Today, manufacturers are experiencing five-plus years of innovation on the plant floor in the space of 12 to 18 months. Changes that traditionally would have taken 5 to 10 years of innovation are now being rushed through on these kinds of sub-year timescales. That's quite phenomenal.

To discover the root cause of defects—and eliminate them—you need to ask targeted questions as you analyze your SPC data.

There have been two sea changes since the widespread introduction of QMS solutions in manufacturing environment—and a third change is on its way.

In modern manufacturing, “good enough” is no longer enough. To compete and be resilient to market disruptions, organizations must leverage data analytics to gain a competitive advantage.

The recent Covid-19 pandemic reminded me of an opportunity working with a federal government agency where I was asked to train high level scientific professionals on the concepts of Cost of Quality.

Thinking big in terms of quality is the goal. Rather than the days of old where quality just meant inspection, not in real time and not easily accessible, today the concept of quality has moved beyond this concept.

Does it seem like continuous improvement initiatives keep moving to the bottom of your task list? Here’s one way to get the big picture back on your radar.

Quality is based on a series of facts and statistics collected and analyzed. To produce a quality product—and continue producing a quality product—you need data.

At the end of the day, nothing matters more than customer satisfaction. Fundamentally, this sounds quite simple; make the customer happy, and all is well. Keeping customers happy and loyal to your brand, however, is not as easy as it sounds. 

Data collection on the factory floor can be a challenge. Even the smallest enterprise can generate massive amounts of data, and collecting this data is only a first step on the path to a successful IIoT project.