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Surface quality improvement for 316L additive manufactured prototype based on magnetorheological polishing

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Abstract. Additive manufacturing has attracted increasing attention in recent years due to its flexibility and near-net shaping advantages. Although recent advancements in metal additive manufacturing accuracy have met the post-processing… Click to show full abstract

Abstract. Additive manufacturing has attracted increasing attention in recent years due to its flexibility and near-net shaping advantages. Although recent advancements in metal additive manufacturing accuracy have met the post-processing requirement for dimensional tolerance, the finishing post-processing of functional surfaces must be further investigated in conjunction with material characteristics. This research aims to investigate the use of a flexible process in the polishing of additive molding samples. As an example, the surface of a 316L stainless steel sample formed by powder bed laser melting was polished using magnetorheological polishing technology. Magnetic field simulation was used to create a longitudinally staggered magnetorheological polishing tool. Surface roughness and residual stress were studied with process parameters such as abrasive content, magnetic particle content, machining gap, and spindle speed. Results show that the polishing effect is better at 4 % and 40 % abrasive and magnetic particles, respectively. The surface roughness Ra is 99 nm when the working gap is 0.6 mm, the surface roughness Ra value is the lowest when the spindle speed is 600 r min−1. The surface roughness was reduced to 61.43 nm after polishing the sample under improved processing conditions (4 % abrasive, 40 % magnetic, 0.6 mm working clearance, 600 r min−1 spindle speed). A nano-scale smooth surface can be obtained by powder bed laser melting and magnetorheological polishing of 316L stainless steel.

Keywords: magnetorheological polishing; surface roughness; surface; surface quality; spindle speed; quality improvement

Journal Title: Mechanical Sciences
Year Published: 2023

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