Integrated electronic circuits (ICs) today are ubiquitous in that they affect every aspect of our daily lives, ranging from use within all forms of mobile devices (smart phones, laptops, etc.) to all modes of transportation (cars, aircraft, etc.). Advances in electronics also form the foundation for the recent and forthcoming advances in machine learning, artificial intelligence, autonomous vehicles, etc. The research work stemming from the project will aid the continued advancement of the electronic semiconductor industry by helping leading companies ensure that electronics work properly and reliably over long time periods. Additionally, the research conducted will include undergraduate student researchers, and the results will be disseminated to the research community, and incorporated into post-secondary curriculum.
The research will specifically examine how electronic failures are modeled, and for any shortcomings discovered, new models that are more accurate will be developed. While it is widely known that model effectiveness greatly depends on the IC and its fabrication, it is not known which models will be proven ineffective beforehand. In addition, especially for cutting-edge technologies, it is expected that there also will be a need for new, more accurate fault models for state-of-the-art ICs. Therefore, the objective of this research is to develop a comprehensive data-driven methodology for the continuous evaluation and development of fault models. Data from failed ICs will be analyzed to understand the likelihood and types of failures. For the expected mismatch between existing models and measured data, new models will be proposed and evaluated. Successfully meeting the objective of this research would will enable IC manufacturers to produce more reliable ICs at much lower cost.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
