Determination of the Surface Roughness Values of Turkish Red Pine (Pinus brutia (Ten.)) Woods
Murat Kılıç *
The aim of this study was to determine the surface roughness values of Turkish red pine samples obtained from the seven natural growth areas in Turkey. The samples were cut with a circular saw, planed with a thickness machine, and sanded with a sanding machine (with No. 80 sandpaper). After the samples were processed as radial and tangential surfaces in the machines, their surface roughness values (Ra, Ry, and Rz) were measured in accordance with ISO 4288 (1996). According to the statistical results, the lowest surface roughness values were in the samples obtained from the Muğla and Samsun areas on the tangential surfaces that were processed with the thickness machine.
Keywords: Surface roughness; Turkish red pine; Pinus brutia Ten woods; Wood machining; Cutting directions
Contact information: Kırıkkale University, Faculty of Fine Arts, Department of Interior Architecture & Environment Design, Yahsihan, Kırıkkale, Turkey; *Corresponding author: email@example.com
Wood materials have many uses in construction and furniture production. While the most important aspects in the selection of wood materials for the construction sector are the mechanical properties, the aesthetic and mechanical properties are important for the material used in furniture (Aslan et al. 2008).
Surface roughness is the most important property in wood material used in furniture production. Surface roughness affects the quality of furniture because aesthetic concerns are significant in this industry (Ilter et al. 2002; Salca and Hiziroglu 2014; Söğütlü et al. 2016).
Among the methods used to minimize surface roughness, the most important one is increasing the number of machine cutters and processing wood materials in the low feed speed (Hiziroglu and Suchsland 1993; Hiziroglu 1996). Another successful method for processing wood in the direction of cutting involves usage of a down-milling machine. The results obtained in applications carried out tangentially are known to give better results compared to application carried out radially (Kılıç et al. 2006; Kılıç 2015; Kılıç 2016).
In the cutting, planing, and sanding processes of wood material, the accurate selection of processing conditions is very important to avoid undesired negative results, primarily surface roughness. Roughness on the wood surface can be minimized with additional precautions, such as increasing the knife and rotation numbers in the machines used to process wood (Pelit et al. 2015; Tiryaki et al. 2015).
The growth area of Turkish red pine (Pinus brutia (Ten.)) is expanding throughout the world and within Turkey. This species has a high economical value and is a principal tree species for Turkey. Forests covered an area of 21,678,134 hectares in Turkey in 2014, which was 27.6% of the country’s total area. Turkish red pine has an expansion area of 5,854,673 hectares (General Directory of Forestry 2014). The Turkish red pine is one of the most important primary tree species in Turkey. Therefore, the study of its basic wood properties is a top priority.
The surface roughness of wood material does not directly affect the surface roughness processes or the bonding resistance. Currently, there are no reports on the surface roughness values of Turkish red pine. For this reason, determining the surface roughness of the Turkish red pine wood is the subject of this study (Fig. 1).
Fig. 1. The importance of surface roughness in the processing of furniture
In the evaluation of surface roughness, three parameters are widely used. These are Ra, which is the average deviation of the profile; Rz, which is the average of the height of the irregularity at 10 points, and Ry, which is the highest level of the profile.
The experiment materials were selected from areas in Adana-Pos, Antalya-Düzlerçamı, Burdur-Bucak, Mersin-Silifke, Samsun-Bafra, Kahramanmaraş-Topçam, and Muğla-Kıyra, which are Turkish red pine natural growth areas in Turkey. For each region, a total of 21 trees from 7 different areas were selected (3 trees per area). The trees were cut in accordance with ISO 4471 (1982). Information about the areas is presented in Table 1.
The trial materials were cut to dimensions of 60 x 500 mm and placed in an environmental test chamber until air-dried humidity (12%) was reached. (Table 2).
The effect of three different surface processing types on Turkish red pine was determined using two cutting directions, tangential, and radial.
