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Managing Semiconductor Test Data in Current Age

December 06, 2016, anysilicon

We are living in a fast changing environment, from light bulbs to cars, everything is getting advanced and more efficient. The functionalities of electronic devices are increasing and the associated costs to produce them are decreasing, intensifying the competition. In such a scenario, it becomes challenging and difficult to sustain the business and stay competitive if the companies don’t upgrade and optimize. The trend in Semiconductor Data Analysis Software development is following the same trajectory, getting complex and advanced, capable of performing a variety of in-depth analysis and generating insightful reports related to data coming out of various nodes of semiconductor wafer fabrication process like Wafer Acceptance Test (WAT) data, Wafer Sort or Final Test data. Thus, making the process of semiconductor test data management intuitive and efficient for the test and product engineers.

 

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Semiconductor data analysis was earlier done using basic STDF data analysis software which required all the data to be of a single standard STDF format, this was not only cumbersome and time consuming for engineers but in most cases non-scalable. With the advancement in assembly test floor operations and addition of the complex equipment, the data generated is now collected in real-time with the ability to trigger alarms and control the assembly line in case of occurrence of failures or issues related to wafers or the test equipment. These highly advanced and complex machines generate other proprietary test data formats than just the STDF format with data mapping unique to the company’s individual specifications and associated customizations. This specialized data is cleansed by the semiconductor test data analysis tools that have custom built parsers capable of reading majority of the test data formats of the semiconductor industry, storing all the data in a centralized database with mapping done in a way that can trace the origin and movement of data throughout the supply chain.

 

Further, the advanced semiconductor test data management tools allows the users to create genealogy tree of the wafers being tested. The tools capture information related to wafer ID, Lot ID and other die traceability data points that are linked from one stage to the other, giving a clear and precise picture of the performance of a specific die or wafer during the whole manufacturing process. This makes it easier to track the wafers irrespective of the geographic location of the nodes and the data mapping mechanism employed. This genealogy helps in early detection of failing lots and prevents from packaging devices on wafers that will not function properly or will have performance issues once delivered to the customer.

 

The modern test data management tools also helps in identifying issues caused by equipment failures and anomalies. These issues not only reduces yield by raising false flags – incorrectly marking wafers as bad that are not bad in real, but also decreases equipment throughput, affecting the operational efficiency of the manufacturing supply chain. Semiconductor test data management tools are also deployed at test sites and are connected with testers capturing real-time test data of wafer being probed. This test data is then analyzed through complex algorithms such as PAT, DPAT and GDBN. These advancements have made managing semiconductor test data easier and the insights gained more effective and meaningful.

 

Author Bio:

Irteza Ubaid is working as a senior strategy executive at yieldWerx, which is a semiconductor yield management software solution provider company that helps IC manufacturers carry out huge data extraction, its transformation and  loading lot genealogy and product data from MES and ATE systems.