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Overview of Statistical Bin Analysis and Its Uses in Semiconductor Testing

Bin analysis is a statistical technique that is used to understand how data is distributed. It can be used to find patterns in data, outliers, and trends. Statistical Bin Analysis can be used with both numerical and categorical data.

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Overview of Statistical Bin Analysis and Its Uses in Semiconductor Testing

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  1. Overview of Statistical Bin Analysis and Its Uses in Semiconductor Testing Introduction to Statistical Bin Analysis Introduction to Statistical Bin Analysis A bin is a grouping of similar items. In statistics, a bin is created when data is organized into groups. For example, if you have data that is grouped by age, you would create bins for each age group. Binning is a way to make data more manageable and easier to analyze. Bin analysis is a statistical technique that is used to understand how data is distributed. It can be used to find patterns in data, outliers, and trends. Statistical Bin Analysis can be used with both numerical and categorical data. There are two types of binning: equal width binning and equal frequency binning. Equal width binning creates bins that are the same size. Equal frequency binning creates bins that contain the same number of items. What are the Applications of Statistical Bin Analysis? What are the Applications of Statistical Bin Analysis? Statistical Bin Analysis has a lot of scope in semiconductor testing. Consider setting limits for good bins associated with various other performance bins. A product engineer can set bin limits for each of the fmax good bins. If there is a shift in the distribution amongst these bins then the engineers can put all the material on hold until they find the root cause of the problem. We can take another scenario of failing bin limits. A product engineer has determined an acceptable IDDQ fail bin 0.2%. If this fail bin exceeds more than 0.2% for an individual wafer or a lot of wafers then the material will be treated as out of control. An efficient yield management system will send a notification to product, quality, and yield enhancement engineers. The material will also be automatically put on hold. STDF Data Analysis is the process of analyzing data logs and providing resulting test data in ATE data format. The resulting test can be loaded into core yieldWerx on the basis real-time automatically or can be imported manually into core yieldWerx

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