Two cutting directions (radial and tangential) and three surface treatment techniques (cutting by circular saw, planning, and sanding) were used in this work, and 300 measurements were taken with 50 test repetitions (2 x 3 x 50=300). In total, 2100 surface roughness measurements were performed for the seven different areas.
As the final process for the Turkish red pine, the samples were planed with a thickness machine three blades (4500 rev/min), cut with a 40-tooth circular saw machine (diameter 30 cm) (6000 rev/min), and sanded with a caliber sanding machine (with No: 80 sandpaper).
Table 1. Information Related to Origins
*(Ilter et al. 2011)
During sample processing, the feeding rate was fixed at 10 m/min. Surface roughness values were measured with a Mitutoyo SJ-301 device (Kawasaki, Japan), which measures with the stylus method, in accordance with ISO 4288 (1996) (Fig. 2). The surface roughness was measured on the fibers in a perpendicular direction with a ± 0.01 μm sensitivity (measurement speed 0.5 m/sec; cut-off wavelength (lc) 4 mm; measurement length (lt) 21 mm; diamond tip stylus; tip angle 90°/tip; and radius 2 m) in accordance with ISO 4288 (1996).
Table 2. Properties of Experimental Trees
*(Ilter et al. 2011)
Fig. 2. Surface profilometer used in this study
With the purpose of presenting the effects of Region, Machine, and Cutting Direction (the main effect, double and triple interactions) on Ra, Ry, and Rz, the Univarite General Linear statistical model was used, and analysis was carried out. For the multiple comparisons of the factors that were considered to be statistically important as a result of the overall F-test of each measurement, the Tukey HSD test was used. A statistical error with an importance level of type one has been determined as α=0.05. In terms of determining the difference effect level, Partial Eta squared statistics was used. The Partial Eta squared parameter indicates the level of effect and it is considered that as its value becomes closer to 1, the effect level increases.
RESULTS AND DISCUSSION
Evaluation of the Data Obtained for Ra (Average Roughness)
The statistical values and the results of the Tukey test according to the areas calculated for the average surface roughness (Ra) are presented in Table 3.
While the area, machine types, and cutting directions affected the Ra value, their double and triple effects were statistically significant in terms of the Ra value as well. In Table 3, the Partial Eta Squared effect value for Ra was found to be highest in Machine. According to the results of Tukey’s tests for the areas, the lowest average surface roughness values were in Samsun (Ra = 5.16 m), Muğla (Ra = 5.17 m), and K. Maraş (Ra = 5.30 m). There was no significant difference in the surface roughness values of these three areas.
The lowest average surface roughness value according to machine types was determined in the thickness machine (Ra = 4.54 m), followed by the sanding machine (Ra = 5.26 m), and the circular saw (Ra = 7.28 m) (Table 4). When the statistical values were analyzed in terms of the cutting directions, the average surface roughness values of the tangentially cut samples were lower than the radially cut samples (RaTangential = 5.53m, RaRadial = 5.86m) (Table 4).
The Ra values determined in previous studies are lower in tangential surfaces than in the radial surfaces as well (Table 5).
Table 4. Statistical Values for Ra According to Machine Type and Cutting Direction
Evaluation of the Data Obtained for Ry (Rmax) (Maximum Roughness)
The statistical values and the results of the Tukey test according to areas calculated for Ry are presented in Table 6. Areas, machine types, and cutting directions affected the Ry value; however their double and triple effects were statistically significant in terms of the Ry value as well.
In Table 6, when the Partial eta squared value was analyzed for Ry, it was seen that the effect of machine was higher. According to the results of the Tukey’s tests for the areas, the lowest average surface roughness values were in Muğla (Ry = 38.51 m), Samsun (Ry = 39.04 m), and K. Maraş (Ry = 39.04 m). There was no statistical difference between the surface roughness of these three areas.
