2024

Vol.31 No.3

Current Issue Archives
Search
Advanced Search
Editorial Office

Review

  • Journal of the Microelectronics and Packaging Society
  • Volume 30(1); 2023
  • Article

Review

Journal of the Microelectronics and Packaging Society 2023;30(1):30-41. Published online: May, 11, 2023

PDF Full Text XML

DOI : doi.org/10.6117/kmeps.2023.30.1.030

Signal-Based Fault Detection and Diagnosis on Electronic Packaging and Applications of Artificial Intelligence Techniques

  • Tae Yeob Kang1 and Taek-Soo Kim2,†
    1 School of Industrial and Mechanical Engineering, The University of Suwon, 2 Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST)
Corresponding author E-mail: tskim1@kaist.ac.kr
Abstract

With the aggressive down-scaling of advanced integrated circuits (ICs), electronic packages have become the bottleneck of both reliability and performance of whole electronic systems. In order to resolve the reliability issues, Institute of Electrical and Electronics Engineers (IEEE) laid down a roadmap on fault detection and diagnosis (FDD), thrusting the digital twin: a combination of reliability physics and artificial intelligence (AI). In this paper, we especially review research works regarding the signal-based FDD approaches on the electronic packages. We also discuss the research trend of FDD utilizing AI techniques.

Keywords Artificial Intelligence, Reliability Physics, Electronic Packaging, Fault Detection and Diagnosis

