Save 45% off ODSC East, it's just a few months away!

days

:

:

for an extra 20% off, use the code: ODSC20
Go

Detecting Defects with Data Science

Tags:

A frequent application of data science in the industry, and more precisely in semiconductor manufacturing, is to detect failed components.

In this article, Anirudh Kondaveeti, a principal data scientist at pivotal, uses classic data science techniques to detect failed wafers on a production assembly line. A process that includes feature extraction, dimensionality reduction through Non-negative Matrix Factorization, outlier detection, and clustering. The final visualization helps uncover common defect patterns occurring in the manufacturing process.

New to Open Data? Register for Free

    Latest Posts

    2 Visualizations

    02/21/2017

    Related posts

    Metrics and Hiring

    08/18/2015

    R-blogs