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Webinar: Faster Design Spec to Implementation using IP-XACT

32 d ago

One of the hardest things to do in life is ask for help, a challenge rooted in the semiconductor industry’s siloed past. Intel has struggled with yield since its 14nm FinFET nodes. PDF Solutions, a publicly traded semiconductor analytics and manufacturing software company (NASDAQ: PDFS) based in Santa Clara, California, helps chipmakers improve yield, quality, reliability, and profitability by collecting and analyzing data from fabrication, test, assembly, and field operations. Founded in 1991 by John K. Kibarian and Kimon W. Michaels, it is the #1 yield expert, having worked with 18 of the top 20 semiconductor companies. In July 2025, Intel and PDF Solutions announced a collaboration to redefine advanced semiconductor manufacturing. Intel CEO Lip-Bu Tan and PDF CEO John Kibarian have an active executive-level business relationship, with both managing projects directly. Tan has emphasized improving manufacturing execution and operational discipline, with yield improvement at the center. Intel’s success with its 18A/P process technology is closely watched. After years of manufacturing challenges, Intel has made progress, aided by partnership with PDF. Yield learning has become exponentially harder at advanced nodes. Technologies like RibbonFET gate-all-around transistors and PowerVia backside power delivery in Intel 18A create new integration challenges and generate vast data. Traditional statistical process control is insufficient. PDF Solutions’ Exensio platform combines data from equipment, metrology, inspection, test, and design into a unified analytics environment to identify yield limiters and accelerate root-cause analysis. For Intel 18A-P, yield learning is critical as the node serves Intel’s own products and Intel Foundry customers. Achieving competitive yields demonstrates foundry credibility. PDF’s analytics enable faster identification of defect patterns and process excursions. As Intel moves beyond 18A-P to 14A, which will introduce even greater complexity, data-driven yield optimization becomes foundational. The partnership reflects a broader trend: semiconductor leadership now depends not only on transistor innovation but also on the ability to collect, analyze, and act on manufacturing data at unprecedented scale.