New growth in manufacturing with deep insights

Years of deep and broad industry engagement have been dedicated to establish the Semiconductor Manufacturing Analytics solution. In that time 6 focus areas have been identified as key features of the Semiconductor Manufacturing Analytics solution to deliver strategy and data models to gain insights and create new growth. Learn how these features may result in an up to 15% improvement in yield by deploying machine and deep learning techniques.

Enterprise analytics to accelerate new growth

Driving new growth through insights for designers, manufacturers and equipment makers.

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Increasing investments for semi manufacturing

There’s a bump in manufacturing investments and the industry is feeling the benefits. Syed Alam and Patrick Moorhead discuss the potential impacts.

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Features

Strategy by design

Leverage the power of your analytics to move beyond analytics as a localized discipline connected with single assets, processes and silos.

AI and ML

Transform complex semiconductor variables into a virtuous cycle of insight and decisiveness with AI and ML insights for cumulative value creation.

Data engineering

Translate valuable insights across the business by harnessing data engineering including abstraction layers and data meshing.

Proprietary tools

Utilize new tools to leverage fresh value across core manufacturing steps form design, wafer fab and sort to assembly, test and ship.

New value insights

Identify and discover the specific use cases that turn the manufacturing dial – for greater yield, faster throughput and ongoing quality advances.

Cyber security

Secure and protect your key IP with a leading global security partner that focuses across enterprise IT and OT to safeguard your data.

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Driving value through data

As semiconductor companies struggle to develop more complex chip customization and growing demand a world-leading chipmaker in the memory space was looking to secure a competitive advantage at every step of the manufacturing process. This advancement in the manufacturing process would evolve their next generation of innovative chip technology. With the goal of applying artificial intelligence and machine learning it would help deliver value and proof of concept for future product extensions.

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