Full Length Research Paper
References
Ambrogio,G, Filice L, Shivpuri R and Umbrello D (2008). Application of NN technique for predicting the in-depth residual stresses during hard machining of AISI 52100 steel. Int. J. Mater. Forming 1:39–45. Crossref |
||||
American Society for Testing and Materials (2007). Standard test methods for small clear specimens of timber. ASTM D 143-94. Annual Book of ASTM Standards, 2008. Section 4, Construction Vol. 04.10. West Philadelphia, PA, USA. pp. 20-52 | ||||
American Society for Testing and Materials (2004). Standard test methods for conducting machining tests of wood and wood-base materials. ASTM D 1666-87. Annual Book of ASTM Standards 2008. Section 4, Construction Vol. 04.10. West Philadelphia, PA, USA. pp. 201-219. | ||||
Basheer AC, Dabade UA, Suhas SJ, Bhanuprasad VV (2008). Modeling of surface roughness in precision machining of metal matrix composites using ANN. J. Mater. Process Technol. 197:439–444 Crossref |
||||
Beaty WT (1983). Preparing wood for finishing: Finishing eastern hardwoods. Forest Products Research Society, Wisconsin, USA. pp. 15–28. | ||||
Benardos PG, Vosniakos GC (2002). Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments. Robot Comput. Integr. Manuf. 18:343–354 Crossref |
||||
Benardos PG, Vosniakos GC (2003). Predicting surface roughness in machining: a review. Int. J. Machine Tools Manuf. 43:833–844 Crossref |
||||
Chang CK, Lu HS (2006). Study on the prediction model of surface roughness for side milling operations. International Journal of Advanced Manufacturing Technology 29:867–878 Crossref |
||||
Correa M, Bielza C, Pamies-Teixeira J (2009). Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process. Expert Syst. Appl. 36 (3):7270–7279 Crossref |
||||
Cus F, Zuperl U (2006). Approach to optimization of cutting conditions by using artificial neural networks. J. Mater. Process Technol. 173:281–290. Crossref |
||||
DIN 4760 (1982). Form deviations, concepts, classification system. Deutches Institut Fuer Normung, Ev, Berlin, Germany. | ||||
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. | ||||
Farmer RH (1972). Handbook of hardwoods, 2nd ed. Department of Environment, Building Research Establishment, Princess Risborough Laboratory. HMSO, London. pp. 3-152. | ||||
Farrokhpayam SR, Ratnasingam J, Bakar ES, Tang SH (2010). Characterizing Surface Defects of Solid Wood of Dark Red Meranti (Shorea sp.), Melunak (Pentace sp.) and Rubberwood (Hevea brasiliensis) in Planing Process. J. Appl. Sci. 10:915-918. Crossref |
||||
Field A (2007). Harvesting an Underwater Forest. Sloan Fellows find a triple-bottom-line business in West Africa. Stanford Graduate School of Business News. 76(1):12-14. |
||||
Fortin Y (2001). Wood machining properties of white spruce from plantation forests. For. Prod. J. 51(6): 4-15. | ||||
Fujiwara Y, Fujii Y, Sawada Y and Okumura S (2001). Development of a parameter to reflect the roughness of a wood surface that corresponds to tactile toughness: A novel filter to exclude local valley effects. Holz als Roh-und Werkstoff 59(5): 351-355. Crossref |
||||
Gilmore R, Barefoot AC (1974). Evaluation of some tropical woods imported into the United States from South America. Forest Prod. J. 24(2):24-28 | ||||
Gurau L, Mansfield-Williams H and Irle M (2005). Processing roughness of sanded wood surfaces. Holz als Roh-und Werkstoff. 63:43-52. Crossref |
||||
Hendarto B, Shayan E, Ozarska B, Carr R (2006). Analysis of roughness of a sanded wood surface. Int. J. Adv. Manufacturing Technol. 28: 775-780 Crossref |
||||
Hiziroglu S, Kosonkorn P (2006). Evaluation of surface roughness of Thai medium density fiberboard (MDF). Building and Environment 41(4): 527–533. Crossref |
