SSI 2025 | April 8-10 | Prague

Klaus looks back on over three decades of experience in software and system engineering, including five years of international delegation to Eastern Europe. With degrees in mathematics and philosophy, he began his career at Nemetschek AG, a leading IT company in the AEC sector. He has gained extensive intercultural experience in international projects, particularly at the European level. His previous roles include membership on the board of the European Software Institute (ESI), the executive board of Digital Europe (DE), the steering group of the Eureka cluster ITEA, and the board of the Alliance Internet of Things Innovation (AIOTI). Since 2002, he has been with Siemens, where he led the global technology field of "Software and System Engineering." From 2011 to 2015, he served as Director for Business Creation & Entrepreneurship at EIT Digital, and from January 2020 to July 2023, he was the CEO of EIT Manufacturing. He is currently active as a board member, advisor, and speaker at various conferences.

Transition to SMART Manufacturing is not an on day action. From simple standardization to LLM. Look into some areas and get insides what the transision means and and where the challenges lie. What are the areas of improvement and what is the benefit for the company and the costumer.

Innovation and quality drive Europe's global competitiveness. The EU Chips Act boosts the semiconductor industry, reducing reliance on foreign manufacturers and strengthening technological sovereignty. However, upcoming legislation, while vital for sustainability, adds regulatory hurdles that may constrain innovation. Balancing progress with compliance is key to maintaining Europe's edge in semiconductors and beyond.

MEMS sensors are integral to modern vehicle safety and functionality, and their use has expanded significantly into consumer electronics, enabling countless daily functions. These sensors are integrated with computing units, embedded software, and communication functionalities, requiring ultra-low power operation and complex system interactions, making MEMS development a cross-domain engineering challenge. The SMP290 sensor module, which includes various components like pressure sensors, accelerometers, and BLE communication, demonstrates the need for collaboration across engineering domains to achieve reliable, low-cost, and ultra-low power operation. Looking ahead, MEMS will play a crucial role in the development of humanoid robots and the transformation of health-care, driving future market demands and innovations.

The APECS pilot line strengthens European semiconductor manufacturing and chiplet innovation as part of the EU Chips Act. It enables companies to access cutting-edge technology, promotes sustainable innovation, and supports the integration of heterogeneous systems. APECS, ten partners from eight countries, provides services for research and industry, enhances quality assurance, and accelerates the market introduction of new technologies.

For real-time control and monitoring, IoT applications at the cloud/edge service layers need to gather, store, and analyze rapidly changing data streams produced by sensors. Using Google’s Kubernetes technology is one of the most effective methods to manage lightweight containers. Still, there are critical elements like resource management for IoT sensors. Without compromising the core of Kubernetes or containers, we developed a technique in this study to integrate container technology and the Kubernetes architecture into an infrastructure for controlling all types of leaf edge resource resources. Thus, we achieve to promote interoperability and simplify the administration of IoT wireless devices in diverse setups.

This presentation is about direct wafer bonding of dissimilar materials at room temperature. Room temperature bonding is of special importance for future applications because dissimilar materials (e.g. Si/LiTaO3) can be bonded without thermally induced stresses and low process costs. For this reason a high interest in roomt temperature wafer bonding arises.

An FPGA-based accelerator design for the computation of the RBF kernel matrix is presented. After first stating the importance of Gaussian Process Regression and its need for acceleration as well as providing some theoretical basics, the key acceleration methods used are introduced and explained. Finally, first computation results of the accelerator are presented and discussed. Ongoing from this, further development steps are mentioned.

This presentation will introduce the European research project GREENER and show a detailed concept of the DNA origami based single photon source to be developed in this project. This includes the fabrication and characterisation of the layer stack as well as the specially developed DNA origami design and its surface integration as a DNA origami QD hybrid.

1) The cost-effective multi-platform sensing system proposed by FAMOSOS, is based on electrochemical sensing and is able to measure different continuous in-situ soil water nitrogen (N) concentrations, temperature and moisture status using automated data acquisition and wireless Lora data transmission through soil with to better prevent, track and report on soil nutrients and pollutants.

