Optimizing Semiconductor Yield with Robust WAT and PCM Processes

Wafer Acceptance Testing (WAT) and Process Control Monitoring (PCM) are instrumental elements within the semiconductor manufacturing industry. They are crucial tools utilized predominantly by fabless companies that seek to monitor and enhance their yield and defect rates.

WAT/PCM is the systematic measurement of various device parameters during different stages of wafer processing. It establishes control over the manufacturing process, leading to better consistency and quality of the final product. This measurement process aims to build a comprehensive database of process information, useful for a variety of process enhancement and control activities.

Understanding the Composition of WAT Data

On average, the wafer acceptance test (WAT) data consists of 40 to 100 tests per wafer. These tests help monitor the consistency of key parameters across the wafer lot, such as sheet resistance, oxide thickness, junction depth, gate length, and others. The data are critical to Fab’s (foundry’s) statistical process control system (spc), facilitating continuous improvement and helping to reduce variances in the manufacturing process.

The Role of Data Delivery and Yield Management Systems

After the completion of the semiconductor manufacturing process, the data is delivered to the fabless customer by the Fab. Typically, the data is delivered per lot, with one lot containing around 25 wafers. ASCII CSV or Excel is the preferred format for data delivery due to its wide acceptability by data analysis and management software.

This data is integral to modern yield management systems (YMS) or yield analysis systems. Whether they are cloud-based or on-premise, these systems securely process and store this data, ensuring its integrity and accessibility for subsequent analysis. The data is divided by wafer ID, and then further segmented into each site, i.e., the location of testing on the wafer, which allows for a comprehensive and detailed analysis.

Advantages of Data Analysis and Visualization

Although the size of WAT data is relatively small, it offers enormous benefits in terms of data analysis and visualization. Despite its compact size, it can provide comprehensive insights into the manufacturing process, potentially identifying variations or shifts in process parameters.

Visualization tools are extensively used to interpret WAT data. These tools help in identifying abnormalities or deviations in the data, which can serve as early warnings for potential yield loss or reliability issues. Detecting such issues at the earliest stages can help companies prevent substantial losses and continually improve their manufacturing processes.

The Importance of Correlating WAT Data

Correlating WAT data against wafer sort and final test data can provide meaningful insights into the causes of yield loss, reliability, and quality issues. This analysis can identify problematic trends, forming a foundation for effective communication with Fab to understand and rectify the root cause analysis in semiconductor. In essence, this correlation is a vital tool for decision-making and continuous improvement in the semiconductor manufacturing process.

Automation of the correlation process, achieved through the deployment of suitable algorithms and tools, enables rapid identification of problem areas. Once these areas have been identified, relevant teams can address the root cause, preventing recurrence and enhancing overall yield and reliability.

The Imperative for Clean and Consolidated Data

A well-implemented system that effectively processes and analyzes WAT data requires clean and consolidated data, especially at the final test stage. Given the vast number of parameters and the complexity of semiconductor devices, the risk of data contamination or inconsistency is high. Implementing data cleansing methodologies is crucial to ensure the integrity and reliability of the WAT data.

Effectively processing and analyzing WAT data can result in substantial cost savings in the semiconductor manufacturing industry by improving manufacturing processes, reducing yield loss, and alleviating reliability issues. Hence, investing in WAT/PCM monitoring and subsequent data management and analysis is a worthy endeavor for any semiconductor manufacturing organization.

Conclusion

The growth of the semiconductor industry is directly proportional to the ability to efficiently manufacture high-quality and high-performance semiconductor devices. This efficiency and quality heavily rely on robust monitoring and control of the manufacturing process, and here, WAT and PCM play a pivotal role.

WAT and PCM have been an integral part of the semiconductor manufacturing process for several decades. Still, with increasing chip complexity and decreasing geometries, their role is becoming even more critical. Moving forward, the semiconductor industry should continue to invest in advanced WAT/PCM systems, automated data analysis, and correlation tools, and stringent data management protocols to keep up with the ever-increasing demands of the market.

References

1. Dehan, M. (2010). Wafer acceptance test: What, why, and how? In 2010 IEEE International Test Conference.
2. Mathew, J., & Rao, M. (2003). Statistical analysis of wafer acceptance test (WAT) data. In 2003 IEEE International Conference on Semiconductor Electronics (ICSE).
3. Semiconductor Manufacturing Technology, 2nd Edition by Michael Quirk and Julian Serda, ISBN-13: 978-0130815200
4. Yield Management Strategies for Semiconductor Manufacturing Industries: A Structural Approach. Sunil Kumar Nair, World Scientific, 2018, ISBN: 9789813235865