Optimizing Semiconductor Manufacturing Yield


Value-Driven Benefits

$39 million

Estimated annual economic impact

1,500

Relevant machine learning features

20

Machine learning algorithms to predict die quality

12

Machine learning algorithms to predict bottom 10% and 20% low-yield wafers

Challenge

A large manufacturer of high-performance semiconductors implemented C3 AI Process Optimization to optimize the manufacturing process of its wireless products, demonstrating the ability to predict low-yield wafers early in the process and identify process improvements to increase overall yield.

The U.S.-based manufacturer designs and delivers a broad set of cutting-edge products, including radio frequency filters, amplifiers, modulators, attenuators, and more. However, the manufacturer had been experiencing lower than expected overall yield in some of its most complex products.

Approach

By implementing C3 AI Process Optimization, the manufacturer can now identify bad wafers, quantify time and costs saved, and tune design and manufacturing processes to optimize yields. The total estimated economic impact is greater than $30 million per year from both manufacturing optimization and design.

Solution Architecture

C3 AI Platform

Enterprise AI for Manufacturing

The C3 AI Platform provides the necessary comprehensive capabilities to build enterprise-scale AI applications 25x faster than alternative approaches. The C3 AI Platform enables manufacturers to rapidly integrate petabyte-scale data from any/all enterprise systems, operational sources, sensor networks, and external providers to power machine learning models that generate predictive insights to solve previously unsolvable problems.

Many global manufacturers are already using the C3 AI Platform to drive digital transformation efforts, generating results such as: reducing inventory by as much as 35%, lowering waste due to quality defects by over 20%, and generating hundreds of millions of dollars in economic value annually.

C3 AI Platform

Proven results in weeks, not years

timeline

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