2)The European Horizon project BioSensei concept is built on the development of a microbial whole-cell-based biosensor system with real-time monitoring for detection of pollutants in watercourses. It will be able to monitor typical nutrients (nitrates and phosphates), estrogenic endocrine-disrupters, PFAS (per and polyfluoroalkyl substances) and microcystins.

This work presents an innovative BioSensei bimodal sensing system embedded within a Safe-and-Sustainable-by-Design framework all along the project.

This publication, as part of the Horizon Europe AURORA project [1] ( https://www.aurora-h2020.eu/ ), describes the development of a low power consumption UltraWide Band (UWB) wireless indoor tracking device focussed on indoor localization of valuable artworks in a museum using wireless sensor network (WSN) technology. AURORA aims to advance the state of the Art in embedded tracking devices for cultural heritage artefacts, striving for minimal impact on the art object.

This presentation introduces an innovative approach to simulating damage propagation in power electronic modules, addressing the growing need for reliable assessment methods in an increasingly power electronic-dependent industry. It explores the initial stages of implementing a prognostic health management system, focusing on advanced modeling techniques for solder interface delamination and simulation strategies to monitor chip temperature. The method enables the evaluation of various thermal management strategies and assesses module reliability across different operating conditions. This concept aim to lay the groundwork for more comprehensive and accurate reliability assessment tools in power electronics, ultimately contributing to the development of more robust and efficient power electronic modules for wide range of applications.

Ensuring security and comfort in public transportation has become increasingly critical, particularly in the context of the COVID-19 pandemic. Passengers seek not only reliable transportation but also assurance of adequate space and healthy air quality.This presentation introduces a system that measures air quality in buses and trains and transmits the data in real-time to a cloud. Together with occupancy data, it can be determined when certain measures need to be taken during specific pandemic situations. These measures include activating air filtration systems, deploying additional vehicles, and providing data to passengers. Additionally, the system offers various analysis options, enabling the creation of forecasts. The hardware and software components developed for this system can be cost-effectively retrofitted in buses and trains. Public transport companies and transport associations do not need specialized IT infrastructure, because the backend system runs entirely in a cloud. The system was developed as part of the research project Semoove, which was funded by the Federal Ministry for Digital and Transport in Germany.

The validation of a novel Industrial Internet of Things (IIoT) sensor platform and a dedicated polymer encapsulation process designed to operate reliably in harsh environmental conditions will be presented. Will the device survive the harsh environmental conditions to which it has been exposed?

The automotive industry is rapidly transforming with new technologies, emphasizing smart cities and shared transportation infrastructures. This shift demands a new digital mobility platform. Innovations like AI, IoT, and automation are reshaping business models and promoting coordinated transportation. The vehicle, evolving into an "Internet node on wheels," exchanges data with diverse platforms emphasizing road safety. Addressing these challenges requires cross-disciplinary solutions and methods, ensuring interaction throughout the development process while meeting safety requirements for embedded real-time systems.

Target of the presentation is showing these three core technologies:
Navigation and path planning including robotic platforms.
Artificial Intelligence for high-definition digital maps taking advantage of C-V2X breakthroughs.
...and accident prevention for Vulnerable Road Users (VRUs) connecting vehicles via IoT between them and to the infraestreucture.

All in all improving transportation efficiency, enhancing safety measures, promoting multimodal transport integration, and leveraging advanced technologies to meet the challenges of modern urban mobility by Sea, Land and Air.

Our solution presents an AI-driven framework for automating network discovery, device classification, and causal inference in Industrial Control Systems. Using autonomous agents, it enables real-time scanning, unsupervised learning, and process modeling. The approach enhances Digital Twin creation, predictive maintenance, and cybersecurity while addressing challenges like real-time constraints, data sparsity, and security risks.

