Episode description

The time is now for manufacturers to start moving toward a smart factory before being left behind by their competitors. But where do they begin? The challenge is that there’s no right answer. To come up with workable solutions, manufacturers must clearly understand the operational problems they face.

For example, a lot of manufacturers still conduct manual defect detection on the production line. This is not only expensive and time consuming, but often leads to inaccurate results. One way to address this issue is to apply machine vision and deep-learning models to smart cameras and automate the quality inspection process.

In this podcast, we explore changes happening on the factory floor, what makes a smart factory run, and how machine vision and AI improve the product inspection process.

Join us as we explore these ideas with:
David Dewhirst, VP of Marketing, Mariner
Christina Cardoza, Associate Editorial Director, insight.tech

David answers our questions about:

• What is a smart factory?
• How manufacturers have adapted to digital transformation
• Getting started on the smart-factory journey
• Computer vision vs. machine vision
• Importance of AI for product defect detection
• What to do when there is lack of IT support
• Data processing in the cloud and at the edge
• Working in a partner ecosystem

Related Content

To learn more about defect detection, read A Guaranteed Model for Machine Learning. For the latest innovations from Mariner, follow it on Twitter at @MarinerLLC and LinkedIn at Mariner.