||||
Karpat Y, Özel T (2007). Multi-objective optimization for turning processes using neural network modeling and dynamic neighborhood particle swarm optimization. Int. J. Adv. Manuf. Technol. 35:234–247 Crossref |
||||
MalkoçoÄŸlu A (2007). Machining properties and surface roughness of various wood species planed in different conditions. Build. Environ. 42(7):2562–2567. Crossref |
||||
MalkoçoÄŸlu A, Özdemir T (2006). The machining properties of some hardwoods and softwoods naturally grown in Eastern Black Sea region of Turkey. J. Mater. Process. Technol. 173(3):315–320. Crossref |
||||
Nemli G, Akbulut T, Zekoviç E (2007). Effects of some sanding factors on the surface roughness of particleboard. Silva Fennica 41(2): 373–378.) Crossref |
||||
Nemli G, Ozturk I, Aydın I (2005). Some of the parameters influencing surface roughness of particleboard. Build. Environ. 40(10):1337–1340. Crossref |
||||
NPA (1993). From start to finish particleboard. National Particleboard Association. Gaithersburg, MD 20879. | ||||
Oktem H, Erzurumlu T, Erzincanli F (2006). Prediction of minimum surface roughness in end milling mold parts using neural network and genetic algorithm. Mater. Des. 27:735–744. Crossref |
||||
Ors Y, Baykan I (1999). The effect of planing and sanding on the surface roughness. Turk. J. Agric. For. 23(3): 577-582. | ||||
Oteng-Amoako AA (2006). 100 Tropical African Timber trees from Ghana: Tree description and wood identification with notes on distribution, ecology, silviculture, ethnobotany and wood uses. Graphic Packaging, Accra, Ghana. 304pp. | ||||
Owusu FW, Ayarkwa J, Frimpong-Mensah K (2011). The sanding properties of seven Ghanaian lesser-used timber species. Ghana J. For. 28(1):1-14. | ||||
Pal SK, Chakraborty D (2005). Surface roughness prediction in turning using artificial neural network. Neural Comput. Appl. 14:319–324 Crossref |
||||
Ratnasingam J, Scholz F (2007). Characterizing surface defects in machine-planing of rubberwood (Hevea brasiliensis). Holz Roh-und Werkst65: 327–327. | ||||
Roger EH, Cool J (2008). Effects of cutting parameters on surface quality of paper birchwood machined across the grain with two planing techniques. Holz Roh-und Werkst. 66: 147-154. Crossref |
||||
Sandak J, Tanaka C (2005). Evaluation of surface smoothness using a light sectioning shadow scanner. J. Wood Sci. 51(3): 270-273. Crossref |
||||
Sieminski R, Skarzynska A (1989). Surface roughness of different species of wood after sanding. For. Prod. J. 32:98-107. | ||||
Skaljic N, Beljo-Lucic R, Cavlovic A, Obucina M (2009). Effect of Feed Speed and Wood Species on Roughness of Machined Surface. Drvna Industrija 60(4):229-234. | ||||
SofuoÄŸlu SD, KurtoÄŸlu A (2014). Some machining properties of four wood species grown in Turkey. Turk. J. Agric. For. 38:420-427. Crossref |
||||
Sogutlu C, Togay A (2011). The effect of the process parameters in the planing processes on the surface roughness of cherry and pear woods. Afr. J. Biotechnol. 10(21):4392-4399. | ||||
Tamizharasan T, Sevaraj T, Haq AN (2006). Analysis of tool wear and surface finish in hard turning. Int. J. Adv. Manuf. Technol. 28:671–679. Crossref |
||||
Tan PL, Safian S, Izman S (2012). Roughness models for sanded wood surfaces. Wood Sci. Technol. 46(1-3):129-142. Crossref |
||||
Taylor JB, Carrano AL, Lemaster RL (1999). Quantification of process parameters in a wood sanding operation. For. Prod. J. 49(5): 41-46. | ||||
Tjernlund C (1984). Guidance on machining Whitewood. A report on work carried out for the Swedish Institude for Wood Technology Research. Swedish-Finnish Timber Council, Retford, Notts, England, U.K. 45pp. | ||||
Copyright © 2024 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0