Advantest, proteanTecs, and PDF Solutions are teaming up to develop solutions that improve semiconductor manufacturing yield, reliability, and quality. 

Advantest has created a real-time data infrastructure (RTDI), called ACS that transforms testing. proteanTecs is pioneering deep data analytics for advanced electronics monitoring, while PDF Solutions is a leading provider of comprehensive data and analysis solutions for the semiconductor ecosystem. 

Together, they aim to address challenges for common customers, like increasing complexity, shrinking process nodes, and demand for higher quality control in order to minimize cost and expedite time to market. The collaboration leverages AI and machine learning to enable real-time decisions for quality and reliability with an interoperable open ecosystem that is designed to be secure and allows for scalable semantic models, reusable models, and impactful ML ops.

Advantest, proteanTecs, and PDF Solutions have a history of successful collaboration, with proven solutions already in the market, including Dynamic Parametric Test, which is designed for the early detection of anomalies in the wafer acceptance test, and a die-to-die solution that collects and analyses high-speed interconnections between die. All three companies aim to look forward and develop applications that span different stages of testing from scribe line testing to system-level tests.

In this podcast, we discuss how AI and machine learning are being used in the semiconductor industry, particularly in the automotive and high-performance computing sectors. We discuss how these technologies can improve quality control, optimize testing processes, and help alleviate supply chain bottlenecks. They also emphasize the importance of understanding device performance through measurement and analytics to make better decisions about test flow and yield. Optimizing throughput, quality, and yield is seen as a key factor in addressing supply chain challenges.

Finally, we discuss the potential challenges and opportunities for the semiconductor industry as AI technology advances. Emphasizing the need to make advanced AI/ML analytical techniques more accessible and easier to integrate into semiconductor operations, particularly in test operations. We discuss what the concept of "mostly good die" is, where products can operate robustly despite not having all transistors working perfectly, as this concept highlights the importance of understanding how to repair and optimize chip performance in real-time.

Don’t miss out on this exciting opportunity to learn more about our collaboration and the latest trends leaders of the semiconductor industry are working on!

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