In today’s highly competitive semiconductor industry, manufacturers face increasing pressure to improve yields, reduce costs, and accelerate time-to-market. PDF Solutions has positioned itself at the forefront of this challenge with its Exensio platform, a comprehensive data and analytics solution designed to provide innovative solutions to access, organize, and analyze data across the entire manufacturing lifecycle.
The Vision: Data-Driven Manufacturing Excellence
PDF Solutions’ vision is to be the world’s leading data and analytics platform for the semiconductor and electronics ecosystems. This vision is centered around providing innovative solutions, like the Exensio platform, that enable semiconductor and electronics companies to access, organize, and leverage data for improved analysis and control of their manufacturing processes. The ultimate goal is helping manufacturers achieve faster time-to-market, higher yields, improved quality, and reduced costs through enhanced operational efficiencies.
Spanning the Entire Manufacturing Lifecycle
What makes Exensio particularly powerful is its ability to span the entire semiconductor manufacturing lifecycle – from IC design and product development through fabrication, testing, assembly, and enterprise-level business processes. This end-to-end perspective allows for unprecedented visibility and control across traditionally siloed operations.
The platform’s reach is impressive, with over 55,000 fab tools connected through its connectivity solutions, more than 40,000 process tools under process control, and a customer base exceeding 350 organizations across 20 countries. These customers include fabless companies, independent device manufacturers, foundries, OSATs, and system-level manufacturers. Exensio is the leading solution for die traceability and the fastest-growing company in test operations.
Creating Digital Twins for Smart Manufacturing
At the heart of Exensio’s capabilities is the creation of digital twins – virtual representations of physical manufacturing processes. These digital twins are built by collecting data from various sources, including tool data, metrology data, events, consumables, parametric sort, assembly and test data, then structuring this data with a semantic data model that captures the complex relationships between different data types. The platform also collects assembly and system-level data, linking it to enterprise resource planning and business data
This approach enables manufacturers to:
- Collect and access data from across the entire manufacturing chain
- Organize information into a knowledge-based semantic data model
- Generate insights through advanced analytics, AI, and machine learning
- Take action by connecting back to control systems to impact outcomes
The Semantic Data Model: Foundation for Success
The semantic data model serves as the foundation for Exensio’s capabilities, essentially functioning as a digital twin that ensures end-to-end data completeness and quality. This model encompasses critical elements such as:
- Materials descriptions and metadata
- Equipment history and tool information
- Defect and metrology data
- Events that occur during manufacturing
- Assembly and system-level data
- Business and financial information
By integrating all this data into a cohesive model, Exensio enables manufacturers to identify patterns, predict outcomes, and make data-driven decisions that would otherwise be impossible.
Addressing Key Manufacturing Challenges
Exensio addresses several critical challenges in semiconductor manufacturing:
- Yield and quality improvement
- Faster time-to-value for new product introduction and ramp
- Breaking down data silos for integrated decision-making
- Spanning geographically distributed supply chains
- Identifying weaknesses and improving efficiency
By spanning the entire semiconductor lifecycle, Exensio delivers efficiency and identifies areas of improvement.
These challenges are addressed through the use of the extensive semantic data model, flexible and scalable data architecture, and insights generated through AI and machine learning – all while maintaining robust security to protect sensitive intellectual property.
Real-World Results
The value of Exensio is evident in the results reported by customers:
- Up to 20% reduction in low yield tails
- Up to 10% improvement in device yields
- 30% faster yield ramps
- Outgoing product quality improved to less than one defect per million parts
- Up to 20% improvement in test or equipment utilization
- 5X improvement in engineering efficiency
These impressive results are achieved by combining fault detection and classification information with manufacturing and metrology data, applying analytics to reduce false alarms, preventing excursions, and tightening parametric and yield distributions.
Future Directions
Looking ahead to 2025, PDF Solutions is focused on enhancing the Exensio platform in several key areas:
- Improving user experience through analytics-driven interface enhancements
- Partnering with companies to deliver advanced applications and new AI capabilities
- Strengthening security and traceability across distributed supply chains
- Expanding remote data exchange services
- Advancing AI and machine learning capabilities from basic statistical analysis to deep learning models
- Improving scalability for faster processing of large datasets
- Enabling integration with third-party applications and data sources
Conclusion
In an industry where margins are tight and competition is fierce, the ability to leverage data effectively can make the difference between success and failure. PDF Solutions’ Exensio platform provides semiconductor manufacturers with the tools they need to collect, organize, analyze, and act on manufacturing data across the entire product lifecycle.
By creating digital twins of manufacturing processes and applying advanced analytics, AI, and machine learning, Exensio enables manufacturers to identify issues, optimize processes, and drive continuous improvement – ultimately leading to higher yields, better quality, and improved profitability.
To learn more about the Exensio Platform:
Exensio Manufacturing Analytics on PDF.com Video Page
Exensio Manufacturing Analytics Datasheet