Photonics is a key enabling technology in the realization of modern medical devices with applications ranging from diagnostics to personalized monitoring. Smart system integration of light sources, integrated optics, advanced packaging, microfluidics etc. is required to meet the tight regulatory requirements. In this talk, perspective of Chips JU project PhotonMed is presented with a focus on multispectral photonic sensor use case.

The presentation focuses on the design, fabrication and characterization of Universal PMUTs.
The work provides a brief introduction to the world of MUTs especially the PMUTs and then dives deep into the universal PMUT technology, mainly focusing on the design, fabrication and characterization of these Universal PMUTs. The unique aspect of this work lies within the adaptive acoustic channels developed implementing the automatic wire bond technology.

This presentation adresses the carbon footprint of self-powered wireless sensors. The power supply by a battery is compared with different solutions of using ambient energies (energy harvesting) in terms of sustainability.

We investigated factors influencing the stability of DNA origami assemblies, with a focus on their potential integration into smart micro- and nanoscale devices. In this study, the stability of DO structures in PBS based buffers is investigated for the first time. Decrease in structureconcentration over time as well as the occurence of defects are documented. Occuring defects were classified and a connection to simulation data was drawn. Furthermore, the 4 key methods to evaluate DO quality are presented.

The presentation explores a wearable device using multi-modal sensors (EEG, PPG, accelerometers) and machine learning (CNN, RNN, SVM) for real-time seizure detection. By integrating IoT and cloud computing, the system improves accuracy, reduces false alarms, and enables remote monitoring. This innovation enhances patient safety, autonomy, and healthcare efficiency for epilepsy management.

Test program development is time-consuming and lacks direct integration with design and verification workflows. Key aspect is the use of SysMLv2 as a connector between the design side—covering system abstraction, requirements, and technical specifications—and the test side, which includes test descriptions, test patterns, and execution models. This coupling intends faster test development by reducing manual steps and thus avoiding errors.

This presentation introduces a customized SysML v2 Profile for model-driven circuit test development (MDCTD). The profile intends to streamline test program creation, reduce effort and time, and ensure indepedence from specific Automatic Test Equipment (ATE). The approach involves the modeling of test setup and test methods within SysML v2, leveraging modular structure for reusablity and flexibility.

The presentation highlights the development of advanced current measurement sensors using multi-material Additive Manufacturing. These sensors handle high currents up to 1000A and operate under varying conditions, including high bandwidths and temperature variations. Early research shows successful production of components with excellent conductivity and strength, demonstrating the high potential of AM-enabled measurement systems for modern mobility and sustainable energy applications.

Upscaling of superconducting qubit based quantum computers will require an alternative for standard coax cables. Here we present a new fabrication route for polyimide- and niobium-based flex lines with a high density of shielded transmission lines, together with a space saving direct-PCB connector. Our concept relies on full roll-to-roll processing with digital maskless lithography, eliminating any limitation to the length of the flexible cables.

The MasterCurveCreator tool represents a significant advancement in the characterization of viscoelastic materials, addressing the complexities associated with generating master curves. By automating the processes of data manipulation and the calculation of temperature-dependent shift factors, this innovative tool effectively reduces the manual effort typically required and minimizes the potential for human error. One of the core principles utilized by the MasterCurveCreator is the Time-Temperature Superposition (TTS) principle. TTS allows for the alignment of viscoelastic property data obtained at different temperatures, enabling researchers to create a single, cohesive master curve that represents material behavior across a wide range of conditions. This comprehensive characterization is essential for understanding the performance of viscoelastic materials in real-world applications, such as in the automotive, aerospace, and civil engineering industries, where materials are subjected to varying temperatures and loading frequencies. The tool not only simplifies the data alignment process but also facilitates the deduction of Prony series coefficients, which are vital for accurately modeling the time-dependent behavior of viscoelastic materials. The Prony series provides a flexible mathematical representation that captures the complex viscoelastic responses of materials, allowing for better predictions of their behavior under different stress and strain conditions.

