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BibTex RIS Kaynak Göster
Yıl 2019, Cilt: 4 Sayı: 4, 598 - 601, 31.12.2019
https://doi.org/10.35229/jaes.635310

Öz

Kaynakça

  • Cool, J. & Hernandez, R.,E., (2011). Improving the sanding process of Black spruce wood for surface quality and water-based coating adhesion. For. Prod. J., 61, 372–380.
  • Davim, J.,P., Clemente, V.,C. & Silva, S., (2009). Surface roughness aspects in milling MDF (medium density fiberboard). Int. J. Adv. Manuf. Technol., 40, 49–55.
  • DIN 4768, (1990). Determination of Values of Surface Roughness Parameters Ra, Rz, Rmax Using Electrical Contact (Stylus) Instruments, Concepts and Measuring Conditions. Deutsches Institut für Norming, Berlin, Germany.
  • Ginting, R., Hadiyoso, S. & Aulia, S., (2017). Implementation 3-Axis CNC Router for Small Scale Industry. International Journal of Applied Engineering Research, 12(17), 6553-6558.
  • Iskra, P. & Tanaka, C., (2005). The influence of wood fiber direction, feed rate, and cutting width on sound intensity during routing. Holz Roh-Werkst, 63, 167–172.
  • Jayachandraiah, B., Krishna, O., V., Khan, P., A. & Reddy, R., A. (2014). Fabrication of Low Cost 3-Axis CNC Router. Int. J. Eng. Sci. Invent., 3(6), 1–10.
  • Koc, K., H., Erdinler, E., S., Hazir, E. & Ozturk, E., (2017). Effect of CNC application parameters on wooden surface quality. Measurement, 107, 12-18.
  • Nas, E., Samtas, G. & Demir, H. (2012). Mathematical modelling of parameters effecting surface roughness via CNC routers. J. Eng. Sci., 18, 47–59.
  • Ozdemir, T., Hiziroglu, S. & Kocapınar, M., (2015). Adhesion strength of cellulosic varnish coated wood species as function of their surface roughness. Adv. Mater. Sci. Eng., 1–5.
  • Raja, S., B. & Baskar, N., (2011). Particle swarm optimization technique for determining optimal machining parameters of different work piece materials in turning operation. Int. J. Adv. Manuf. Technol., 54, 445–463.
  • Sofuoglu, S., D., (2017). Determination of optimal machining parameters of massive wooden edge glued panels which is made of Scots pine (Pinus sylvestris L.) using Taguchi design method. European Journal of Wood and Wood Products, 75(1), 33-42.
  • Sutcu, A., (2013). Investigation of parameters affecting surface roughness in CNC routing operation on wooden EGP. BioResources, 8, 795–805.
  • Sutcu, A. & Karagoz, U., (2012). Effect of machining parameters on surface quality after face milling of MDF. Wood Res., 57, 231–240.
  • Tan, P., L., Sharif, S. & Sudin, I., (2012). Roughness models for sanded wood surfaces. Wood Sci. Technol., 46, 129–142.
  • Wilkowski, J., Czarniak, P. & Grzes´kiewicz, M., (2011). Machinability evaluation of thermally modified wood using the Taguchi technique, in: COST Action FP0904 Workshop Mechano-Chemical Transformations of Wood during Thermo-Hydro-Mechanical (THM) Processing, pp. 109–111.
  • Zhong, Z.,W., Hiziroglu, S. & Chan, C., T., M., (2013). Measurement of the surface roughness of wood based materials used in furniture manufacture. Measurement, 46, 1482–1487.

Determination of the Optimum Feed Rate and Spindle Speed Depending on the Surface Roughness of Some Wood Species Processed with CNC Machine

Yıl 2019, Cilt: 4 Sayı: 4, 598 - 601, 31.12.2019
https://doi.org/10.35229/jaes.635310

Öz

In modern furniture
industry, CNC machines are widely used, especially when high quality of product
and flexibility of manufacturing process are expected. Even though there are
many advanced computer-aided manufacturing systems for furniture producers, it
is difficult to set process parameters according to obtain desired material
surface properties because wood is a natural polymeric material with a
heterogeneous structure. Wood surface properties are affected both material and
machining factors, such as wood species, anatomical characteristics, moisture
content, grain direction, feed rate, spindle speed, cutting depth, and tool
geometry. In this study, it was aimed to determine of the optimum feed rate and
spindle speed depending on the surface roughness of some wood species processed
with CNC machine. Spruce, chestnut, larch and iroko were used as wood species.
Three spindle speed (10000, 14000 and 18000 rpm) and feed rate (5000, 7000 and
9000 mm/min) were determined for CNC processing. The surface roughness (Rz) of
wood samples were determined according to DIN 4768 standard. As a result of the
study, the lowest surface roughness values were found in 10000 rpm spindle
speed and 5000 mm/min feed rate for spruce and chestnut wood and 18000 rpm
spindle speed and 7000 mm/min feed rate for larch and iroko wood. The highest
values in the all of wood species were obtain from 10000 rpm spindle speed and
9000 mm/min feed rate.

