Determination of Machining Parameters Affecting Surface Roughness of MDF Using the Taguchi and RSM Methods

Abstract

In this study, the influence of the machining parameters on surface roughness of MDF machined on a CNC router based on machining parameters such as feed rate, spindle speed,, depth of cut and depth of cut) was investigated with Taguchi and Response surface method (RSM) metod.  Taguchi L₁₆ orthogonal array has was used for experiments design. The significant machining parameters effect on surface roughness were analyzed with the analysis of signal to noise ratios (S/N), ANOVA, main effect graphs of means and 3 D surface plots.   Mathematical prediction models of the effects of processing parameters on surface roughness were developed using response surface methodology (RSM). it was observed that the main effects of factors (depth of cut , feed rate, spindle speed) on roughness were found to be statistically significant, although interaction of factors has no effect on surface roughness.  It was found that surface roughness value increased with increasing feed rate and depth of cut and decreasing spindle speed. The better surface roughness values were obtained at 25000 mm/min of feed rate, 24000 rpm of spindle speed and 4 mm of depth of cut.  

Keywords

• surface roughness,surface milling,Taguchi

Kaynakça

1. 1. Bardak, T, Bardak, S., and Sözen, E., (2017). Determination of strain distributions of solid wood and plywood in bending test by digital image correlation. Kastamonu Uni., Orman Fakültesi Dergisi, 2017, 17 (2): 354-361
2. 2. Debnath, S., Reddy MM, Yi QS (2016) Influence of cutting fluid conditions and cutting parameters on surface roughness and tool wear in turning process using Taguchi method. Measurement 78:111–119
3. 3. Funck, J. W., Forrer, J. B., Buttler, D. A., Brunner, C. C., and Maristany, A. G. (1992). Measuring surface roughness on wood: A comparison of laser-scatter and stylus-tracing approaches, The International Society for Optical Engineering (SPIE) 1821, 173-184. DOI: 10.1117/12.145533.
4. 4. Gupta, A., Jordan, P.J., and Pang, S. (2006). “Modelling of vertical density profile of MDF in hot pressing”. In: Proceedings of CHEMECA 2006: Knowledge and Innovation, CHEMECA, Auckland, New Zealand,17–20.
5. 5. Haq, S., and Srivastava, R. (2016). Measuring the influence of materials composition on nano scale roughness for wood plastic composites by AFM, Measurement 91, 541-547. DOI: 10.1016/j.measurement.2016.05.095
6. 6. Hazir, E., Erdinler, E.S., and Koc, K.H. (2018). “Optimization of CNC cutting parameters using design of experiment (DOE) and desirability function”. Journal of Forest Research, 29(5):1423–1434.
7. 7. Hazir. E., and Özcan, T. (2018). Response Surface Methodology Integrated with Desirability Function and Genetic Algorithm Approach for the Optimization of CNC Machining Parameters. Arabian Journal for Science and Engineering, pp 1–15.
8. 8. Hızıroğlu, S. (1996). Surface roughness analysis of wood composites: A stylus method, Forest Products Journal 46(7/8), 67-72.

9. 9. Koc, K.H., Erdinler, E.S., Hazir, E., and Öztürk, E. (2017). “Effect of CNC application parameters on wooden surface quality”. Measurement, 107,12–18.
10. 10. Magoss, E. (2008). “General regularities of wood surface roughness”. Acta Silv. Lign. Hung., 4, 81-93.
11. 11. Malkoçoğlu, A. (2007). “Machining properties and surface roughness of various wood species planed in different conditions”. Building and Environment, 42, 2562-2567.
12. 12. Palanikumar K., and Valarmathi, T.N. 2016, Experimental Investigation and Analysis on Thrust Force in Drilling of Wood Composite Medium Density Fiberboard Panels. Experimental Techniques, 40: 391– 400.
13. 13. 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, 33-42.
14. 14. Sofuoglu, S.D. 2015. Determination of optimal machining parameters of massive wooden edge-glued panels made of European larch (Larix Decidua Mill) using Taguchi method BioResources, 10 (4) , 7772-7781.
15. 15. Sütçü A. (2013). “Investigation of parameters affecting surface roughness in CNC routing operation on wooden EGP”. BioResources, 8, 795–805.
16. 16. Sütçü, A., and Karagöz, Ü. (2012). “Effect of Machınıng Parameters On Surface Qualıty After Face Milling of MDF”, Wood Research, 57 (2), 231-240.
17. 17. Sütçü, A., and Karagöz, Ü. (2013). “The influence of process parameters on the surface roughness in aesthetic machining of wooden edge-glued panels (EGPs)”. BioResources, 8(4): 5435-5448.
18. 18. Tiryaki, S., Malkoçoğlu, A., and Özşahin, Ş., (2014).Using artificial neural networks for modeling surface roughness of wood in machining process. Construction and Building Materials 66 (2014) 329–335
19. 19. V.N. Gaitonde, S.R. Karnik, J.P. Davim, 2008. Taguchi multi-performance characteristics optimization in drilling of medium density fibreboard (MDF) to minimize delamination using utility concept. J. Mater. Process. Tech., 196 (2008), pp. 73-78.
20. 20. Zhong, Z. W., Hiziroglu, S., and Chan, C. T. M. (2013). “Measurement of the surface roughness of wood based materials used in furniture manufacture,” Measurement 46(4), 1482-1487.