The understanding of this material behavior and its mathematical and physical description forms the basis for efficient actuator and sensor design. The working group develops analytical and numerical models that support the design of prototypes. Due to the non-linearity, the control and eventual regulation of the materials is also a further challenge. New control strategies and concepts allow the optimized operation of the intelligent actuators in the application.

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In addition, special electronic solutions are required for the simultaneous acquisition of sensory quantities. The developed solutions are compactly integrated into complete systems, both in applications with limited installation space and in flexible systems. Microcontroller programming is also an important part of the research.

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In a joint project funded by the Werner von Siemens Foundation with the University Hospital and Saarland University, as well as the German Research Center for Artificial Intelligence (DFKI), novel, smart implants are being developed that will dramatically shorten the healing times for bone fractures in a patient-specific manner.

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The focus is on electrical and electro-mechanical field simulations as well as coupled multiphysical analyses of thermo-mechanical and fluidic systems. In cooperation with the groups of the different subject areas, the developed models and tools are experimentally validated. These are used for the design and adaptation of application-oriented system solutions. The aim is to optimize the developed systems for a wide range of applications.

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There they replaced conventional drive systems such as electromagnets or use hydraulic concepts in combination with their special material effects.

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The integrated sensor technology enables precise detection of movement and vital parameters. At the same time, input surfaces and active areas offer the possibility of direct interaction with the digital or virtual environment. Through haptic feedback or acoustic signals, textile-based systems can be developed for industrial, medical and gaming applications.

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Due to their high performance and high beam quality, the latest photonic production processes open up a great potential for optimization for material processing processes. The highly dynamic manufacturing processes usually require optical monitoring in order to be able to control and ultimately regulate the machining process in a first step without contact and with high temporal and spatial resolution.

There are already industrially available process monitoring systems that influence the beam guidance or provide simple qualitative evaluations of the process quality. However, these reach their limits when superimposed influences occur under production conditions, the effects of which are not clearly attributable to the production result. For the implementation of a control system, this data must be taken up in order to ensure a constant quality.

approach

By integrating existing monitoring systems into a production cell, online process data is recorded and the measurement curves are correlated with phenomena that occur during the process. The resulting findings are then used for the development of a nonlinear MPC control system, which influences the process online and thus keeps the product quality stable.

benefits

• Online analysis of processing processes

• Selection and integration of monitoring and control systems

• Metallographic evaluation of joined metals

• Marking of metallic surfaces

Due to the process, this results in the great advantage that the hardness of the components to be machined has no influence on the process result. However, in practice there is wear on the tool electrodes, which leads to the challenge that a new electrode should be used again and again for the final processing in the spark-erosive countersink processing.

Our approach combines various manufacturing processes for the production of tool electrodes for the subsequent surface structuring of carbide.

The aim of the development is the construction of a process chain that allows a reproducible structuring of surfaces by means of spark-erosive countersinking, whereby the required tool electrodes are produced electrochemically suitable for mass production.

• Pulsed electrochemical ablation (en. PECM – Pulse Electrochemical Machining)

• Photonic technologies (remote laser welding)

• Spark erosion removal

In cooperation with our project partners and chairs at both Saarland University and Saarland University of Applied Sciences, we are able to present an extensive portfolio in the context of manufacturing process development.

Our services:

• The consideration of interactions when combining the abrasive methods with each other as well as with conventional methods.

• Investigations for individual process management and process design.

• Investigations of pre- and post-treatment

• Analysis of the materials used before and after processing.

The PECM process enables non-contact surface processing and the insertion of room shapes as well as microstructures in workpieces, whereby the processing of all metals, regardless of their structural state, is possible without machining stresses and without process-related material wear.

PECM technology is therefore finding more and more applications in metalworking, e.g. in the production of complicated room shapes or in the processing of hard-to-machine workpieces or workpieces that must not be subjected to thermal stress or subjected to low mechanical stress during machining.

