Additive Manufacturing Technologies (AMT)
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Digital Photonic Production

Additive Manufacturing technologies (AMT) and their achievements have drawn a lot of attention over the previous 10 years. However, to implement the high potential of such technologies on a widespread scale, there are still a few demands that need consideration. This includes for example the creation of suitable design tools that will help designers in capitalizing on the possibilities presented by Additive Manufacturing (e.g., broad design flexibility, consumer and patient-specific designs, digital materials, etc.). Additionally, the materials utilized and workpiece properties achieved must meet the demanding requirements of applications e.g., in medicine or industry (thermomechanical characteristics, repeatability, and cost, etc.)

“DigiPhot” seeks to address the scientific challenges associated with the aforementioned subjects by offering a set of PhD projects that follows the experience of the participating partners in FH Campus Wien and TU Wien. The project is divided into four distinct topics, each of which is represented in form of a PhD thesis. These topics include advanced methods for characterizing nanostructured additive manufacturing materials, novel tools for the generative design of additive manufacturing parts, methods for online monitoring of laser-based additive manufacturing processes, and process simulation of selective laser melting. Each of the four sub-projects meant to reflect the supervisors' and sub-project leaders' expertise and research interests, with the aim of maintaining the focus of the particular research groups and enhancing their international visibility. Merge across the projects ensures a consistent frame around the overall project.



  • Project 1: Fracture mechanical analysis of heterogeneous photopolymers for additive manufacturing

Supervisor:   J. Stampfl                            Co-supervisor(s): H. Sandtner

Ph.D. student: M. Ahmadi


The goal of this PhD project is the development and investigation of methods for providing heterogeneous, 3D-printable photopolymers with thermomechanical properties close to thermoplast like ABS. In polymer-based additive manufacturing, despite the fact that the amorphous photopolymers offer supreme stiffness, strength, and heat deflection temperature, their low toughness and elongation at break restrict their extensive use in 3D-printing engineering applications. These drawbacks stem from the homogeneous nature of amorphous materials, which limits their resistance to crack propagation and makes them susceptible to break. Eliminating this drawback through appropriate toughening mechanisms can open a broad spectrum of innovative applications for 3D-printed parts. The most relevant approach of toughening compliant with characteristics of photo-curable resins and predefined manufacturing is to create heterogeneity in the bulk polymer without using external instrumentation. This is feasible through a process known as Photopolymerization-Induced Phase Separation (PhIPS), which generates heterogeneity into an initially homogeneous system by enabling marginally or completely incompatible components to diffuse with the polymerization progress. The resulted structures offer adjustable mechanical properties based on the interaction of soft and hard phases so that the established domains are able to dissipate the associated energy of crack propagation and increase toughness and elongation at break without sacrificing strength or stiffness of the material.



AFM results of a droplet-like (a) and interconnected (b) phase structure



  • Project 2: Process simulation for laser-assisted additive manufacturing

Supervisor:   A. Otto                              Co-supervisor(s): I. Miladinovic

Ph.D. student: C. Zenz


Additive manufacturing processes provide the possibility to produce physical parts directly from CAD. Many different processes like e.g. laser powder bed fusion (L-PBF) or laser direct energy deposition (L-DED) have been developed and industrialized in the past years. However, it is still very difficult to find the correct processing parameters for every single part to be produced. The thermal and thermo-mechanical as well as the metallurgical behaviour of a part during the building process are not only strongly influenced by the processing strategy but also by its geometry and material. This often leads to distortion or cracks, to overheated areas and to many other processing failures to be avoided. Thus, producing first-time-right parts, obviously strongly desired by industry, is still an exception and demands for skilled experts.

Process simulations provide the possibility to study the effects that lead to processing failures and are in principle an appropriate tool for supporting the process design. However, those simulations are very demanding as they exhibit both multiscale and metaphysical characteristics:

·         Multiscale, both from the temporal and spatial point of view: typical building times for a part with dimensions of a few cubic centimetres are a few hours, typical fluctuation times on the process scale that may also lead to failures are a few microseconds and they take place on the µm-range.

·         Multiphysical, as a correct process description involves optics, heat conduction including phase transitions, fluid dynamics, powder physics, solid mechanics, material science and so on.

Currently there are no simulation tools available covering all these multiscale and multiphysical aspects. Thus, a major objective of future research work in this field of additive manufacturing must be the development of tools and strategies that enable the simulation of laser-assisted additive manufacturing processes. This will be the prerequisite for the desired first-time-right production.

