edfas.org 9 ELECTRONIC DEVICE FAILURE ANALYSIS | VOLUME 25 NO. 3 There has been promising progress in improving the signal-to-noise ratio by processing the amplitude and phase raw images and acquiring raw image data at different exposure times. In future studies, the aim is to develop algorithms that are sensitive enough to detect hotspots at varying exposure times. ACKNOWLEDGMENTS This research work is funded under SIT-MOE Ignition Grant, R-MOE-A403-F022, Singapore Institute of Technology (SIT), Singapore. We would like to thank all SIT members (University Co-Principal Investigator: Associate Professor Neelakantam Venkatarayalu, Associate Professor Indriyati Atmosukarto and Associate Professor Benjamin Premkumar Annamalai) for their contributions. This collaboration between SIT and Infineon offers opportunity to students to embark on applied research projects on problem statements and digitalization arising from the industry. REFERENCES 1. L.C. Wagner: “Failure Analysis,” Handbook of Semiconductor Manu- facturing Technology, Second Edition, 2007, https://doi.org/ 10.1201/9781420017663. 2. R.Z. Tan, et al.: “Localization of Hotspots from Lock-in Thermography Images for Failure Analysis,” 2021 IEEE 23rd Electronics Packaging Technology Conference (EPTC), p. 45-49, 2021, https://doi.org/10.1109/ EPTC53413.2021.9663910. 3. R.Z. Tan, et al.: “Supervised Image Retrieval and Ranking Technique for Lock-in Thermography Images,” 2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA), 2022, https://doi.org/10.1109/IPFA55383.2022.9915757. 4. R.J.G.B. Campello, et al.: “Density-based Clustering,” WIREs. Data Min. Knowl. Discov., 2020, https://doi.org/10.1002/widm.1343. 5. K. Simonyan and A. Zisserman: “Very Deep Convolutional Networks for Large-scale Image Recognition,” 2014, https://doi.org/10.48550/ arXiv.1409.1556. 6. A. Krizhevsky, I. Sutskever, and G.E. Hinton: “ImageNet Classification with Deep Convolutional Neural Networks,” Advances in Neural Information Processing Systems 2012, 25. ABOUT THE AUTHORS Kyu Kyu Thinn works for Infineon Technologies Asia Pacific Pte. Ltd. as a failure analysis engineer with the Product Analysis Team in Singapore and received her bachelor’s in electrical engineering from National University of Singapore. She has more than 10 years of experience in analyzing electrical failures of IC devices. Rui Zhen Tan is an assistant professor in the engineering cluster at Singapore Institute of Technology, SIT. Her research interests are in data analytics, predictive maintenance, and mathematical modeling. Prior to SIT, she was a postdoc at the Bioinformatics Institute, A*STAR. Teh Tict Eng has a master’s degree in electrical and electronics engineering from National University of Singapore. She has many years of experience in semiconductor industry, focusing on failure analysis and people management. Her expertise is in quality management system in failure analysis lab scope. Ming Xue has 40 years of electronics/semiconductor industrial experience: 10 years as RF designer, four years as a print circuit board assembly process engineer, and 26 years as head of Singapore FA and senior principal. He is key technical staff in Infineon Failure Analysis and Back End. Advertise in Electronic Device Failure Analysis magazine! For information about advertising in Electronic Device Failure Analysis: Kelly Johanns, Business Development Manager 440.671.3851, kelly.johanns@asminternational.org Current rate card may be viewed online at asminternational.org/mediakit.
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