Within the presentation " Wafel Level Technologies for System Integration" the D2W integration technology Micro-Transfer Printing will be introduced and recent developments at X-FAB will be highlighted. In this context, more details on I) the preparation of transferable µASICs, II) the wafer-level die integration itself and III) subsequent metallization via Cu-RDL will be shared. In addition, Through-Silicon Vias and capabilities of varied Bonding Technologies are shown.

A hydrogel-coated capacitive pressure sensor (Infineon DPS422) is investigated as a novel humidity sensor. The thermo-responsive pNiPMAAm hydrogel was drop-coated, causing membrane deformation upon swelling, which is read out capacitively. Initial tests show fast response times. Future work will focus on optimizing the coating process and evaluating long-term stability.

Real-time pH and oxygen concentration sensing is critical for monitoring tissue damage and organ health; however, there is no report to date on a single device in such context that can simultaneously detect both pH and oxygen changes. This work reports the development of a single optical sensor device that can simultaneously and reversibly respond to changes in both pH and oxygen concentration. The proposed optical sensor integrates both pH and oxygen sensitive probes, and is optimized to achieve minimal cross sensitivity during simultaneous measurements. This approach enables high accuracy in early detection of chemical correlates of tissue or organ damage, improving screening and efficacy in organ transplants.

Proper mounting is crucial for accurate acceleration measurements with MEMS sensors. This research investigates whether MEMS accelerometers are capable of assessing their mounting integrity and detecting loose bolts when attached to 3D-printed fixtures. Effects of loose mountings on vibration transmission were captured using a laser vibrometer, and a support vector machine classified MEMS data to reliably identify mounting faults.

The presentation describes the progress towards processes for design, fabrication and wafer level characterization of photonic integrated functionalities based on silicon nitride and aluminum nitride. Passive photonic components like waveguides, couplers and ring resonators are designed with the aim to combine them with standard MEMS processes.

Anomaly detection in vibration signals is vital for condition monitoring in industrial and structural health applications. This study evaluates cost-effective, energy-efficient smart sensors combining MEMS accelerometers with microcontrollers against a laboratory setup. Two platforms --Arduino Nano 33 BLE and Analog Devices MAX78000 --were assessed for performance, energy consumption, and real-time anomaly detection feasibility. Results indicate that all embedded systems achieve accuracy comparable to the reference setup. Notably, the MAX78000 offers superior inference speed and processing capabilities with a modest energy trade-off. Integrated micro-electromechanical systems (MEMS) and microcontroller solutions prove to be viable, scalable alternatives for on-site condition monitoring

In this talk we show how we built a modular AI platform based on open-source tools and existing software. One of the major aims was to retain full control over the process at any point to meet unforseen requirements. Furthermore, third-party cloud dependencies should be avoided to handle even confidential data or deliver trained models on-premise. Finally, two use cases from electronic systems domain are implemented within the proposed architecture.

The presentation focuses on pre-processing techniques designed to enhance the accuracy and robustness of an AI model. The data used includes both simulated and real far-field measurements. Before the data can be utilized effectively, it must undergo several transformations, such as noise reduction, augmentation, and feature extraction.

The transition to a circular economy is key to sustainable automotive innovation. The Horizon Europe-funded UNICORN project advances functional electronics as enabler for circular mobility. This presentation outlines a vision and roadmap for integrating printed and flexible electronics, enhancing modularity, reparability, and material recovery. It highlights key pathways, lifecycle impacts, and policy recommendations for sustainable transformation.

# This paper presents the development of a cloud-based monitoring system for a DC microgrid designed for community applications.
# The system integrates a simulated utility grid (SUGS), a battery energy storage system (BESS), and a solar power generation system (SPGS) with a cloud-based front-end monitoring interface.
# A Long Short-Term Memory (LSTM) model is employed to forecast the subsequent day's load curve, while a solar simulator replicates diurnal variations in solar irradiance.
# To optimize economic performance under peak and off-peak time-of-use (TOU) pricing regimes, a greedy algorithm is implemented via a local selection strategy to allocate energy optimally among the SUGS, BESS, and SPGS.
# Finally, the economic viability and technical feasibility of the proposed approach are verified through a derating case study comprising both simulations and experiments.

