Current projects
- Data-driven condition monitoring of electronic systems
Condition monitoring of electronic systems by integrating expert knowledge and hardware tests into machine learning algorithms - Reliability of Adaptive Load-Bearing Structures
Collaborative Research Centre 1244: adaptive skins and structures for the built environment of tomorrow - Lifetime Tests of HV Batteries with Prior Knowledge
Efficient planning of lifetime tests for reliability assurance of hv batteries considering prior knowledge - Moisture Transfer
Soft sensors to determine the humidity conditions in solar inverters - Lifetime Model for a Timing Belt Drive
Lifetime model for a timing belt drive in steering gears based on design of experiments (L-DoE) - Reliability Process for Photovoltaic & Battery Inverters
Development and evaluation of an efficient and reliable methodology for reliability prediction and lifetime prediction of photovoltaic & battery inverters and their critical components - Module-Integrated Electronics for Photovoltaic Systems
Evaluation of the reliability of module-integrated and system-optimized electronic solutions of photovoltaic systems - Lifetime Model Winding Insulation
Development of a holistic lifetime model for the winding insulation of electrical machines on the basis of the acting damage mechanisms and their different load levels
Recently completed projects
- System Reliability Demonstration Using Prior Knowledge
System reliability demonstration considering uncertainty of prior knowledge - Modular and Scalable Safety Concept
Conceptual development of a modular and scalable safety concept including a prototypical implementation for the example of an electronic power distributor - Future-Load-Model for Predicting Representative Load Collectives
Function development to form representative load collectives based on past load for predictive diagnosis of lead-acid batteries - Functional Safety in the Field of Powernet
Functional safety in the field of powernet with a focus on technical safety mechanisms - Close-to-Reality System Analysis with a Confidence Interval
Modelling and Analysis of Reliability and Availability by stochastic modelling techniques considering continuously the statistical quality of the initial dat
Project archive
Martin Diesch, MTU Friedrichshafen GmbH
Methods and technologies for fail-safe adaptive bearing structures and their elements and structures
Andreas Ostertag, DFG Sonderforschungsbereich (SFB 1244)
In the SFB 1244 the aspired adaptive structures need to adapt to the current load situation like wind and weather and the user. Beside of guaranteeing a high reliability the behavior of the system when it comes to a failure is very important. The objective is to have a Fail-Safe-concept managing an adaptive fault response which keeps the operating condition sustainable as far and as long as possible. Furthermore supporting Fail-Safe-elements will be developed and applied.
Andreas Kroner, Daimler AG
Thomas Herzig, IMA
The testing effort required to prove the reliability target can already be taken into account in the early development process. The aim is to achieve an optimum between product development costs (material, production, ...) and testing costs (test type, number of test items, ...) by adjusting the overdimensioning. (material, production, ...) and testing costs (type of test, number of test items, number of test rigs required, choice of load levels in accelerated testing, ...). The choice of the appropriate testing strategy is thereby objectively evaluated with the help of test costs, total time and probability of success and is influenced by the oversizing of individual failure mechanisms considered in the development process.
Mark Henß, IMA
The use of machine learning enables automatic recognition of relevant patterns and trends in data that are difficult to access for humans. Missing training data, labels and a low data quality are obstacles for implementation. This project investigates how prior knowledge can be implemented in the algorithms to eliminate these deficits.
Alexander Kremer, Walther Flender GmbH
Kevin Lucan und Mark Henß, Bergische Achsen, DAF, Daimler, Haldex, IVECO, Knorr-Bremse, MAN, MERITOR, SAF Holland, WABCO
Frank Müller und Jan Gröber, Festo AG & Co. KG
Julian Popp, HSA Aalen, ISSA Forschungsprojekt
The demand for raw materials from the deep sea is constantly increasing. In order to extract these raw materials, systems are needed that are environmentally friendly, safe, reliable and also available. The project will develop a system architecture with a focus on mechatronic drive technology that meets the enormous requirements that prevail in the deep sea. Verification and validation on a self-developed test bed environment is also part of the project.
Volker Schramm, CERN
Analysis of surveillance systems for particle accelerators to improve the reliability, availability and the protective function. Development of a methodology on how to design, produce, test and operate dependable electronic systems. In addition, application of the methodology for the system reliability analysis, definition of the operational strategy and execution of functional and reliability tests.
Sebastian Imle, WITTENSTEIN motion control GmbH
The extraction of raw materials in the deep sea requires an environmentally friendly and safe propulsion solution. The system architecture defines the components and interfaces of the system in terms of type and quality. The processing quality of this information via a secure communication architecture determines the diagnostic coverage and functional safety of the system. The design of a condition monitoring system for use in the deep sea is the goal of this project.
Alexander Grundler, Martin Dazer; Daimler AG
Alexander Grundler, ZF Friedrichshafen AG
Frederic Heidinger, Patrick Münzing and Andreas Ostertag, Robert Bosch GmbH
Fei Long, GSaME, DFG
Zeljana Beslic, IMA
Sebastian Held, Knorr-Bremse Systeme für Nutzfahrzeuge GmbH
Martin Dazer, Knorr-Bremse Systeme für Nutzfahrzeuge GmbH
Contact Head of Reliability Engineering

Martin Dazer
Dr.-Ing.Head of Reliability &Head of Drive Technology Department
Temporary Head of Railway Vehicle Department