Table 5. The Ra Values Determined in Previous Studies
The lowest average surface roughness value according to machine types was determined in the thickness machine (Ry = 35.84 m), followed by the sanding machine (Ry = 40.78 m), and the circular saw (Ry = 50.46 m) (Table 7). When the statistical values were analyzed in terms of the cutting directions, the Ry surface roughness values of the tangentially cut samples were seen to be lower than the radially cut samples (Ry Tangential = 41.58m, Ry Radial = 42.73m) (Table 7).
Evaluation of the Data Obtained for Rz (Mean Peak-to-valley Height)
The statistical values and the results of the Tukey’s test according to areas calculated for Rz are presented in Table 9. The areas, machine types, and cutting directions affected the Rz value; however, their double and triple effects were statistically significant in terms of the Rz value as well.
In Table 9, the Partial Eta squared effect for Rz was found the highest in Machine. According to Tukey’s test for the areas, the lowest average surface roughness values were in Samsun (Rz = 30.44 m) and Muğla (Rz = 30.48 m). There was no statistical difference between these two areas’ surface roughness values.
The lowest average ten-point height surface roughness values (Rz) in terms of machine types were found in the thickness machine (Rz = 27.59 m), followed by sanding machine (Rz = 29.78 m), and the circular saw (Rz = 41.19 m) (Table 10). When the statistical values were analyzed in terms of the cutting directions, the Rz surface roughness values of the tangentially cut samples were lower than the radially cut samples (Rz Tangential = 32.50 m, Rz Radial = 33.22 m) (Table 8).
Table 6. Variance Analysis and Tukey’s Test for Ry According to Region
Table 8. Statistical Values for Rz According to Machine Type and Cutting Direction
Table 9. Variance Analysis and Tukey’s Test for Rz According to Region
- Turkish red pine trees were selected from areas in Adana, Antalya, Burdur, Mersin, Samsun, Kahramanmaraş, and Muğla, which are natural growth areas in Turkey. The lowest surface roughness values were obtained from the samples taken from the Muğla and Samsun areas.
- The samples obtained from the Turkish red pine were processed with the most common surface processing techniques in the wood processing sector: sawing with a circular saw, planing with a thickness machine, and sanding with a sanding machine (No. 80 sandpaper). After the samples were processed radially and tangentially, their roughness values (Ra, Ry, and Rz) were determined. When the statistical results of surface roughness values were analyzed, the lowest surface roughness values were obtained in the Turkish red pine samples that were processed with the thickness machine.
- The Partial Eta Squared effect level values for Ra, Ry, and Rz were the highest in Machine type. The variable with the second highest value level after Machine type was Region.
- In Muğla and Samsun regions, the reason why the lowest surface roughness values were obtained might be related to density and the growth area of the samples. In future studies, it might be useful to analyze the red pine trees in these areas anatomically.
- The roughness values of the tangentially cut surfaces were determined to be lower than the radially cut surfaces. Burdurlu et al. (2006) have also determined that the Ra values of tangentially cut samples of red pine trees were lower than the values of radially cut surfaces. In the same manner, the Ra values of surfaces processed with the thickness machine were found to be lower compared to surfaces sanded with no: 80 sandpaper (Table 5). The results are in line with this study.
- An important aspect of this study lay in determining the surface roughness of Turkish red pine samples selected from the seven natural growth areas in Turkey and introducing these results to literature.
The author is grateful for the support of the Turkey General Directorate of Forestry, Central Anatolia Forestry Research Institute, Grant. No. 23.7132/2009-2015.
Aslan, S., Coskun, H., and Kılıç, M. (2008). “The effect of the cutting direction, number of blades and grain size of the abrasives on surface roughness of Taurus cedar (Cedrus libani A. Rich.) woods,” Building and Environment 43, 696-701. DOI: 10.1016/j.buildenv.2007.01.048
Burdurlu, E., Kılıç, Y., Eli̇bol, G. C., and Kılıç, M. (2006). “The shear strength of Calabrian pine (Pinus brutia (Ten.)) bonded with polyurethane and polyvinyl acetate adhesives,” Journal of Applied Polymer Science 99, 3050-3061. DOI: 10.1002/app.22905
General Directory of Forestry (2014). The Presence of Forest Turkey, GDF Publications, Ankara, Turkey.
