The Chair of Production Systems is conducting research within Subproject 2 of the research group on the automation of the robot-assisted DED-LB/M process for the additive manufacturing of metallic freeform components. The primary objective is to enhance the efficiency and performance of the process chain through an intelligent integration of additive and subtractive manufacturing techniques. Central to this endeavor is the development of an advanced, simulation-driven toolpath planning methodology that incorporates topology optimization, real-time process monitoring, and thermal process control to enable the production of high-quality, load-optimized components. To this end, the dynamic behavior of a six-axis industrial robot is comprehensively analyzed across its entire workspace, with particular emphasis on natural frequencies and mode shapes as functions of joint configurations.
Complementary to this, a robot-guided milling process is being investigated to enable the targeted finishing of functionally critical surfaces and to ensure defined surface qualities. In the long term, the project aims to realize simultaneous processing via material deposition and milling in order to significantly reduce overall process time. Additionally, the interactions between manufacturing processes and robot kinematics are systematically examined.
Through these efforts, the subproject makes a substantial contribution to the overarching objective of the research group: the simulation-supported, manufacturing-oriented design and production of structurally optimized metallic freeform components.
The subproject aims to produce freeform geometries using wire-based laser metal deposition (DED-LB) with high precision and minimal tolerances. The focus is on developing a reproducible material deposition process, even in complex spatial orientations. In addition to geometric accuracy, the (thermo-)mechanical properties of the components are considered, which are influenced by material composition, microstructure, and temperature control during the process. To manufacture stable and load-optimized components, the effects of various process parameters—such as laser energy, wire feed rate, and movement speed—on temperature development and residual stresses are investigated.
An experimental setup with a 6-axis robot and a rotary-tilt table enables welding in any spatial orientation. The goal is to determine robust process windows for different materials and build strategies. Further tasks include measuring the geometry and surface roughness of the components and optimizing them through subsequent laser processing. Special attention is given to so-called welding vectors, which can be used as self-supporting structures in topology-optimized components. In collaboration with other departments, the relevant process parameters are determined experimentally and used for the development of control concepts.
In this sub-project, load-optimized and additively manufactured components made of stainless austenitic steels such as 1.4404 (316L) and 1.4307 (304L) are examined and tested with regard to their microstructure and their mechanical and metal-physical properties. This includes the characterization of the microstructures with regard to volumetric defects and solidification-induced microsegregation. The rapid and directed solidification in the DED-LB/M process leads to the formation of equiaxial to columnar dendrites. Strong constitutional undercooling can enrich the interdendritic space with the alloying elements, while the dendrite cores are particularly rich in the base element iron. In addition, heat-affected zones and heat build-up depending on the component geometry can influence the degree of segregation and the fineness of the resulting microstructures. This special microstructure formation leads to locally varying phase stability. The phase stabilities are of particular importance in the austenitic stainless steels investigated. Some stainless austenitic steels appear in a metastable austenitic state after DED-LB/M processing. Driven by residual stresses or externally introduced deformations and depending on the local phase stability, the metastable austenite can undergo a martensitic transformation. The martensitic transformation has a major influence on the mechanical properties and thus on the behavior of the workpiece during machining and subsequent application. Particularly with regard to applications in hydrogen environments, local martensitic transformation can cause critical embrittlement of components. In this context, it is aimed to prevent local martensitic transformation through process and alloying measures.
In subproject 6, the manufacturing of topology-optimized geometries from carbon-martensitic hardening tool steels using the additive manufacturing process “Directed Energy Deposition–Laser Beam (DED-LB/M)” will be investigated. During DED processing of complex geometries, a transient heat flow arises, leading to locally varying solidification conditions and reheating effects due to the layer-by-layer material deposition. This results in locally heterogeneous microstructures and material properties.
The goal of subproject 6 is to understand the locally differing microstructure formation processes, formed from the melt and in the solid, and the associated properties during DED-LB processing, using a carbon-martensitic hardening tool steel as an example. Therefore, specimens with different geometries will be produced by DED using a flux-cored wire. Temperature and melt-pool data will be recorded in situ during the manufacturing process so that the interaction of geometry, process parameters, and microstructure evolution can be modeled using phase-field and CALPHAD simulations. The relationship between the locally formed microstructure and the resulting properties will be determined experimentally by local microstructural characterization (SEM, EDX, EBSD) and property measurements (nanoindentation).
The insights gained will allow validation of the preceding simulations and will feed directly into adaptive in-process strategies (laser parameters, interpass dwell times) and into topology optimization to deliberately tailor the local microstructure and mechanical properties of the fabricated component. Finally, the adjustment of near-surface material properties and surface quality using a heat treatment (laser hardening, tempering) and subtractive post-processing will be examined.
The working group Virtual Machining at TU Dortmund University is involved in Subproject 7 of the research unit, focusing on the analysis and optimization of robot-assisted milling processes for components manufactured using robot-based DED-LB additive manufacturing. The objective is to enable the demand-oriented design of the post-processing procedure for these components, particularly considering form deviations and dimensional fluctuations resulting from the additive manufacturing process. A central focus lies in identifying and evaluating the challenges encountered during robot-assisted subtractive post-processing, developing a solution-oriented approach to address these challenges, and providing corresponding insights - such as boundary conditions - already during the topology-optimized design of the component geometry. In addition, the specific influence of anisotropic material properties of additively manufactured components on their machinability is being investigated, particularly with regard to the resulting process forces. The existing milling simulation system is being further developed to account not only for form deviations but also for process variations caused by manufacturing-related directional dependencies, as well as the process-dynamic boundary conditions characteristic of robot-assisted milling. Special attention is given to adequately representing the identified variations in compliance behavior within the process simulation and to developing a method for multiscale in-situ digitization of components. The aim is to map this information within an adaptively resolvable workpiece model and to make it usable for simulation-based process planning. Building on this, a methodology for evaluating engagement scenarios is being developed, enabling the targeted derivation and provision of boundary conditions and recommendations for the adjustment and optimization of NC tool paths.
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Last update: Jun 20, 2025
