Surface finishing by laser re-melting applied to robotized laser metal deposition
Introduction
Laser metal deposition (LMD) is an additive manufacturing process employable for producing medium to large components with bulky and thin-walled features. It is especially suited to producing axial-symmetric parts as well as parts developing around an axis. Moreover, LMD can be used both to build new parts or to add features and to repair already existing components [1], [2]. As a matter of fact, LMD has a higher potential of geometric flexibility and accessibility when integrated with robotic manipulation systems [3]. The use of robotic manipulators has proven to be advantageous for employing new deposition strategies that do not rely on the common slicing techniques used for the powder bed fusion processes. The part or the head can be inclined during the process to follow continuous 3D scan trajectories making it possible to generate complex geometries without the need of support structures [4], [5]. However the major drawbacks are the low dimensional accuracy of the robotic system and the poor surface finish resulting from the layer-wise nature of AM processes, as well as the presence of sintered particles on the surface [6], [7]. Therefore, post-processes are usually needed to comply with the geometrical and mechanical requirements.
Several works have shown the influence of processing conditions on the surface quality of LMD produced parts [8], [9], [10]. The surface roughness along the build direction commonly remains at very high values (Ra =20-30 µm and Sa=20-30 µm) for many of the engineering applications. For instance, a rough turning or milling operation would typically produce an average surface roughness in the range of Ra=1-2 µm [11]. Hence, in industrial applications the surface quality of LMD produced parts requires finishing steps, which increase production time and costs [12], [13]. The geometrical flexibility of the LMD process with robotic manipulation systems increases the geometrical complexity of the parts, which also renders the finishing process more difficult. Undercuts and regions that are difficult to reach may limit the use of mass finishing processes as well as chip removal post processing.
The use of hybrid approaches to deposit and finish the workpiece within the same machine is an appealing approach for LMD processed parts to resolve finishing issues related to complex geometries [14]. The machining process can also be used to correct the geometrical deviations if the material allowance is sufficient. On the other hand, process planning between additive and subtractive processes should be carefully applied to the accessibility of the machined regions. The use of laser re-melting as a surface polishing operation is another solution that is intrinsically available to the LMD system. The same laser source used for the deposition process can be employed to polish the surface by re-melting [15], [16], [17], [18]. Concerning additively manufactured components, the use of laser re-melting has been explored more widely for products obtained using powder bed fusion techniques. Despite its high potential to finish complex part geometries, the use of laser re-melting with LMD produced products still requires further attention [19], [20].
One of the issues concerning the finishing of LMD produced surfaces relates to the difficulty in characterizing them. Such surfaces are composed of complex features such as high slopes, undercuts and changes in optical properties that makes it challenging for the measurement instruments to recreate the roughness profile dataset [21]. Moreover, the presence of strong anisotropy given either by the visible layers in vertical surfaces or different tracks in horizontal ones, imposes the necessity to employ 3D acquisitions to obtain a meaningful description of the surface topography [22].
Different and highly detailed standards have been developed over the years to analyse the roughness and waviness of conventionally manufactured surfaces [23], [24], [25]. However, the applicability of these standard surface roughness measurement parameters to additively manufactured complex surfaces is still limited [26]. The use of areal surface roughness measurements, texture analysis methods, and techniques in spectral domain seems to be more appropriate for such purposes [27], [28], [29]. Indeed, a point that requires attention concerning laser re-melting is the fact that this finishing process may also produce a new surface texture. While lowering the roughness and waviness amplitudes of the surface, laser re-melting can also generate a new texture, which can degrade the surface quality.
In literature, the capability of laser re-melting to reduce the surface roughness has been proven when applied to bulky components [30], [31], [32] and thin-walled structures [33]. The re-melting process has also been proposed for modifying and tailoring the microstructure of LMD parts [34]. However, the laser re-melting process has mostly been performed with the use of separate laser sources and/or machines from that used for deposition or it has been performed in a separate step. The effects of the interaction between material and laser beam during the re-melting process have been analysed by Ramos et al. [35]. The authors defined two different working conditions namely, Surface Shallow Melting (SSM) and Surface Over Melting (SOM). The transition zone between the two conditions was the one capable of obtaining the best results in terms of surface roughness reduction. Mathematical models have also been developed to predict the laser-material interaction in the re-melting process [36]. However, the efficacy of these models for predicting the final surface topography is limited due to complex multi-physics phenomena.
