated Pinus yunnanensis wood. Wood Science and Technology, 50(2), 285-296. DOI: 10.1007/s00226-015-0793-x
• Fountas, N., Kimpenis, A., Vaxevanidis, N. & Davim, J. P. (2012). Single and multi-objective optimization methodologies in CNC machining. In Statistical and Computational Methods in Manufacturing. Springer, 187-218. DOI: 10.1007/978-3-642-25859-6_5
• Gindl, M. & Tschegg, S. (2012). Significance of the acidity of wood to the surface free energy components of different wood species. Langmuir, 18(8), 3209- 3212. DOI: 10.1021/la011696s
• Gindl, M., Reiterer A., Sinn, G. & Stanzl-Tschegg, S.E. (2004).Effects of surface ageing on wettability, surface chemistry, and adhesion of wood. Holz Roh Werkst, 62(4), 273-280. DOI: 10.1007/s00107-004- 0471-4
• Gürgen, A., Çakmak, A., Yildiz, S. & Malkoçoğlu A. (2022). Optimization of CNC operating parameters to minimize surface roughness of Pinus sylvestris using integrated artificial neural network and genetic algorithm. Maderas. Ciencia y Tecnología, 24(1), 5. DOI: 10.4067/s0718-221x2022000100401
• Hazir, E. & Koc, K.H. (2019). Optimization of wood machining parameters in CNC routers: Taguchi orthogonal array based simulated angling algorithm, Maderas. Ciencia y Tecnología, 21(4), 493-510. DOI: 10.4067/S0718-221X2019005000406
• Hazir, E. & Ozcan T. (2019). Response surface methodology integrated with desirability function and genetic algorithm approach for the optimization of CNC machining parameters. Arabian Journal for Science and Engineering, 44(3), 2795-2809. DOI: 10.1007/s13369-018-3559-6
• Hazir, E., Erdinler, E.S. & Koc, K.H. (2018). Optimization of CNC cutting parameters using design of experiment (DOE) and desirability function. Journal of Forestry Research, 29, 1423-1434. DOI: 10.1007/s11676-017-0555-8
• Iskra, P. & Hernandez, R. E. (2009). The influence of cutting parameters on the surface quality of routed paper birch and surface roughness prediction modeling. Wood and Fiber Science, 28-37.
• Karagöz, U. (2011). CNC ile işlemede ahşap malzemenin yüzey kalitesini etkileyen faktörler. Kastamonu Üniversitesi Orman Fakültesi Dergisi, 11(1), 18-26, 2011.
• Karagoz, U., Akyildiz, M.H. & Isleyen, O. (2011). Effect of heat treatment on surface roughness of thermal wood machined by CNC. Pro Ligno, 7(4), 50-58.
• Kopač, J. & Šali, S. (2003). Wood: an important material in manufacturing technology. Journal of materials processing technology, 133(1-2), 134-142. DOI: 10.1016/S0924-0136(02)00217-0
• Krimpenis, A.A. & Vosniakos G.C. (2009). Rough milling optimisation for parts with sculptured surfaces using genetic algorithms in a Stackelberg game, Journal of Intelligent Manufacturing, 20(4), 447-461. DOI: 10.1007/s10845-008-0147-8
• Li, C., Li ,L., Tang, Y., Zhu, Y. & Li, L.(2019). A comprehensive approach to parameters optimization of energy-aware CNC milling. Journal of Intelligent Manufacturing, 30, 123-138. DOI: 10.1007/s10845- 016-1233-y
• Ohuchı, T. & Murase, Y. (2005). Milling of wood and wood- based materials with a computerized numerically controlled router IV: development of automatic measurement system for cutting edge profile of throw-away type straight bit. Journal of Wood Science, 51, 278-281. DOI: 10.1007/s10086-004- 0663-x
• Özşahin, Ş. (2012). The Use Of An Artificial Neural Network For Modeling The Moisture Absorption And Thickness Swelling Of Oriented Strand Board, BioRes., 7(1), 1053-1067. DOI: 10.15376/biores.7.1.1053-1067
• Rathke, J. &Sinn, G. (2013). Evaluating the wettability of MUF resins and pMDI on two different OSB raw materials. European Journal of Wood and Wood Products, 71(3), 335-342. DOI: 10.1007/s00107- 013-0675-6
• Stanojevic, D., Mandic, M., Danon, G. & Svrzic, S. (2017). Prediction of the surface roughness of wood for machining. Journal of Forestry Research, 28(6), 1281-1283. DOI: 10.1007/s11676-017-0401-z
• Supadarattanawong, S. & Rodkwan, S. (2006). An investigation of the optimal cutting conditions in Parawood (Heavea Brasiliensis) machining process on a CNC wood router. Agriculture and Natural Resources, 40(5), 311-319.
• Suresh, R., Basavarajappa, S., Gaitonde, V. N. & Samuel, G. L. (2012). Machinability investigations on hardened AISI 4340 steel using coated carbide insert. International Journal of Refractory Metals and Hard Materials, 33, 75-86. DOI: 10.1016/j.ijrmhm.2012.02.019
• Sutcu, A. (2013). Investigation of parameters affecting surface roughness in CNC routing operation on wooden EGP. BioResources, 8(1), 795-805. DOI: 10.15376/biores.8.1.795-805
• URL-1 (2023). Deutsches Institut für Norming DIN 4768, Determination of Values of Surface Roughness Parameters Ra, Rz, Rmax Using Electrical Contact (Stylus) Instruments, Concepts and Measuring Conditions, Germany, May, 1990.
• https://www.scribd.com/document/465303105/DIN -4768-1-RUGOSIDAD, erişim tarihi: Aralık 5, 2023 URL-2. (2024). https://www.alphacam.com/ALPHACAM- router/, erişim tarihi: Ekim 10, 2024
• Yaghoubi, S. & Rabiei, F. (2023). Investigating the CNC milling machine parameters and machining tool specifications on surface roughness of wooden products. Journal Of Applied and Computational Sciences in Mechanics, 35(3), 65-74.
• Yavaşcı, E., Kardökmak, A.Ş. & Demirsöz, R. (2022). Talaşlı imalatta kesme hızı, ilerleme ve kesme derinliği değişkenlerinin torna tezgâhı güç tüketimi üzerine etkileri. Çelik Araştırma ve Geliştirme Dergisi, 3(1), 17-24.