Our services:

• Conducting basic investigations in the field of electrochemical material processing using cyclovoltammetry and chronoamperometry

• Investigations for individual process management and process design

• Investigations of pre- and post-treatment

• Analysis of the materials used before and after processing

• Creation of static FEM simulations for the calculation of current density distributions

Research activities include:

• diverse layer deposition by means of sputtering technology,
• Flexible sample structuring by laser ablation,
• Setup and contacting various force and pressure transducers,
• Precise characterization under a wide variety of environmental conditions.

Sputter deposition, including reactive and co-sputtered processes, can produce a wide variety of materials and material combinations. Thin layers of nanoscale particles in various matrix systems (granular metals) are used for advanced sensor technology. Even metal layers with certain additives can have excellent sensor properties. Examples of our coating systems are:

• Metal-carbon layers (e.g. Ni-C). Similar to the known piezoresistive semiconductors, they have an increased sensitivity. Suitable additives such as chromium allow the layers to be stabilized even for very high ambient temperatures. The behaviour under harsh environmental conditions is extensively investigated. Characteristics relevant to transducers, such as signal crawling, are precisely characterized.

• Special antiferromagnetic metal alloys. In addition to high sensitivity, these also enable particularly high stability and robustness with adjustable temperature behavior.

In research and development projects with partners from industry, the functional layers are used for specific sensor developments. Existing physical analysis (electron microscopy, X-ray diffraction, etc.) and our expertise in laser fine machining (ultra-short-time lasers), coating technology (sputtering systems) and sensor construction (laser welding, ultrasonic bonding, etc.) can also be used in the context of service contracts.

The activities can be divided into the following main areas of responsibility:

• Design of Experiment for Condition Assessment with Machine Learning

– Advice on and preparation of experimental plans and the optimal compromise between many statistically independent training data and experimental costs

– Advice on sensor technology and data acquisition and support with the help of a modular measurement case for training data acquisition

– Data analysis accompanying the experiment for continuous monitoring of the quality of the data and the course of the experiment

• Automated Machine Learning Toolbox for Condition Assessment of Industrial Machines

– Prediction of remaining service life of machine components

– Detection of sensor errors such as offset, drift, unusual noise or signal outliers by exploiting (partial) redundancies in sensor networks

– Early detection of committees

– Soft sensing

– Damage detection to assist maintenance personnel

• Sensor-based signal processing

– Data reduction directly at the sensor through feature extraction and selection

– Special algorithms for sensor-based signal processing and inference with low resource requirements

– Use of dedicated hardware chips for ML inference (with partners)

• Explainable AI

– Physical interpretation of automatically learned damage symptoms in order to avoid random correlations and to make ML decisions comprehensible

– Robustness and transferability analyses by physically motivated cross-validation for maximum reliability of the learned models

• Measuring uncertainty analysis of machine learning

– Measurement uncertainty considerations based on GUM for precise estimates of the reliability of predictions

– Continuous traceability of lifetime

• Anomaly detection

– Detection of unknown machine damage

– Plausibility checks for ML inference

– Outlier detection to improve training data

Research activities can be divided into the following priorities:

• PLC-based applications
– Control and regulation with PLC systems
– Process visualization
– Motion control and drive solutions
– Prototype development
– Training and further education

• Process development
– Control and process optimisation of laser welding processes
– Automated contacting of FGL materials with electrically conductive materials
– Process analysis of PECM plants
– Automated archiving of documents

• Digital automation systems
– Standardised design of automation systems
– Integration and processing of planning data for the automated configuration of automation solutions

Based on experience and current developments in automation technology, new and innovative applications are developed and designed and verified in production-related demonstrators. Current trends and new solutions, especially in the digitization of production processes, are incorporated into methods, concepts and solutions. The working group conducts research in national collaborative projects with cooperation partners from research, associations and industry and contributes to technology transfer for regional and supra-regional SME companies.