The challenges before semiconductor fabs are expansive and evolving. As the size of chips shrinks from nanometers to eventually angstroms, the complexity of the manufacturing process increases in response. It can take hundreds of process steps and more than a month to process a single wafer. It can subsequently take more than another month to go through the assembly, testing, and packaging steps necessary to get to the final product.

Artificial Intelligence (AI) can be deployed within a fab to address the complexity and intricacy of semiconductor manufacturing. A fab generates petabytes of data as wafers go through the multitude of process and test operations. This wealth of data also presents a challenge in that it needs to be analyzed and acted on quickly to ensure tight process control, high yield, and avoid process excursions. Beyond navigating the complexity of the manufacturing process, new solutions are necessary to help make the process as efficient as possible and the yield as high as possible to produce the most business value for fabs.

The benefits of AI-enabled analysis tools for IC manufacturers

Traditional techniques to detect issues in the manufacturing process have run out of steam, especially at advanced technology nodes. For example, an engineer must do their own yield analysis to seek out potential problems. Once they identify an issue, they communicate with the defect and process teams to determine the root cause and then troubleshoot it. The defect team will begin work to find some correlation behind the issue and the process team troubleshoot and link it to the root cause.

All these steps take up significant time that could be focused on achieving the highest yield of chips possible, driving costs down and reducing time to market. One of the biggest benefits of enabling AI in analysis tools is that an engineer can quickly recognize and pinpoint an issue in a specific chip to see which process step and/or equipment has caused the issue.

Beyond the fast and accurate process control that AI allows for, there are numerous other benefits that result from the saved time and money, including:

• Predictive applications: Enables fabs to take leap from reactive to predictive process control
• Scalability: Analyzes petabytes of data, connects multiple fabs, and comes cloud-ready
• Efficiency: Allows fab to make better decisions and reduce false alarms

To enable the next generation of manufacturing, Synopsys is enabling AI and Machine Learning (ML) for a comprehensive process control solution.

Actionable insights with AI and ML

Wafer, equipment, design, mask, test, and yield are silos within a fab that can benefit from a comprehensive AI/ML enabled solution. Such a solution can specifically help engineers generate actionable insights into the following:

• Fault detection and classification (FDC)
• Statistical process control (SPC)
• Dynamic fault detection (DFD)
• Defect classification and image analytics
• Defect image analytics
• Decision support system (DSS)

Fast analysis of petabytes of data, from equipment sensors or process parameters, allows manufacturers to quickly identify the root cause of process excursions and take action to maintain yield.

AI and ML in the fab

Synopsys is a provider of software solutions for silicon manufacturing and silicon lifecycle management, including solutions for TCAD, mask solutions, and manufacturing analytics. Its existing solutions are connected to thousands of pieces of equipment over multiple fabs with millions of sensors, analyzing hundreds of petabytes of data. By providing real-time visibility into the manufacturing process, Synopsys enables predictive analytics and optimizes product quality and yield to help give semiconductor fabs a leg up in this competitive landscape.

Synopsys has introduced an AI/ML enabled software offering, Fab.da, to make semiconductor manufacturing efficient. Fab.da is a part of the Synopsys EDA Data Analytics solution, which brings together data analytics and insights from the entire chip lifecycle

It offers a complete data continuum by bringing together these different data types from many different sources into one platform for both advanced and mature node chips. This data continuum allows for high user productivity, maximum data scalability, and increased speed and accuracy in root cause analysis for issues.

Delivering process control solutions to manage complexity at leading-edge fabs, Fab.da can help chip designers and manufacturers drive operational excellence and productivity, providing a competitive edge in today’s manufacturing landscape.

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