An overall analysis of literature shows the need for combining surface characterization and process knowledge to develop a laser re-melting process for finishing needs of freeform LMD components. Accordingly, this work analyses the laser re-melting process applied to thin-walled tubular AISI 316L stainless steel parts produced by LMD. A robotic LMD system was used for both the deposition and the re-melting phases, with a view to adapting this process for freeform structures. Within the work, areal surface measurements were used along with the power spectrum of the surface to understand the texture formation. In particular, the filtering stages were defined to employ the conventional areal average roughness Sa parameter along with a non-conventional waviness parameter on the areal data. An experimental campaign was conducted including the main laser re-melting process parameters, such as laser power and overlap, as well as parameters used to assess the feasibility of reaching restricted zones by employing different scan strategies and inclination angles with a robotic system. The experimental work was conducted to minimize surface roughness and waviness together, while not producing a new surface texture. Finally, the use of re-melting on more complex geometries starting from the optimal results on simple geometries was discussed.
Section snippets
Robotic LMD system and material
Fig. 1 shows the robotic LMD system, namely AddiTube, developed for large area deposition with high geometrical flexibility (BLM Group, Cantù, Italy) [5]. The deposition head positioning was carried out by a 6-axis anthropomorphic robot (ABB IRB 4600-45, Zürich, Switzerland), while a 2 degree freedom positioner (ABB IRBP A-250, Zürich, Switzerland) manipulated the workpiece synchronously. The laser source used was a multimode fibre laser with 3 kW maximum power output (IPG YLS-3000, Cambridge,
Laser re-melting strategies
Laser re-melting was performed with varying scanning strategy and process parameters to study the effect and interaction in the surface quality improvement obtained. At the end of the deposition, the tilting axis of the workpiece positioner was rotated by 90° to place the tube in a horizontal direction and perform the re-melting on top external surface of the horizontally oriented tube.
Given the geometry of the component two main possible strategies were defined, whose schematic representations
As-deposited surface
Fig. 5.a reports an example of the as-deposited specimen, while a pseudo-colour image of the surface morphology can be seen in Fig. 5.b. The process capability for the areal roughness Sa, SL and waviness Sa, LF parameters were identified as average values ± three-times the sample standard deviation (µ± 3σ) as an industrial indicator for process stability [45]. Measurements were averaged over 5 samples, hence, Sa, SL and Sa, LF values were found to be 10.35 ± 0.42 µm and 9.57 ± 0.48 µm
Discussion
The results obtained show strong dependency of surface quality improvement on all four varied process parameters as well as on their interaction. Given the results obtained both in terms of measured roughness Sa, SL and waviness Sa, LF parameters and in terms of analysed surface topography, the main effects of each parameter on the surface topography obtained can be discussed.
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Laser power. This parameter directly affects the energy input provided during the process, determining the working
Conclusions
This work shows the laser re-melting process applied to thin-walled cylindrical components produced by a laser metal deposition (LMD) robotic system. Tubular specimens were deposited, and their surfaces were re-melted with the same plant set-up assessing the feasibility of employing the method in view of complex geometries. The main conclusions of this work can be summarized as follows.
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The LMD produced parts are layered showing strong anisotropy beyond the highly irregular surface. The surface
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors acknowledge the technical support from the BLM Group. This work was supported by the European Union, Repubblica Italiana, Regione Lombardia and FESR for the project MADE4LO under the call ”POR FESR 2014-2020 ASSE I - AZIONE I.1.B.1.3”. The Italian Ministry of Education, University and Research is acknowledged for the support provided through the Project "Department of Excellence LIS4.0 - Lightweight and Smart Structures for Industry 4.0”.
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