Mr. Don ONG
Director and Head of Innovation, Advantest Field Service Business Group Advantest, Singapore
Mr. Don Ong is the Director and Head of Innovation for Advantest Field Service Business Group – a division of Advantest Inc. He has over 18 years of experience in the semiconductor industry spanning multiple roles including program management, product, application and test engineering in both Silicon Valley and Asia. He has a Bachelor in Electrical and Electronics Engineering from Nanyang Technological University (Singapore) and a Master’s of Studies from University of Cambridge (United Kingdom).
Presentation Title:
Hyper-Edge Computing and Open Analytics Ecosystem for Heterogenous Package Testing Using AI and Machine Learning
Semiconductor test, like many industries, is experiencing a data revolution. With unprecedented demand for electronics of ever higher complexity, and in the face of a bend in the curve of Moore’s Law, manufacturers are moving to a chiplet-based paradigm. These products enable us to cram incomprehensible numbers of components into a growing array of products, resulting in the world’s total output of a staggering 1.6x1021 transistors in 2021 according to VLSI Research. All those components must be tested, and the corresponding amount of test data would meet any reasonable definition of “Big Data”. Compounding the problem, the sources of data feeding the test process are becoming more diversified, and traditional production electrical data is being augmented with equipment metadata, optical inspection data, on-chip lifecycle management data, and others, limited only by our collective creativity.
In this presentation, we describe data analytics-related trends that we observe in the industry. We elaborate the challenges that we see such as high-performance real-time decision-making in test operations and IP and data security across a disaggregated supply chain. We will give some specific examples of collaborative solutions being developed by Advantest and a wide ecosystem of analytics partners to address these issues including adaptive test solutions at parametric (e-test) and production test and show how they solve real industry problems and result in significant improvements in product decision-making, test cost, yield and capacity (the last two critical in the time of industry-wide shortages). We conclude with observations about what we see as crucial next steps.