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Overview of Big Data Analytics in Semiconductor Yield Management

As semiconductor manufacturing yield advances, the industry is increasingly turning to big data analytics to manage yield and improve productivity. By understanding the relationship between process variation and device performance, manufacturers can identify areas for improvement and make informed decisions about process changes.

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Overview of Big Data Analytics in Semiconductor Yield Management

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  1. Overview of Big Data Analytics in Semiconductor Yield Management Big Data Analytics in Semiconductor Yield Management

  2. Introduction to Big Data • As semiconductor manufacturing yield advances, the industry is increasingly turning to big data analytics to manage yield and improve productivity. By understanding the relationship between process variation and device performance, manufacturers can identify areas for improvement and make informed decisions about process changes.

  3. Cont’d •  Big data (semiconductor data) analytics can help semiconductor manufacturers in a number of ways, including: • 1. Analyzing production data to identify process variation and potential causes of yield loss; • 2. Providing real-time feedback on process changes to help optimize manufacturing; • 3. Predicting device performance based on process conditions; • 4. Providing early warning of potential yield issues; and • 5. Helping to track the root cause of yield issues.

  4. How Big Data is Applied in Semiconductor Yield Management • Semiconductor yield management systems is the art and science of achieving the highest possible yield from a semiconductor manufacturing process. In order to achieve this, manufacturers must track, analyze and optimize a huge amount of data. This data includes everything from equipment performance data to recipes and process parameters.

  5. Cont’d • In the past, all of this data was stored in silos and was difficult to access and analyze. However, with the advent of big data yield analytics, all of this data can now be collected in one place and analyzed to help identify trends and optimize process conditions.

  6. Big Data Analytics • Big data analytics is playing an increasingly important role in semiconductor yield management. By helping manufacturers collect, track and analyze all of their data in one place, it is possible to identify issues early on and make necessary changes to improve yields. In addition, big data analytics can help uncover hidden relationships between different process variables that can be exploited to further improve yields.

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