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Semiconductor Wafer Inspection Transformed

Many laboratories rely on time consuming, labor intensive activities that must be performed by experts, often generating only basic/necessary data, or providing a yes/no answer. 

In this video, Mike Connell, VP Organizational Transformation, discusses how a time consuming quality inspection chore is transformed to reduce the time, while generating new data. The result is an innovative workflow that improves the manufacturing process.

Mike Connell | 1m42s | Semiconductor Wafer Inspection Automation Case Study

Possibilities Across the Industry

Ever more complex chips at advanced nodes is highlighting the power of applying machine learning techniques across the industry; from research and design, to manufacturing and trouble shooting client issues in the field.

Advanced algorithms can recognize and learn patterns in data, make predictions and identify problems; for example, finding and classifying defects. Laboratories are being redesigned to focus on generating the massive data sets necessary for applying machine learning techniques.

Enthought scientists have business-relevant domain expertise, enabling greater understanding of client challenges. Combining this with coding skills enables rapid prototyping to get started immediately in creating the new possibilities enabled by digital technologies.

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Create New Possibilities

Talk to us about transforming your lab performance, removing drudgery from the work of scientists, and using the power of today's AI/Machine Learning techniques.

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