REFERENCES
  • IEEE Electronic Packaging Society, "Heterogenous Integration Roadmap 2021 Edition", IEEE, (2021).
  • D. Kwon, M. R. Hodkiewicz, J. Fan, T. Shibutano, and M. G. Pecht, "IoT-Based Prognostics and Systems Health Management for Industrial Applications", IEEE Access, 4, (2016).
  • Y.-J. Park, S.-K. S. Fan, and C.-Y. Hsu, "A Review on Fault Detection and Process Diagnositics in Industrial Processes", MDPI Processes, 8, (2020).
  • A. Moradzadeh, B. Mohammadi-Ivatloo, K. Pourhossein and A. Anvari-Moghaddam, "Data Mining Applications to Fault Diagnosis in Power Electronic Systems: A Systematic Review", in IEEE Transactions on Power Electronics, 37(5), (2022).
  • W. G. Fenton, T. M. McGinnity and L. P. Maguire, "Fault diagnosis of electronic systems using intelligent techniques: a review", in IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 31(3), (2001).
  • K. Chen, C. Huang, and J. He, "Fault detection, classification and location for transmission lines and distribution systems: a review on the methods", High Voltage, 1(1), (2016).
  • H. Tanaka and K. Kim, "Introduction of Reliability Test Technology for Electronic Package", J. Microelectron. Packag. Soc., 19(1), (2012).
  • B. Chistiansen, "Choosing a Maintenance Strategy Right for You", https://limblecmms.com/blog/maintenance-strategy, (2021).
  • F. Harada, "An Issue and Foresight for Accelerated Test in Reliability Engineering", (In Japanese), J. Reliability Engineering Association of Japan, 31(2), 101 (2009).
  • S. Suh, H. Lee, J. Jo, P. Lukowicz, Y. O. Lee, "Generative Oversampling Method for Imbalanced Data on Bearing Fault Detection and Diagnosis", Applied Sciences, 9(4), (2019).
  • J. Choi, "A review on prognostics and health management and its applications", Journal of Aerospace System Engineering, l8(4), (2014).
  • An et al., "Prediction of remaining useful life under different conditions using accelerated life testing data", JMST, 32(6), (2018).
  • A. Moradzadeh, B. Mohammadi-Ivatloo, K. Pourhossein and A. Anvari-Moghaddam, "Data Mining Applications to Fault Diagnosis in Power Electronic Systems: A Systematic Review", IEEE Transactions on Power Electronics, 37(5), (2022).
  • H. Qi, N. M. Vichare, M. H. Azarian, N. Azarian, M. Pecht, "Analysis of Solder Joint Failure Criteria and Measurement Techniques in the Qualification of Electronic Products", IEEE Trans. on Components and Packaging Technologies, 31(2), (2008).
  • J. F. Caers, E. H. Wong, S. K. W. Seah, X. J. Zhao, C. S. Selvanayagam, W. D. van Driel, N. Owens, M. Leoni, L. C. Tan, P. L. Eu, Y.-S. Lai, C.-L. Yeh, "A Study of Crack Propagation in Pb-free Solder Joints under Drop Impact", 2008 58th Electronic Components and Technology Conference (2008).
  • D. Kwon, "Detection of interconnect failure precursors using RF impedance analysis", in Ph.D. dissertation, University of Maryland, College Park, 53-64 (2010).
  • A. K. M. M. Alam, M. Kandic and G. E. Bridges, "TDRBased Fault Detection in Grounding Electrodes Using a Rod Insertion Method", 2021 IEEE 19th International Symposium on Antenna Technology and Applied Electromagnetics (ANTEM), Winnipeg, (2021).
  • D. Kwon, M. Azarian, M. Pecht, "Early detection of interconnect degradation by continuous monitoring of RF impedance", IEEE Transactions on device and materials reliability, 9(2), (2009).
  • N. J. Jameson, M. H. Azarian and M. Pecht, "ImpedanceBased Condition Monitoring for Insulation Systems Used in Low-Voltage Electromagnetic Coils", IEEE Transactions on Industrial Electronics, 64(5), (2017).
  • K. Wang, H. Guo, A. Xu, M. Pecht, "Degradation Monitoring of Insulation Systems Used in Low-Voltage Electromagnetic Coils under Thermal Loading Conditions from a Creep Point of View", Sensors, 20(13), (2020).
  • I. Shin, K. Koo, D. Kwon, "Development of a non-invasive on-chip interconnect health sensing method based on bit error rates", Sensors, 18(10), (2018). https://doi.org/10.3390/s18103415
  • J. Lee and D. Kwon, "A digital technique for diagnosing interconnect degradation by using digital signal characteristics", Microelectronics Journal, 60(C), (2017).
  • M. Waqar, Y.-B. Chang, J. Kwon, J.-H. Kim and S. Baeg, "DDR4 Ball Grid Array Package Intermittent Fracture Effect on Signal Integrity", IEEE Transactions on Components, Packaging and Manufacturing Technology, 13(1), (2023).
  • J. Putaala, T. Kangasvieri, O. Nousiainen, H. Jantunen, and M. Moilanen, "Detection of Thermal Cycling-Induced Failures in RF/Microwave BGA Assemblies", IEEE Trans. on Electronics Packaging Manufacturing, 31(3), (2008).
  • S. Foley, L. Floyd, and A. Mathewson, "A Novel Fast Technique for Detecting Voiding Damage in IC Interconnects", Microelectronics Reliability, 40, (2000).
  • R. Ghaffarian, G. Nelson, M. Copper, L. D. Lam, S. Strudler, A. Umdekar, K. Selk, and B. Bjorndahl, "Thermal Cycling Test Results of CSP and RF Package Assemblies", International Conference of Surface Mount Technology Association, Chicago, (2000).
  • T. Y. Kang, D. Seo, J. Min and T.-S. Kim, "Quantification of Performance Variation and Crack Evolution of Bond-Wire Interconnects Under Harsh Temperature Environments by SParameter Analysis", in IEEE Transactions on Components, Packaging and Manufacturing Technology, 11(6), (2021).
  • D. Kwon, M. H. Azarian and M. Pecht, "Remaining-Life Prediction of Solder Joints Using RF Impedance Analysis and Gaussian Process Regression", IEEE Transactions on Components, Packaging and Manufacturing Technology, 5(11), (2015).
  • A. S. Narwariya, P. Das, S. Khursheed and A. Acharyya, "Operational Age Estimation of ICs using Gaussian Process Regression", 2022 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), Austin, (2022).
  • C. Li, Z. Liu, Y. Zhang, L. Chai, and B. Xu, "Diagnosis and location of the open-circuit fault in modular multilevel converters: An improved machine learning method", Neurocomputing, 331, (2019).
  • M. Fei, L. Ning, M. Huiyu, P. Yi, S. Haoyuan, and Z. Jianyong, "On-line fault diagnosis model for locomotive traction inverter based on wavelet transform and support vector machine", Microelectron. Rel., 88(90), (2018).
  • A. Martinez, S. Khursheed, T. Alnuayri, and D. Rossi, "Online remaining useful lifetime prediction using support vector regression", IEEE Trans. Emerging Topics in Computing, 6, (2022).
  • N. T. Nguyen and H. P. Nguyen, "Fault diagnosis of voltage source inverter for induction motor drives using decision tree", Proc. Lecture Notes Elect. Eng., 398, (2017).
  • T. Y. Kang, "Reliability Assessment on Electrical Interconnects using S-parameter Pattern Analysis", in Ph.D. dissertation, pp. 88-98, KAIST, Daejeon, (2021).
  • G. H. Bazan, P. R. Scalassara, W. Endo, A. Goedtel, R. H. C. Palacios, and W. F. Godoy, "Stator short-circuit diagnosis in induction motors using mutual information and intelligent systems", IEEE Trans. Ind. Electron., 66(4), (2019).
  • Z. Ke et al., "Single-submodule open-circuit fault diagnosis for a modular multi-level converter using artificial intelligentbased techniques", Proc. IEEE Appl. Power Electron. Conf. Expo., (2019).
  • D. N. Coelho, G. A. Barreto, and C. M. S. Medeiros, "Detection of short circuit faults in 3-phase converter-fed induction motors using kernel SOMs", in Proc. 12th Int. Workshop SelfOrganizing Maps Learn. Vector Quantization, (2017).
  • Q. Lin, S. Chen, and C.-M. Lin, "Parametric fault diagnosis based on fuzzy cerebellar model neural networks", IEEE Trans. Ind. Electron., (2019).
  • Q. Sun, Y.Wang, and Y. Jiang, "A novel fault diagnostic approach for DC-DC converters based on CSA-DBN", IEEE Access, 6, (2018).
  • L. Gaber, A. I. Hussein, M. Moness, "Fault Detection based on Deep Learning for Digital VLSI Circuits", Procedia Computer Science, 194, (2021).
  • L. Xu, M. Cao, B. Song, J. Zhang, Y. Liu, and F. E. Alsaadi, "Opencircuit fault diagnosis of power rectifier using sparse autoencoder based deep neural network", Neurocomputing, 311, (2018).
  • https://www.codingworldnews.com/news/articleView.html?idxno=2036
  • M. Raissi, P. Perdikaris, G. E. Karniadakis, "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations", Journal of Computational Physics, 378, 686-707 (2019). https://doi.org/10.1016/j.jcp.2018.10.045