Areal Surface Roughness Optimization of Maraging Steel Parts Produced by Hybrid Additive Manufacturing

Abstract

We report on an experimental study and statistical optimization of the surface roughness using design of experiments and the Taguchi method for parts made of 1.2709 maraging steel. We employ a hybrid additive manufacturing approach that combines additive manufacturing by selective laser melting with subtractive manufacturing using milling in an automated process within a single machine. Input parameters such as laser power, scan speed, and hatching distance have been varied in order to improve surface quality of unmachined surfaces. Cutting speed, feed per tooth, and radial depth of cut have been varied to optimize surface roughness of the milled surfaces. The surfaces of the samples were characterized using 3D profilometry. Scan speed was determined as the most important parameter for non-machined surfaces; radial depth of cut was found to be the most significant parameter for milled surfaces. Areal surface roughness S a could be reduced by up to 40% for unmachined samples and by 23% for milled samples as compared to the prior state of the art.

Design Rules for Hybrid Additive Manufacturing Combining Selective Laser Melting and Micromilling

“…Thus, injection molds get manufactured by conventional milling so far, ensuring a high surface quality. Though, the objective of this study is to identify design rules, it can be stated that, in general, the surface roughness Ra of the hybrid approach is better than m for vertical and horizontal surfaces [ 34 ]. In case of curved geometries, like shown in Figure 19 , this value raises slightly to Ra = m.…”

“…The study is performed processing maraging tool steel 1.2709. As the focus of this study is on design rules, we applied previously optimized, standard process parameters for the SLM (see Table 1 ) [ 34 ].…”

“…Without this fundamental knowledge, the described hybrid process may not be used to full capacity. Wüst et al report on an experimental study to optimize the surface roughness of hybrid additive manufactured parts [ 34 ], with particular focus on optimization of both SLM and milling to improve the vertical and horizontal surfaces. As the described hybrid process bears the opportunity to adapt the surface properties in dependence of the local required quality, it is crucial to define precise threshold values.…”

Optimization of Process Parameters for Additively Produced Tool Steel 1.2709 with a Layer Thickness of 100 μm

“…Furthermore, this study states the significant influence of the preheating process of 200 °C in the production of the material H13. Wüst et al [ 17 ] optimized the process parameters for SLM technology concerning surface quality. By choosing the optimal parameters, it was possible to reduce the roughness of the skin surfaces to Sa = 9.0 μm, which corresponds to a reduction of 40% compared to the manufacturer’s recommendations.…”

Challenges in a Hybrid Fabrication Process to Generate Metallic Polarization Elements with Sub-Wavelength Dimensions

“…Typical subtractive, material-removing, processes are, e.g., laser modification and removal [ 1 , 2 ], laser ablation [ 3 , 4 ], laser micro-drilling [ 5 , 6 ], laser cutting [ 7 , 8 ], and laser structuring [ 9 , 10 ]. Laser-based additive manufacturing encompasses, most commonly, stereolithography [ 11 , 12 ], selective laser melting [ 13 , 14 , 15 ], laser sintering [ 16 , 17 ], or laser metal deposition [ 18 , 19 ]. In addition to these, predominantly for macroscopic components employed technologies, additive manufacturing has been advanced to a technology that is capable of generating structures in the sub-micrometer range through the use of ultrashort pulse lasers.…”