Surface roughness prediction using measured data and interpolation in layered manufacturing

Layered manufacturing (LM) technology can efficiently fabricate 3D physical models without the restriction of geometric complexities. However, because of the LM process itself, the surface quality of processed parts is often unsatisfactory compared to that of machined parts made using traditional numerically controlled manufacturing technology. Hence, the surface roughness has become a matter of utmost concern despite the many potential advantages of LM. In the initial step of the LM process, reasonable process planning can be achieved by predicting the surface roughness in advance. Therefore, we propose an elaborate methodology to predict the surface roughness of LM processed parts. Theoretical and real characteristics of surface roughness distributions are investigated to reflect actual roughness distributions in the predictions, and a roughness distribution expression that can obtain surface roughness values for all surface angles is introduced using measured roughness data and interpolation. A prediction application is presented, and the validity and effectiveness of the proposed approach are demonstrated through several application examples.