Kaynakça

  • Cool, J. & Hernandez, R.,E., (2011). Improving the sanding process of Black spruce wood for surface quality and water-based coating adhesion. For. Prod. J., 61, 372–380.
  • Davim, J.,P., Clemente, V.,C. & Silva, S., (2009). Surface roughness aspects in milling MDF (medium density fiberboard). Int. J. Adv. Manuf. Technol., 40, 49–55.
  • DIN 4768, (1990). Determination of Values of Surface Roughness Parameters Ra, Rz, Rmax Using Electrical Contact (Stylus) Instruments, Concepts and Measuring Conditions. Deutsches Institut für Norming, Berlin, Germany.
  • Ginting, R., Hadiyoso, S. & Aulia, S., (2017). Implementation 3-Axis CNC Router for Small Scale Industry. International Journal of Applied Engineering Research, 12(17), 6553-6558.
  • Iskra, P. & Tanaka, C., (2005). The influence of wood fiber direction, feed rate, and cutting width on sound intensity during routing. Holz Roh-Werkst, 63, 167–172.
  • Jayachandraiah, B., Krishna, O., V., Khan, P., A. & Reddy, R., A. (2014). Fabrication of Low Cost 3-Axis CNC Router. Int. J. Eng. Sci. Invent., 3(6), 1–10.
  • Koc, K., H., Erdinler, E., S., Hazir, E. & Ozturk, E., (2017). Effect of CNC application parameters on wooden surface quality. Measurement, 107, 12-18.
  • Nas, E., Samtas, G. & Demir, H. (2012). Mathematical modelling of parameters effecting surface roughness via CNC routers. J. Eng. Sci., 18, 47–59.
  • Ozdemir, T., Hiziroglu, S. & Kocapınar, M., (2015). Adhesion strength of cellulosic varnish coated wood species as function of their surface roughness. Adv. Mater. Sci. Eng., 1–5.
  • Raja, S., B. & Baskar, N., (2011). Particle swarm optimization technique for determining optimal machining parameters of different work piece materials in turning operation. Int. J. Adv. Manuf. Technol., 54, 445–463.
  • Sofuoglu, S., D., (2017). Determination of optimal machining parameters of massive wooden edge glued panels which is made of Scots pine (Pinus sylvestris L.) using Taguchi design method. European Journal of Wood and Wood Products, 75(1), 33-42.
  • Sutcu, A., (2013). Investigation of parameters affecting surface roughness in CNC routing operation on wooden EGP. BioResources, 8, 795–805.
  • Sutcu, A. & Karagoz, U., (2012). Effect of machining parameters on surface quality after face milling of MDF. Wood Res., 57, 231–240.
  • Tan, P., L., Sharif, S. & Sudin, I., (2012). Roughness models for sanded wood surfaces. Wood Sci. Technol., 46, 129–142.
  • Wilkowski, J., Czarniak, P. & Grzes´kiewicz, M., (2011). Machinability evaluation of thermally modified wood using the Taguchi technique, in: COST Action FP0904 Workshop Mechano-Chemical Transformations of Wood during Thermo-Hydro-Mechanical (THM) Processing, pp. 109–111.
  • Zhong, Z.,W., Hiziroglu, S. & Chan, C., T., M., (2013). Measurement of the surface roughness of wood based materials used in furniture manufacture. Measurement, 46, 1482–1487.
Toplam 16 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Evren Osman Çakıroğlu 0000-0001-5303-8967

Aydın Demir 0000-0003-4060-2578

İsmail Aydın 0000-0003-0152-7501

Yayımlanma Tarihi 31 Aralık 2019
Gönderilme Tarihi 21 Ekim 2019
Kabul Tarihi 25 Kasım 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 4 Sayı: 4

Kaynak Göster

APA Çakıroğlu, E. O., Demir, A., & Aydın, İ. (2019). Determination of the Optimum Feed Rate and Spindle Speed Depending on the Surface Roughness of Some Wood Species Processed with CNC Machine. Journal of Anatolian Environmental and Animal Sciences, 4(4), 598-601. https://doi.org/10.35229/jaes.635310


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