Based on previous work at TUW concerning the mechanistic simulation of the L-PBF process the PhD project aims at the implementation of several new features into the existing simulation tool. These include:

·         Coupling of the existing model (based on discrete element method and fluid dynamics) and thermo-mechanics.

·         Implementation of a grain growth models and other metallurgical aspects.

·         Development of a simplified model for L-PBF in order to reduce the simulation time.

·         Derivation of strategies to couple the mechanistic and the simplified model.

TU Wien will lead this PhD project by providing supervision and access to the in-house software for simulating laser material processing that has been developed within the last decade. The project will be embedded in the research group “Laser Process Simulation” providing strong expertise in programming and physics with respect to laser material processing.




Preliminary results of a coupled fluid and solid mechanics simulation of a single track conduction mode weld track (domain cut along weld bead centerline); showing liquid melt pool colored by temperature and hydrostatic solid body stress (top), axial and vertical solid body displacement (bottom).



  • Project 3: Generative design for Selective Laser Sintering and Hot Lithography

Supervisor: C. Hölzl                           Co-supervisor(s): J. Stampfl

Ph.D. student: S. Geyer


The goal of this PhD project is to develop algorithms for topologically optimized parts that can be produced by means of SLS and Hot Lithography. Using proven software tools such as SolidWorks for the design of models, Altair Inspire for topology optimization, ANSYS for verification via FEM and both Rhinoceros and Grasshopper for the development of algorithms for structural optimization via non-conformal lattice structures, an easy to use toolchain for part optimization is to be developed. In the scope of the development of algorithms, the potential of using machine learning algorithms will be evaluated and compared with conventional algorithms. For that purpose, components from the open source machine learning library LunchBoxML will be used and adopted.

Both mentioned Additive Manufacturing processes are to be used to produce the optimized parts that in a next step are to be verified via given tools of material testing. Parts produced using the Hot Lithography process additionally have to be optimized in respect of support structures so that no additional support is needed.

The key goal of this project is the development of tailored algorithms that automatically optimize input data from CAD and FEM software under the boundary conditions of design space, fixtures, loads and the soft kill option (SKO) approach, as well as physical parameters specific to the material/fabrication system used, to minimize weight and maximize stiffness of the resulting geometries.

FH Campus Wien will provide software needed to design and optimize part design as well as mentioned fabrication processes. Furthermore, FH Campus Wien will provide supervision for the development of algorithms and machine learning related topics.

TU Wien will provide tools and machinery to verify the optimized and manufactured parts.

Examples of TO and lattice structures



  • Project 4: Development of In-Situ measurement methods for monitoring and recording printing errors to predict part quality

Supervisor: M. Bublin                                                        Co-supervisor(s): A. Otto  

Ph.D. student: V. Klamert


There are already many in situ measurement methods, which monitor the process of selective laser sintering (SLS) with polymer powders. However, process monitoring is an important topic for determining the print quality and the mechanical properties of the components and should be improved during the PhD project. The efficiency of SLS processes for polymers increased by non-destructive analysis, since the reject is reduced by using predictive models. In addition, the aim is to replace sample examinations of the components with process monitoring and subsequent modelling of the influences in the event of errors in the process.

Defects in the powder bed, such as coating defects, uneven distribution of the powder over the installation space and uneven temperature distribution over the sintering process have a negative impact on the material properties of the component. This can lead to the fact that the manufactured components cannot be used for their intended purpose. In order to be able to assess the quality of the components after production, in situ measurement methods should be developed and implemented in the SLS system.

Shift errors can be detected using these measuring methods. With sufficient measuring accuracy of the methods, their influences on the subsequent layers of the components should also be determined. For this purpose, powder defects are specifically created, and their influence is determined.

In addition, dummy samples are produced to measure the effects of the errors on the material properties. Standard measuring methods are used to characterize the material properties (determination of tensile strength, bending strength, surface topology ...).

Based on the measurement data and the measurements of the material properties, a model should be created that describes the quality of the component in the SLS process. For this purpose, close coordination with the TUW, which contributes the material simulations, is required.

It is planned that the PhD candidate will continuously define and supervise theses (master and bachelor theses) from the aforementioned subject area during the doctorate.



Curling (a) and coating defects (b) in SLS processes with plastic powder