Akademik Veri Yönetim Sistemi
International Journal of Scientific Research Engineering & Technology (IJSRET), cilt.5, sa.10, ss.494-501, 2016 (Hakemli Dergi)
The prediction of optimal machining conditions for wood surface quality play a very important role in process
planning for furniture industry. In this study a mathematical model was developed to predict the surface roughness and
to determine optimal machining condition of European Black pine (Pinus nigra Arnold). Design of experiment was
used to study the effect of CNC machining parameters such as spindle speed, feed rate and depth of cut on arithmetic
average roughness (Ra). The optimization process was adopted by a combined approach of
central composite face-centered (CCFC) experimental design and response surface methodology (RSM). The second
order mathematical models in terms of machining parameters were developed for surface roughness using response
surface methodology. The results indicate that the most effective parameters were found in the interaction between
feed rate and spindle speed, and their contribution to the model value was 62.41 % on the surface roughness. To
achieve the minimum surface roughness, the optimum values obtained for spindle speed, feed rate and depth of cut
were 18000 rpm, 2 m/min and 2.646 mm, respectively.