TY - CHAP A1 - Stenzel, Gerhard A1 - Schmid, Kyrill A1 - Kölle, Michael A1 - Altmann, Philipp A1 - Lingsch-Rosenfeld, Marian A1 - Zorn, Maximilian A1 - Bücher, Tim A1 - Gabor, Thomas A1 - Wirsing, Martin A1 - Belzner, Lenz ED - Steffen, Bernhard T1 - SEGym: Optimizing Large Language Model Assisted Software Engineering Agents with Reinforcement Learning T2 - Bridging the Gap Between AI and Reality, Second International Conference, AISoLA 2024, Crete, Greece, October 30 – November 3, 2024, Proceedings UR - https://doi.org/10.1007/978-3-031-75434-0_8 Y1 - 2024 UR - https://doi.org/10.1007/978-3-031-75434-0_8 SN - 978-3-031-75434-0 SP - 107 EP - 124 PB - Springer CY - Cham ER - TY - JOUR A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Elger, Gordon T1 - Solder joint lifetime model using AI framework operating on FEA data JF - Engineering Failure Analysis N2 - The thermo-mechanical reliability of electronic systems is often limited by the crack growth within the solder joints. Addressing this issue requires careful consideration of the design of the package and solder pads. Finite Element Analysis (FEA) is widely used to predict crack growth and to model their lifetime. Traditionally, FEA post-processing methods rely on human expertise to select appropriate regions for evaluating plastic and creep strain at critical locations and correlating these values with experimental data using the Coffin-Manson equation, which predicts fatigue lifetime based on cyclic plastic strain. This study introduces a novel method for FEA post-processing of surface-mounted devices (SMD) on printed circuit boards (PCB) using artificial intelligence. The method transforms the FEA data into a 2D grid map of creep strain values and employs a Convolutional Neural Network (CNN) for automatic feature extraction. Afterwards, a fully connected layer correlates the extracted features with the experimental measured solder joint lifetime, effectively capturing nonlinear relationships. The study focuses on the development of the concept of crack formation in the solder interconnects of ceramic based high-power LED packages used in the automotive industry for headlights. The validated FEA model is based on an extensive data set of 1800 LED packages including seven different ceramic-based LED packages and five different solders. The design of the ceramic LED package covers two-pad and three-pad footprint for soldering and thin film and thick film metallized ceramic carriers. Results show a strong agreement (R2 Score is 99.867 %) between simulations and experimental data for ceramic LED packages. This automatic feature extraction from FEA data sets a new benchmark for improving solder reliability predictions, and it has proved to be better than established methods for lifetime prediction of solder joints. UR - https://doi.org/10.1016/j.engfailanal.2024.109032 Y1 - 2024 UR - https://doi.org/10.1016/j.engfailanal.2024.109032 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-53803 SN - 1350-6307 VL - 2025 IS - 167, Part B PB - Elsevier CY - Oxford ER - TY - CHAP A1 - Mohd, Zubair Akhtar A1 - Kreiner, Christian A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Tetzlaff, Ulrich A1 - Elger, Gordon T1 - Fully Connected Neural Network (FCNN) Based Validation Framework for FEA Post Processing to Improve SAC Solder Reliability Analysis T2 - 2024 IEEE 10th Electronics System-Integration Technology Conference (ESTC), Proceedings UR - https://doi.org/10.1109/ESTC60143.2024.10712023 Y1 - 2024 UR - https://doi.org/10.1109/ESTC60143.2024.10712023 SN - 979-8-3503-9036-0 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Elger, Gordon T1 - LEDs Lifetime Prediction Modeling: Thermomechanical Simulation for SAC305 and SAC105 T2 - 2024 25th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) UR - https://doi.org/10.1109/EuroSimE60745.2024.10491530 Y1 - 2024 UR - https://doi.org/10.1109/EuroSimE60745.2024.10491530 SN - 979-8-3503-9363-7 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schwan, Hannes A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Layer Resolved Thermal Impedance Measurement with Laser Stimulated Transient Thermal Analysis of Semiconductor Modules T2 - THERMINIC 2024: Proceedings of 2024, 30th International Workshop on Thermal Investigations of ICs and Systems UR - https://doi.org/10.1109/THERMINIC62015.2024.10732233 Y1 - 2024 UR - https://doi.org/10.1109/THERMINIC62015.2024.10732233 SN - 979-8-3503-8782-7 PB - IEEE CY - Piscataway ER -