In last month’s article, “ANOVA and the Process Behavior Chart,” we saw how both techniques use the same basic comparison to answer completely d

Understanding the inner workings of your industrial artificial intelligence (IAI) system is crucial if you want it to add measurable value to your manufacturing operations. Here, we’ll dig into one important aspect of every AI: the inputs, aka your data.

In global manufacturing, two key goals—intertwined yet distinct—heavily dominate the industry’s agenda: addressing the growing demand for environmentally sustainable practices, and optimizing operational efficiency.

Today I’m looking at the free energy principle (FEP) by the British neuroscientist Karl Friston. The FEP basically states that to resist the natural tendency to disorder, adaptive agents must minimize surprise.

In the ever-changing landscape of business management, the concept of quality has undergone significant transformations.

Wharton management professor Peter Cappelli is routinely asked to predict the future of work.

Paul was sitting in his office staring at production numbers from the past quarter. Despite having a great team, strong customer demand, and state-of-the-art equipment, the factory’s performance wasn’t meeting expectations.

I enjoy painting, and I’ll admit that I’m not the neatest painter out there—I get a lot on me. And I’m not the fastest painter either, but I feel like I do a pretty good job.

We live in a world where problems aren’t just growing—they’re evolving into ever-more complex challenges. During the 20th century, we pushed the boundaries of innovation, creating complicated systems that demanded structured problem-solving approaches.

Audits and inspections are critical components of industrial safety management. These processes help organizations ensure compliance with legal requirements, identify risks, and improve workplace safety and operational efficiencies.