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.


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.


Industry Events

In 2021 Enthought will be participating in the September SEG/AAPG combined event in Denver and in ADIPEC in November.