Semiconductor manufacturing

Micron is using AI models to analyze 3.3 million images each day, which contributes to a 50% reduction in new product ramp time, and 18% increase in labor productivity. Micron expects the greatest AI contributions in intelligent analytics, intelligent robots, and content generation.

How manufacturers can accelerate transformation and stay ahead of the competition in 2024 and beyond.

Digital Twin is a concept, not an application, and definitely not a shortcut to achieving smart manufacturing benefits. Unfortunately, it is necessary to understand that the path to I4.0 is a path of sophistication, but also of maturity.

AI has always been a topic filled with concern and curiosity when it is discussed in manufacturing. Manufacturing leadersneed to look at AI pragmatically, focusing on its potential in current operations instead of concern over an AI takeover.

By applying a graphical treatment and a uniform set of evaluation criteria, the Gartner Magic Quadrant helps you quickly ascertain how well technology providers are executing their stated visions and how well they are performing against Gartner’s market view.

Can your MES help the company achieve your CEO’s goals? Yes, you should expect it to do that. It is time to expect more from projects – including MES implementations.

Having a more automated semiconductor manufacturing operation begins with a modern MES at the core of a digital transformation.

When it comes to deploying an MES across multiple manufacturing facilities, platform architecture is critical. It will impact the ease of implementation and maintenance, and the ability to continuously improve the platform’s applications to ensure the latest technologies and methodologies can be embraced and that manufacturers have greater agility.

Leaders in an organization need to take the initiative when it comes to digital transformation and MES selection.