TU Graz unveiled its latest initiative, the "CD Laboratory for EMC-Aware Robust Electronic Systems," on May 16, funded by the Austrian Federal Ministry of Labour and Economy. Led by Jan Hansen from the Institute of Electronics, the lab focuses on leveraging machine learning models to address challenges posed by electrostatic discharges and electromagnetic interference in shrinking electronic components. These issues can disrupt electronic systems, crucially impacting sectors like automotive engineering and medicine.
Minister Martin Kocher highlighted the importance of high reliability in electronic products, emphasizing their critical role in sensitive applications. He underscored the lab's role in integrating AI to analyze and apply extensive experience in system design, facilitated by collaborations with industry partners BMW Motoren, Infineon Technologies Austria and Infineon Technologies.
The lab's research spans two primary areas: mitigating influences on electronic components during design and manufacturing, and optimizing their integration into larger systems. Jan Hansen elucidated on the challenges posed by semiconductor production, where electrostatic charges can lead to defects, complicating fault diagnosis. The lab is pioneering new physical models to elucidate these complexities and refine production processes.
Environmental conditions, such as humidity variations, further complicate operational reliability. Here, machine learning proves invaluable, accelerating analysis by orders of magnitude compared to traditional methods. Hansen likened machine learning models to databases of precomputed results, expediting the assessment of diverse parameter distributions critical for system optimization.
Beyond manufacturing, the lab's innovations promise to revolutionize electronic vehicle drives, where factors like mechanical components, semiconductor characteristics, and electromagnetic emissions converge. Hansen highlighted the newfound ability to comprehensively model entire drive units, previously hindered by computational limitations, thereby enabling unprecedented optimization across diverse operational scenarios.
hristian Doppler labs exemplify TU Graz's commitment to applied basic research, fostering collaborations between top-tier scientists and forward-thinking companies. These labs, supported jointly by public funding bodies like the Federal Ministry of Labour and Economic Affairs and corporate partners, epitomize best practices in promoting innovation and industry-academic partnerships.
TU Graz's new CD lab represents a significant stride towards enhancing electronic component reliability and optimizing system performance across various industrial applications. The integration of advanced technologies like machine learning promises to reshape how electronic systems are designed and deployed, setting new benchmarks in reliability and efficiency.
