The quest to optimize equipment efficiency, ensure consistent quality, and lower operational costs while empowering a stronger workforce continues to permeate the industrial landscape.

When do we need to fit a lognormal distribution to our skewed histograms? This article considers the basic properties of the lognormal family of distributions and reveals some interesting and time-saving characteristics that are useful when analyzing data.

My favorite time of year is rolling around (and no, it’s not the holidays with their nauseatingly excessive tinsel-before-turkey consumerism). I’m talking about the time for end-of-year progress reviews.

Nothing is more annoying than someone bragging about their success. Right? Not necessarily, it turns out. When bosses brag, it can inspire employees to put more effort into their own work.

It’s hard asking for help. Getting rejected stings. But by not asking, you’re probably missing out on some great opportunities.

There’s an old saying in regulated industries: If it isn’t documented, it didn’t happen.

For professor Elsa Olivetti, tackling a problem as large and complex as climate change requires not only lab research but also understanding the systems of production that power the global economy.

Anyone who has ever seen a crew team rowing down the river has likely wondered why one person is a passenger and everyone else in the boat is rowing like mad. It would seem the coxswain has the easiest job in the boat.

Calibration is essential in almost every facet of industrial processes. The calibration process verifies test instrument accuracy by comparison with recognized standards, and measurement validity hinges on one crucial concept: traceability.

Why are some pro sports teams perennial contenders while others can’t seem to get out of the cellar? Great players are essential, but that’s not enough. Often, the unheralded MVPs of a successful team are people who wear suits, not uniforms, to work.