Offers
PostDoc
If you are interested to join as a PostDoc, please send a brief letter of motivation to the respective contact person.
Postdoctoral Researcher – Acoustic Emission Analysis
For the Researchgroup Condition Monitoring at the Chair "Hybrid Materials" with the Professorship "Mechanical Engineering" at the University of Augsburg, we are looking for a Scientific Associate (m/f/d) - Post-Doc with a focus on Acoustic Emission Analysis.
Our research mainly involves the use of sensor data for process monitoring and structural health monitoring. An important method for this is acoustic emission analysis, which should fall under your responsibility. Your research should enable the development of new concepts for the manufacturing, approval, and monitoring of pressure vessels in the field of hydrogen driven mobility. This gives you the opportunity to contribute to achieving climate and sustainability goals. Furthermore, you have the opportunity to independently explore new research fields and topics.
If you are interested in this position, please contact us by phone or email or send your application directly to the contact persons.
Doctoral Theses
If you are interested to join as a doctoral candidate, please send a brief letter of motivation to the respective contact person
Doctoral Researcher (m/f/d) – Process monitoring for intelligent manufacturing processes
We are looking for a Doctoral Researcher (m/f/d) – Process monitoring for intelligent manufacturing processes to join the team of Mechanical Engineering in the research group Condition Monitoring at the University of Augsburg.
Your research mainly involves the use of sensor data for process monitoring of a complex production chain. The focus of your work is mainly on monitoring innovative injection molding processes. Therefore, you will use various sensor technologies for example acoustic sensors or transducers. In addition to the sensory data acquisition, you will also ensure that the data is further processed in the diagnosis and prognosis systems developed by you, including AI-based systems. Your research will not remain a theoretical concept, but will be implemented directly in the university's own research factory of the
AI Production Network or within the framework of an interdisciplinary Bavarian research network. In this way, you can make your contribution to digitalization and resource efficiency in production.
If you are interested in this position, please contact us by phone or email or send your application directly to the contact persons.
Doctoral Researcher (m/f/d) – AI based Monitoring of machining processes
We are looking for a Doctoral Researcher (m/f/d) – AI based monitoring of machining processes to join the team of Mechanical Engineering in the research group Condition Monitoring at the University of Augsburg.
Your research primarily involves the utilization of sensor data for process monitoring of complex industrial machining tools. The focus of your work is on monitoring complex turning processes. To monitor these processes, you employ various vibration-based sensor technologies. In addition to sensor integration and data acquisition, you take care of the further processing of the data in the diagnostic and predictive systems you have developed, including AI-based systems. Your research is not just a theoretical concept but is directly implemented within the framework of the
AI Production Network and research projects carried out in collaboration with industrial partner companies. This allows you to make your contribution to the digitalization of production.
If you are interested in this position, please contact us by phone or email or send your application directly to the contact persons.
Doctoral Researcher (m/f/d) – Robot-based multimodal non-destructive testing
We are looking for a Doctoral Researcher (m/f/d) – Robot-based multimodal non-destructive testing to join the team of Mechanical Engineering in the research group Condition Monitoring at the University of Augsburg.
Non-destructive testing is an essential part of the manufacturing process, particularly for safety-critical and highly stressed structural components in industries such as aerospace. Various testing concepts, ranging from visual inspection to X-ray tomography, are employed based on specific requirements. In your research, you will play a leading role in the design and implementation of a robot-based testing cell. Your main focus will be on exploring how data acquisition across different testing methods can be automated for individual inspection tasks using industrial robots and your developed algorithms. To enhance the quality of testing, you will investigate concepts for selecting testing procedures and fusing measurement results. Artificial intelligence methods will be applied for data analysis. The findings from the testing cell will contribute to evaluating the quality of other manufacturing processes and labeling datasets from production. Therefore, you will be responsible for a central facility within the research factory of the
AI Production Network at the University of Augsburg.
If you are interested in this position, please contact us by phone or email or send your application directly to the contact persons.
Master Theses
If you are interested, please contact the respective research associate by e-mail
Electromagnetic Modelling and Simulation of Axial Flux Motor
The aim of this master thesis is to develop a simulation model of an axial flux motor with cryogenic cooling system to evaluate the electromagnetic effects of an axial flux motor in 2D and 3D space Also, further evaluations of sensitivity of model to magnetic material properties are of crucial importance to the further development of the electric motor The electro magnetic simulation aims at evaluation and optimization of axial flux motor design.
More information can be found in the hyperlinked pdf:
Electromagnetic Modelling and Simulation of Axial Flux Motor
Analysis of tool influence on signal data in machining using AI
The aim of the work is the investigation of the tool influence on features and the associated creation of a model with methods of artificial intelligence. Among other things, the model should make it possible to predict expected features on the basis of tool information, which can be taken from data sheets, and specified process parameters. By investigating the tool influence, it can be found out whether the tool information and the process parameters are sufficient to describe the correlations between them and the features and thus whether a generalized model is possible. In addition, this would enable the generation of a database for anomaly detection in manufacturing processes. For this purpose, sensor data will first be generated during machining with different tools and process parameters. Subsequently, features will be extracted from the sensor data. With the input of tool information and process data, the established model should predict relevant features of machining processes.
