Influence of toolpath strategies during laser polishing on additively manufactured biomaterials
Source abstract
Abstract
Nowadays, Additive Manufacturing ( AM), i.e., the 3D Printing process, is one of the advanced manufacturing processes for making a complex geometry with high accuracy. Additive manufacturing processes are widely used worldwide and are the fastest-growing industrial technology, as any complex structure with minimal wastage of materials can be fabricated. However, poor surface quality is a major limitation of additive manufacturing due to surface defects, including unmelted powder particles, balling, porosity, etc. Laser polishing utilizes remelting and reflowing of the surface irregularities under the influence of a high-power laser source to efficiently improve the surface quality of the additively manufactured parts. Herein, a thin layer of the surface is molten, and because of surface tension, molten material flows from the peak into the valley with no loss of material from the surface. Laser polishing is a CNC-operated surface finishing method, hence an appropriate toolpath strategy is required to produce uniform surface quality on the polished surface. In the present work, the impact of various toolpath strategies, i.e., raster, offset flat, contour parallel, Hilbert, Peano, and spiral, over the final surface quality is analyzed during the laser polishing. The maximum 92% reduction in average surface roughness with uniform surface quality is observed with a fractal-based toolpath strategy, i.e., Peano with improved surface hardness. Moreover, laser polishing is capable of reducing all surface defects from the fabricated surface, as observed from the scanning electron microscope. Furthermore, an insignificant change in the surface composition of the material is observed after the laser polishing.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · Additive Manufacturing and 3D Printing Technologies · Laser Material Processing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty Fellow, Indian Institute of Technology Guwahati, TIH, Guwahati, India
Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, India
Funding
Science & Engineering Research Board (SERB), New Delhi, India
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