Laser metal deposition (LMD) is getting more attention as a 3D printing technique recently. Compared to the cladding application, the process of building 3D structures is more challenging to control when it comes to complex structures. Changing heat transfer mechanisms over the building height and at critical part geometries can lead to instabilities during the process. This paper studies the effect of the surface temperature on single track geometry formation during the LMD process. The geometrical characteristic of the track formation is a key factor that needs to be controlled and monitored in any deposition process for a stable build job. To quantify the effect of the surface temperature on the track geometry, a stepwise preheated substrate from 25 to 500 °C is used, and the track height, width, and degree of dilution are evaluated. This experiment mimics the varying temperature of the prebuilt layers that occur during additive manufacturing of freeform structures with many layers. Understanding the influence of the surface temperature over the layer geometry gives an idea of build geometry variation due to the accumulated heat input along the build direction. This helps in defining process strategies and process parameters for the laser metal deposition of components with increased accuracy and reproducibility. Advanced process strategies that are essential for a successful build job need to be incorporated into a data preparation tool for robot code generation. Commercial software packages are available for regular additive path planning using industrial robots. However, when several process strategies and process parameters need to be adapted and varied along the build direction, one is pushed to the limits of the software capabilities. Therefore, an automated data preprocessing toolbox based on MATLAB has been developed for the implementation of process strategies through user-definable rules and algorithms. This eliminates manual robot code preparation and correction. Implementation and the level of automation of this process preparation toolbox have also been discussed in this paper.
Scanner-based selective laser deburring (SSLD) is an innovative edge-refinement process. This wear-free deburring process uses a single laser source for several materials to create defined radii and bevels. The study is based on a three-stage approach. The first stage describes the process development with interdependencies between deburring and its process parameters, for burrs in laser cut sheet-metal parts. Edges are remelted using a 5 kW Yb:YAG laser at a wavelength of 1.03 μm and a scanner system in order to create refined edges with defined radii. Optimized parameters for the SSLD process are investigated to achieve described cutting qualities. Based on preceding studies, which examined the SSLD process parameters and a thermographic quality assurance, the second stage investigates the automated in-process part handling under certain requirements. This paper presents the dependence between the deburring result and the temperature field in- and post-process. In order to achieve this, the surface temperature near the deburred edge is monitored with infrared thermography. Strategies are discussed for the approach using the infrared information as a quality assurance. A thorough feasibility study is performed in the third stage. For this purpose, a representative specimen with complex geometry is designed. The specimen exhibits the worst case scenario for the SSLD process stability and the developed quality assurance. Based on this, the SSLD process and the quality assurance with 3D vision and accuracy determination are validated. The influence of shape complexity on edge quality is characterized for the developed SSLD process. The gathered in-depth knowledge on process behavior, the quality assurance approach, and the analysis of shape complexity influences are summarized. An outlook is given on further applications and concepts.
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