Abstract:
Yield enhancement is one of the major objectives for semiconductor manufacturing. In addition to the usual functional yield that needs to achieve a much higher ratio of g...Show MoreMetadata
Abstract:
Yield enhancement is one of the major objectives for semiconductor manufacturing. In addition to the usual functional yield that needs to achieve a much higher ratio of good dies in a wafer, parametric yield requires other important factors that can improve the quality and capability of the wafer. Owing to the much more complexity for the processes of wafers in today's semiconductor technology, it is difficult to find the root causes that may affect the parameter yield. Based on the selected important factors that may affect the parametric yield, this study aims to provide an efficient analytic framework for modeling the factors with high correlations. A modified PLS approach (mPLS) is applied in this study for model building that can simultaneously handle collinear problems and provide reasonable explanations with physical meaning.
Date of Conference: 20-23 August 2017
Date Added to IEEE Xplore: 15 January 2018
ISBN Information:
Electronic ISSN: 2161-8089
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- IEEE Keywords
- Index Terms
- Semiconductor Industry ,
- Yield Enhancement ,
- Collinearity Problems ,
- Partial Least Squares Approach ,
- Low Yield ,
- Predictive Power ,
- Data Mining ,
- Manufacturing Process ,
- Explanatory Power ,
- Partial Least Squares ,
- Domain Experts ,
- Partial Least Squares Regression ,
- Vector Core ,
- Mean Absolute Percentage Error ,
- Electrical Parameters ,
- Partial Least ,
- Partial Least Squares Model ,
- Non-negativity Constraints ,
- Good Predictive Power ,
- Partial Least Squares Algorithm ,
- Effects Of Collinearity
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Semiconductor Industry ,
- Yield Enhancement ,
- Collinearity Problems ,
- Partial Least Squares Approach ,
- Low Yield ,
- Predictive Power ,
- Data Mining ,
- Manufacturing Process ,
- Explanatory Power ,
- Partial Least Squares ,
- Domain Experts ,
- Partial Least Squares Regression ,
- Vector Core ,
- Mean Absolute Percentage Error ,
- Electrical Parameters ,
- Partial Least ,
- Partial Least Squares Model ,
- Non-negativity Constraints ,
- Good Predictive Power ,
- Partial Least Squares Algorithm ,
- Effects Of Collinearity