We propose the development of smart biochemical sensing technologies for the detection of water pollutants (e.g. nutrients) online, embedding powerful data fusion tools based on neural networks to achieve a predictive system for on-line water quality monitoring. Sensor signals are treated with neuromorphic electronics integrated in silicon chips, being therefore robust, miniaturizable and scalable in its production.

Edge computing systems urgently require innovative solutions for rapid processing of complex multidimensional AI data so as to minimize latency. In this presentation, we will show that electronic traps in the gate oxide of a logic Si transistor, previously deemed undesirable and suppressed during every technology cycle development, may be harnessed for the computation of spatiotemporal signals in real time. We will present a case study showing the prospects of how a simple array of logic Si transistors may completely bridge the gap between a dynamic vision sensor and established light weight models (e.g., ResNet) already developed for static image data.

Wafer bonding, the process of stacking and joining processed substrates, is a key step in MEMS manufacturing and smart systems integration. It enables the realization of 3-dimensional chip structures for protecting, sealing and completion of MEMS and their integration with CMOS driving and signal processing electronics. In recent years, the requirements on wafer bonding technologies increased. The main aspects are: smaller bond frame sizes to enable smaller chips for mobile applications, but more importantly cost reductions, high vacuum sealing and electrical contacts between the wafers. On the one hand, established wafer bonding processes such as glass frit bonding are reaching their limits. On the other hand, the introduction of novel wafer bonding processes in production lines is very challenging. This study was carried out to identify the most suitable wafer bonding process for different applications in a wafer foundry. 

The presentation will begin with a brief description of CeNTI, highlighting the different research departments, as well as the technological areas and focuses. This will be followed by an overview of the Illiance project, and subsequently, the iPower subproject. Within the iPower subproject, various technologies are under development. An update on the progress of these developments will be provided, and the results achieved will be presented.

Image-based detection is vital to a range of droplet microfluidics applications in biotechnology. A high enough image resolution and throughput in terms of framerate are necessary to capture and analyze droplet formation. In this work we demonstrate a setup based on a low-cost camera chip and FPGA to achieve an imaging throughput of ~150 fps at a resolution adequate to visualize individual droplets.

The presentation provides an overview about Parylene as a memristive material to establish memristors that can be directly integrated into the previously developed ultra-thin Parylene based packaging platform for flexible smart systems. Particularly, memristive test architectures used for the detailed analysis of the impact of the different parameters on the memristive properties are presented.

Bio-Remote Sensing in Real-Time Thermographic Face Detection and Respiratory Rate Measurement

We present a software tool for testing federated learning when data is limited. The key idea is to use data augmentation to artificially create multiple non-IID client datasets. This can then be used to test how different the client data can be for federated learning to still work. And which fedarted aggregation strategy best works with the challenges of the dataset.

Advanced micro integration technologies for fabrication of micro-ion-traps for a trapped-ion quantum computer

The integrated photonics industry focuses on combining photonic functions onto a single chip to enhance optical communication, imaging, and computing. Its success relies on a collaborative ecosystem involving academic research, industry partnerships, government support, and infrastructure development. This talk will explore how ecosystems like PhotonDelta contribute to this growth through stakeholder collaboration, scalable manufacturing, and support for startups. We will also address current challenges in the PIC industry and proactive initiatives for a brighter future in photonic integration.

Indium bump interconnect technology

The presentation summarizes our work on flexible large-area pressure sensors for integration with battery cells. Together with temperature sensors and combined in an array matrix, they allow for health monitoring of individual cells and avoidance of critical failures. The optimization of a piezoresistive functional layer processed by drop casting gives an insight in process development and technological integration.

High-Fidelity Synthetic Data-Driven Machine Learning Framework for Predictive Maintenance of Three-Phase Industrial Motors

Generative Pattern Learning for Missing Sensor Data Imputation in Industrial IoT