Reliability Assessment & Lifetime Prediction

Reliable prediction of fatigue life and structural durability is now an integral part of modern product development. Whether in material selection, system design, or in fatigue life prediction during operation, our reliability assessment methods ensure that risks are identified early and products are sustainably secured—from the initial idea to actual use.

Our range of research and development services for comprehensive system analysis, material characterization, and fatigue life assessment

We have comprehensive expertise in holistic system analysis and offer you a unique system analysis with characterization and evaluation of metal and plastic materials and components. The focus is on mechanical, physical, and chemical properties, cyclic material behavior, reliability and fatigue life under realistic operating conditions. In addition, monitoring systems for continuous condition monitoring of components and systems are implemented to enable individual fatigue life predictions and evaluations. You benefit from a holistic analysis that secures both development and operation and creates a reliable basis for decision-making for innovation, optimization, and risk minimization as early as the system design phase.

Specifically, the range of services includes:

• Knowledge-based optimization of system designs, for example by selecting suitable materials and manufacturing processes for reliable and sustainable products, from material selection in the design phase to fatigue life prediction during operation.
• Molecular characterization of plastics and compounds for precise evaluation of material properties, e.g., as input for material selection and specification in the early phase of the product development process.
• Evaluation of aging and failure mechanisms to predict fatigue life and reliability, enabling risks to be identified early and requirements to be verified.
• Analysis and evaluation of cyclically loaded components and materials (metal and plastic) for reliable statements on structural durability in the development phase to ensure a safe operation.
• Experimental and numerical investigations to understand and specifically control the effects of manufacturing processes and material properties on product reliability and fatigue life.
• Development of methods and characteristic values for the targeted optimization of assemblies and systems in the concept phase.
• Use of data-driven models for plastics for efficient fatigue life prediction and component development
• Development of requirement-specific testing and validation procedures under complex conditions to validate fatigue life assumptions from initial simulation to final validation.
• Model-based design methods and experimental analyses for evaluating and optimizing the dynamic behavior of components and systems.
• Integration of sensor and actuator systems for condition monitoring and automated adjustment of system dynamics.

Our research focuses on reliable fatigue life predictions already in the requirements analysis and design phase

We develop methods for the holistic evaluation of materials and components from the development phase through the entire life cycle to ensure reliability from the outset and throughout the entire life cycle. The focus is on linking physical-chemical analysis with structural and dynamic properties, integrating life cycle and criticality assessments, and developing digital evaluation and prediction models. The aim is to gain a better understanding of aging and failure mechanisms, thereby enabling reliable fatigue life predictions for complex systems as early as possible to optimize the system requirements analysis and design phase. 

Our research topics in detail:

• System reliability analysis and probabilistic FMEA for identifying and evaluating weak points so that risks can be detected early and addressed in a targeted manner.
• In-situ interpretation for continuous assessment capability from development to use. Establishment of structured data pipelines for material and component data.
• Life cycle assessment (LCA), criticality assessment, and integration of the digital product passport (DPP) into evaluation processes in the early development phase.
• Monitoring/forecasting methods (CM/SHM/PHM) integrated into digital twins, derivation of R strategies from operating data.
• Microstructure-informed reliability models and coupling with material-probabilistic FMEA for early evaluation of system designs.
• Description of material behavior and use of these models for targeted system definition.