Outlier detection is a technique used to identify unusual observations, and data points that don't fall within the distribution. It's often used in SPAT semiconductor testing, where it can help identify manufacturing defects or variations and classify them as rejects although passing a set of specified criteria. It identifies test results that are outside of the normal range. Outlier detection helps semiconductor manufacturers only ship high-quality semiconductor devices.

1. A Brief Overview and
Importance of Outlier Detection
Method in Semiconductor
Manufacturing
OUTLIER DETECTION METHOD IN SEMICONDUCTOR MANUFACTURING

2. Outlier Detection

3. Outlier Detection
 Outlier detection is a technique used to identify unusual
observations, data points that don't fall within the
distribution. It's often used in SPAT semiconductor testing,
where it can help identify manufacturing defects or
variations and classify them as rejects although passing a set
of specified criteria. It identifies test results that are outside
of the normal range. Outlier detection helps semiconductor
manufacturers to only ship high-quality semiconductor
devices.

4. Outlier Detection Test
 Outliers can indicate a problem on a particular device
under test. For example, if most of the devices under
test are behaving within normal parameters except
for some that have significantly higher or lower
results, there is a high probability that these devices
are latent defects. Outlier detection test can help
identify these potential problems so that they can be
screened out and not used in the intended
application.

5. Importance of Outlier Detection
Method in Semiconductor Industry
 Semiconductor ICs or microchips are used in almost every
major industry like automotive, consumer electronics,
smartphones, gaming consoles, high-tech military equipment
and more. This is the reason that ensuring the quality of each
and every chip is crucially important for semiconductor data
manufacturers. These chips perform some key functions in
important fields. For example, various sensors that work with
the help of microchips initiate the air bag protection function
in cars during a car crash. If the airbag doesn’t open on time
because of a faulty sensor, lives can be lost.

6. Cont’d
 Let’s take another example of smartphones. Smartphone
manufacturers have to face a lot of competition from other
manufacturers that manufacturing yield. They cannot
compromise on quality. Suppose they launch a high-end
mobile phone in the market but some of the phones are
shipped with faulty processors. This will cause consumer
returns, negative reputation and market share loss. No one
wants a faulty chip because of the risks associated with it.

7. Cont’d
This is why outlier detection method should be
used in semiconductor testing. It removes the
dice that pass standard tests but deviate grossly
from the normal distribution. Various statistical
algorithms are applied to find these outliers so
they are never shipped to the customer.