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.

1. Overview of Statistical Bin
Analysis and Its Uses in
Semiconductor Testing
STATISTICAL BIN ANALYSIS

2. 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.

3. Cont’d
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.

4. Cont’d
 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.

5. 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.

6. Cont’d
 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.

7. Cont’d
 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.

8. STDF Data Analysis
 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