Posted in Semiconductor Engineering. Click here to view original article
By: Christophe Begue
Accurate real-time data is the bridge between design, manufacturing, and operations.
As the semiconductor industry evolves toward a $1-trillion revenue milestone by 2030, fueled largely by AI applications, its challenges have magnified—a globalized supply chain, increasingly complex chip architectures and mounting cybersecurity demands.
Assessing how data collaboration occurs within the ecosystem is essential, while secure data collaboration facilitated by cutting-edge platforms is an imperative for unlocking greater efficiency, innovation and productivity.
Secure data sharing promotes collaboration across the semiconductor value chain, presenting opportunities and challenges. Companies like PDF Solutions are setting the standard.
Moving beyond Moore’s Law
The deceleration of Moore’s Law presses the semiconductor industry to innovate with 3D architectures, chiplets and hybrid packaging, technologies with significant complexities that are a result of interdependencies between equipment manufacturers, foundries and fabless chip designers.
AI presses the semiconductor industry to innovate, too. According to industry forecasts, AI-related applications will account for 70% of semiconductor revenue by 2030. AI chip architectures like these need massive volumes of data to be collected, aligned and analyzed across the ecosystem, making secure data collaboration a critical enabler for AI adoption.
Data collaboration is key
Data has strategic value for semiconductor companies. Fab operators rely on equipment-level data for predictive maintenance. Test facilities require traceable test data to improve yields. Fabless chip designers depend on performance data from foundries to refine their designs.
Inefficiencies emerge without visibility and a mechanism to securely share data between stakeholders. Accurate real-time data is the bridge between design, manufacturing and operations. Secure data collaboration facilitates this connection while ensuring privacy, intellectual property (IP) protection and operational control.
Barriers for secure data collaboration have hampered seamless operations and range from data silos and security risks to scalability and ownership.
Core manufacturing data and test data are often scattered, leading to data silos that delay insights and inefficiencies. A connected supply chain introduces cybersecurity vulnerabilities and risk with IP theft. Collaborating efficiently over global supply chains requires scalable infrastructures that handle massive data volumes.
For collaborative efforts to succeed, ownership of shared data and IP must be clearly defined and respected. AI-powered platforms are breaking down these barriers while ensuring security and trust.
Connecting the ecosystem
PDF Solutions is at the forefront of secure data collaboration with close to 30 years of experience and 350 customers. Its tools unlock efficiencies by combining actionable insights with secure platforms.
Its Exensio analytics platform integrates manufacturing, test and operational data through a scalable architecture and semiconductor-specific semantic data model designed for advanced analytics. It transforms raw data into actionable insights that optimize decision-making at every node in the ecosystem.
A recent addition to the portfolio is SecureWISE for secure semiconductor collaboration. Originally built for semiconductor manufacturing equipment, it provides secure, remote connections that allow stakeholders to work together without compromising safety or data privacy. It enables real-time, secure connections between equipment vendors, fabs and fabless companies. Equipment manufacturers can access specific tools at fabs to analyze machine-level data, enabling predictive maintenance and efficient troubleshooting, for example.
An AI-driven collaboration platform, such as the combination of SecureWISE and the Exensio platform, ensures a smarter, safer semiconductor supply chain and a unified framework that empowers equipment vendors, fabs and fabless companies to securely collaborate.
AI-driven collaboration platforms enable organizations to collaborate freely while maintaining high levels of security and accelerating operational success. Embedding AI into the architecture enables rapid analytics that deliver actionable insights across multiple domains, including process control, product screening and operational optimization. Each stakeholder retains control of their data while benefiting from collective intelligence within a secure ecosystem.
Semiconductor manufacturing is at a crossroads as the industry balances innovation and operational efficiency while contending with unprecedented cybersecurity threats. Secure data platforms are more than operational enablers—they form the backbone for achieving global AI-driven ambitions. Semiconductor businesses must adopt secure collaboration practices and data platforms at scale to keep pace with market demand, allowing each stakeholder to operate competitively in an increasingly globalized ecosystem.
Secure data sharing isn’t just about protecting intellectual property—it’s about unlocking new levels of innovation and efficiency across the semiconductor industry. The convergence of AI, data scalability and secure connectivity offers unprecedented opportunities to enhance productivity and reduce costs across the value chain.