Synopsys Sunsets EES and FDC Fab Control Software – Legacy Tools Phase Out

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On July 8, EDA leader Synopsys announced it will discontinue two core wafer fab analysis tools: Equipment Engineering System (EES) and Fault Detection Classification (FDC). The company notified over a dozen chipmakers—including Samsung, SK Hynix, Kioxia, and Qorvo—between April and May, informing them of the end-of-life status.

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EES and FDC are critical for real-time equipment monitoring, anomaly detection, and defect prevention in wafer fabs. They help maintain yield and reduce downtime across both mature and advanced nodes.

Synopsys clarified that these are legacy diagnostics, not mission-critical modules, and will honor existing contracts and support while continuing to develop next-generation manufacturing tools.

The move reflects a broader industry shift. With rising complexity in AI chips, advanced packaging, and leading-edge processes, fabs increasingly demand AI-driven yield management, digital twins, and integrated cross-equipment data platforms—capabilities old tools cannot support. Synopsys is reallocating R&D resources toward high-margin segments like AI design and premium EDA.

The EES portfolio originated from Synopsys’ 2021 acquisition of Korea’s BISTel. Maintenance costs have been high and margins thin. The company is trimming related teams—dozens of positions already cut—and expects to finalize after-sales negotiations with all customers by July. Following its $35 billion Ansys acquisition in 2025, Synopsys is consolidating resources around full-system premium software, further de-emphasizing legacy fab control tools.

Data security is another factor driving customer replacement. EES and FDC require fabs to share process parameters, equipment status, and yield data. Major players like Samsung have already developed in-house control tools, reducing external commercial software demand.


From ICgoodFind: Legacy fab software is dying – AI-native tools are taking over. Synopsys is betting big on design, but fabs are building their own control layers. The real question: who owns the data wins.

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