In today’s rapidly evolving technological landscape, generative artificial intelligence (gen AI) has emerged as a transformative force, reshaping industries and redefining operational paradigms.

Recent developments in thermal signature analytics have expanded the applications of thermal cameras beyond routine troubleshooting; they now contribute to paper machine control, energy usage benchmarking, wet streak detection, and the identification and prediction o

In manufacturing, the term connected worker has quickly gone from emerging concept to executive mandate. As companies grapple with turnover, skill gaps, and increasing complexity, the urgency to modernize frontline work has never been clearer.

Your market is shifting, your competitor just pulled ahead, and the one person who could execute the next move has resigned. You can’t get more data fast enough, yet the window to act is closing.

Organizations are eager to benefit from generative artificial intelligence.

In this article I’m looking at the notion of organizational purposes in light of cybernetic constructivism. The ideas here are inspired by giants like Stafford Beer, Spencer Brown, Ralph Stacey, Werner Ulrich, Russell Ackoff, and Erik Hollnagel.

Plan a route, grab some snacks, and fuel up. Engineers and scientists have been sending massive magnets from U.S. Department of Energy (DOE) national labs on cross-country road trips.

There’s a lot of talk about automation these days, not just in manufacturing circles but also the news in general.

Today, manufacturing is largely shaped by supply chain volatility, complex labor dynamics, and—like most global industries—the rise of AI.

Simulations still can’t predict precisely when an earthquake will happen. Still, with the incredible processing power of modern exascale supercomputers, they can now predict how they will happen and how much damage they will likely cause.