Predictive Modelling of Surface Roughness in Layered Manufacturing Using H15N5D4B and KH28M6

Abstract

Layered manufacturing (LM) technology has the capability to fabricate 3D physical models efficiently, overcoming the limitations of geometric complexities. However, the surface quality of LM-processed parts often falls short compared to parts made through traditional numerically controlled manufacturing technology. This issue of surface roughness has become a significant concern, despite the numerous potential advantages offered by LM. To address this, an elaborate methodology is proposed to predict the surface roughness of LM-processed parts. The proposed methodology takes into account both theoretical and real-world characteristics of surface roughness distributions to accurately reflect the actual roughness distributions in the predictions. This methodology was tested and used to evaluate properties of the H15N5D4B and KH28M6 materials. To achieve this, a design of the testing sample was developed, and a roughness distribution expression was introduced, utilizing measured roughness data from the aforementioned sample. This expression allows engineers to obtain surface roughness values for all surface angles, i.e., desired 3D models. The methodology also includes a prediction application, which demonstrates the validity and effectiveness of the proposed approach through several application examples.