How advances and limitations are defined by the data.
Second in a seven-part series: Machine learning is a mathematical construct that is the foundation for nearly all the advancements in AI. ML came first, but it remains relevant even today. It can be applied to semiconductor fab for such things as predictive maintenance of manufacturing equipment, rather than just maintenance on a schedule, which decreases downtime. But getting this right is harder than it sounds. Data needs to be relevant, clean, and organized in the right form. Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about what can go wrong in gathering and applying data, why so much compute horsepower is required, and where to harvest the data needed to keep it relevant. (This is the second part in a seven-part series on AI in manufacturing. Part one is here and part three is here.
Complete series:
 |
 |
 |
 |
 |
 |
 |  |
 |  |
 |
 |
Leave a Reply