JMP White Paper: Advantages of Bootstrap Forest for Yield Analysis

This white paper highlights practical examples on how to use partitioning techniques for semiconductor manufacturing data. These methods also have wider applicability.



Advantages of Bootstrap Forest for Yield Analysis

This white paper highlights a number of practical examples to demonstrate the use of partitioning techniques for semiconductor manufacturing data.



The semiconductor industry is becoming increasingly competitive and forcing manufacturers to achieve significant reductions in time to market. As a result, every step in the manufacturing process needs to be completed in less time while maintaining a high level of control and quality. This must be accomplished based on an increasing number of requirements to satisfy customer demands, particularly for products aimed at the automotive industry and the medical sector.

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Through two case studies, you will learn how to:
  • Partition for root-cause identification in the case of a loss of electrical yield that is not detected during the manufacturing process.
  • Examine a variation in electrical yield detected during manufacturing.

 


Engineers must have access to high-performance tools and methods that make it possible to get to the root of the problem as quickly and reliably as possible. This white paper focuses on the bootstrap forest method available in JMP® Pro for root-cause analysis.

Download the white paper.