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Synopsys Unifies Electrical, Thermal, Mechanical, and Optical Analysis with Multiphysics Fusion Solutions

32 d ago

The semiconductor industry is shifting toward advanced packaging and chiplets-based architectures as traditional process-node scaling becomes more complex and costly. Manufacturers now use heterogeneous integration, combining multiple dies in a single package for higher performance and flexibility. This transformation creates massive data volumes across stages like wafer fabrication, sort, assembly, package test, final test, and system-level validation. However, data often remains isolated within each operation, limiting downstream decisions. PDF Solutions addresses this challenge with Data Feed Forward (DFF), an architecture designed to collect, transform, transport, and apply manufacturing and test information across the global supply chain. DFF enables upstream test results to influence downstream decisions, turning intelligence into actionable process improvements. It supports AI-driven test methodologies at scale, moving from experimentation to production. Key platforms include Exensio Test Operations, which provides real-time data collection and monitoring across sites, and Exensio StudioAI, which enables training, validation, deployment, and lifecycle management of machine-learning models. Together, they create infrastructure for operationalizing AI in semiconductor test. DFF enables per-device decisions based on individual manufacturing history, optimizing test coverage, quality screening, and resource allocation. Benefits span efficiency (reducing redundant testing and predictive burn-in), quality (earlier issue detection through connected data), and performance (richer AI models from cross-stage signal fusion). As advanced packaging reshapes the industry, competitive advantage depends on operationalizing intelligence across the manufacturing ecosystem. PDF Solutions’ DFF architecture, with Exensio platforms, provides the backbone for AI-driven test, helping semiconductor companies improve efficiency, quality, and performance in increasingly complex chiplets-based systems.