More information can be found in the hyperlinked pdf:
Analysis of tool influence on signal data in machining using AI
Comparative evaluation of conventional orthosis production with 3D printed structures
The aim is to compare and evaluate conventional orthosis production with the production of orthoses using 3D printing technologies. The properties and performance of both manufacturing processes are to be recorded and compared objectively by means of mechanical tests. Sub-goals include examining the accuracy and ergonomics, evaluating the materials and manufacturing processes, and analyzing the time and cost efficiency.
More information can be found in the hyperlinked pdf:
Comparative evaluation of conventional orthosis production with 3D printed structures
Dynamic mechanical behavior of self-reinforced bio-based polymers
This work focuses on the investigation of the thermal-mechanical properties of srPC. In this context, dynamic-mechanical analyses are carried out in order to derive important material parameters. Furthermore, the aim is to consider different load cases and, if necessary, to compare the thermal-mechanical behavior of different srPCs. The tested material will then be processed into filament and 3D printed to produce new sample material. A comparison of the mechanical properties of the recycled material will round off the work.
More information can be found in the hyperlinked pdf:
Dynamic mechanical behavior of self-reinforced bio-based polymers
Experimental investigation of the damage behavior under long-term loading of fiber-reinforced plastics
This work focuses on the investigation of the damage behavior of fiber-reinforced materials under long-term cyclic loading. The first objective is to integrate the measurement technique of acoustic emission and digital image correlation into the experimental setup so that measured data can be recorded. After that, the goal is to record measurement data and evaluate and interpret it to gain an understanding of the damage that occurs.
More information can be found in the hyperlinked pdf:
Development and testing of sensors based on dielectric analysis for the application of non-destructive material characterization
The aim of the work is to further develop the method of dielectric analysis with regard to sensor design, measurement and evaluation in such a way that it is possible to obtain quantitative information about the material properties of the sample independently of external influences such as sample geometry or measuring distance. After a successful development, the sensor is supposed to be used in a larger measurement setup for non-destructive material characterization.
More information can be found in the hyperlinked pdf:
Development and testing of sensor technology based on active thermography for use as a non-destructive method for determining thermal material properties
The aim of the work is to further develop a novel variant of active thermography for use in determining characteristic values. This should make it possible to infer quantitative properties of the material by heating the sample locally and following the heat propagation on its surface. Numerical simulation methods can also be used for this purpose. This should make it possible to investigate thermal properties of materials non-destructively and without great effort.
More information can be found in the hyperlinked pdf:
Development and testing of sensors based on eddy current for the application of non-destructive material characterization
The aim of the work is to further develop the method of eddy current testing with regard to sensor design, measurement and evaluation in such a way that it is possible to obtain quantitative information about the material properties of the sample independently of external influences such as sample geometry or measuring distance. After a successful development, the sensor is supposed to be used in a larger measurement setup for non-destructive material characterization.
More information can be found in the hyperlinked pdf:
Designing and developing a smart sensor for process and condition monitoring
For real-time monitoring, which is a central topic in the working group “condition monitoring” and is already being implemented through the use of ultrasonic sensor, a smart sensor is now to be developed. For this purpose, this work aims to form a basis by enhancing a commercially available sensor of lower frequency with a microcontroller / single-board computer in such way, that it is able to collect, process and forward the data to a central computer via a suitable communication interface. The comparison of the developed sensor with a corresponding commercial system should round off the work.
More information can be found in the hyperlinked pdf:
Designing and developing a smart sensor for process and condition monitoring
Bachelor Theses
If you are interested, please contact the respective research associate by e-mail
Comparative evaluation of conventional orthosis production with 3D printed structures
The aim is to compare and evaluate conventional orthosis production with the production of orthoses using 3D printing technologies. The properties and performance of both manufacturing processes are to be recorded and compared objectively by means of mechanical tests. Sub-goals include examining the accuracy and ergonomics, evaluating the materials and manufacturing processes, and analyzing the time and cost efficiency.
More information can be found in the hyperlinked pdf:
Comparative evaluation of conventional orthosis production with 3D printed structures
Dynamic mechanical behavior of self-reinforced bio-based polymers
This work focuses on the investigation of the thermal-mechanical properties of srPC. In this context, dynamic-mechanical analyses are carried out in order to derive important material parameters. Furthermore, the aim is to consider different load cases and, if necessary, to compare the thermal-mechanical behavior of different srPCs. The tested material will then be processed into filament and 3D printed to produce new sample material. A comparison of the mechanical properties of the recycled material will round off the work.
More information can be found in the hyperlinked pdf:
Dynamic mechanical behavior of self-reinforced bio-based polymers
Experimental investigation of the damage behavior under long-term loading of fiber-reinforced plastics
This work focuses on the investigation of the damage behavior of fiber-reinforced materials under long-term cyclic loading. The first objective is to integrate the measurement technique of acoustic emission and digital image correlation into the experimental setup so that measured data can be recorded. After that, the goal is to record measurement data and evaluate and interpret it to gain an understanding of the damage that occurs.
More information can be found in the hyperlinked pdf:
Working in the lab
We regularly offer opportunities to work in the laboratory (HiWi jobs). If you are interested in working with us, please send a short email with a letter of motivation directly to the respective scientific assistant.