İlter, E., and Balkız, O. (2005). “Determination of surface roughness values of eucalyptus (Eucalyptus camaldulensis Dehn.),” Technical Bulletin No. 283, Central Anatolia Forestry Research Instıtute, Ankara, Turkey.
İlter, E., Çamlıyurt, C., and Balkız, O. (2002). Researches on the Determination of the Surface Roughness Values of Bornmullerian fir (Abies bornmülleriana (Mattf.)) (Technical Bulletin No. 281), Central Anatolia Forestry Research Institute, Ankara, Turkey.
İlter, E., Saraçbaşı A., and Balkız, O. (2011). “Determination of Technological Properties of some Red pine Origins (Technical Bulletin No. 281), Central Anatolia Forestry Research Institute, Ankara, Turkey.
Hiziroglu, S. (1996). “Surface roughness analysis of wood composites: A stylus method,” Forest Products Journal 46(7-8), 67-72.
Hiziroglu, S., and Suchsland, O. (1993). “Linear expansion and surface stability of particleboard,” Forest Products Journal 43(4), 31-34.
ISO 4471 (1982). “Wood – Sampling sample tree and logs for determination of physical and mechanical properties of wood homogeneous stands,” International Organization for Standardization, Geneva, Switzerland.
ISO 4288 (1996). “Geometrical product specifications (GPS) – Surface texture: Profile method rules and procedures for the assessment of surface texture,” International Organization for Standardization, Geneva, Switzerland.
Kılıç, M., Hızıroğlu, S., and Burdurlu, E. (2006). “Effect of machining on surface roughness of wood,” Building and Environment 41(8), 1074-1078. DOI: 10.1016/j.buildenv.2005.05.008.
Kılıç, M. (2015). “Effects of machining methods on the surface roughness values of Pinus nigraArnold wood,” BioResources 10(3), 5554-5562. DOI: 10.15376/biores.10.3.5554-5562.
Kılıç, M. (2016). “Effect on shear strength of machining methods in Pinus nigra Arnold bonded with polyurethane and polyvinyl acetate adhesives,” BioResources 11(3), 6663-6676. DOI: 10.15376/biores.10.3.6663-6676.
Pelit, H., Budakçı, M., Sönmez, A., and Burdurlu, E. (2015). “Surface roughness and brightness of scots pine (Pinus sylvestris) applied with water-based varnish after densification and heat treatment,” Journal of Wood Science 61(6), 586-594. DOI: 10.1007/s10086-015-1506-7
Salca, E. A., and Hiziroglu, S. (2014). “Evaluation of hardness and surface quality of different wood species as function of heat treatment,” Materials & Design 62, 416-423. DOI: 10.1016/j.matdes.2014.05.029.
Söğütlü, C., Nzokou, P., Koc, I., Tutgun, R., and Döngel, N. (2016). “The effects of surface roughness on varnish adhesion strength of wood materials,” Journal of Coatings Technology & Research 13(5), 863-870. DOI: 10.1007/s11998-016-9805-5.
Tiryaki, S., Bardak, S., and Bardak, T. (2015). “Experimental investigation and prediction of bonding strength of Oriental beech (Fagus orientalis Lipsky) bonded with polyvinyl acetate adhesive,” Journal of Adhesion Science and Technology 29(23), 2521-2536. DOI: 10.1080/01694243.2015.1072989
Article submitted: September 10, 2016; Peer review completed: October 29, 2016; Revised version received: November 1, 2016; Further input: December 22, 2016; Accepted: December 27, 2016; Published: January 4, 2017.