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At Cary Rosenberg’s company, Watts Water Technologies, validating material properties to ensure they are composed of the correct elemental composition is an important part of their work.

Within manufacturing, a shift has begun to extend big data analytics and condition monitoring beyond the factory door to both ends of the supply chain—to customers, other end users and to second-and third-tier suppliers.

Additive manufacturing (AM) refers to processes used to make a three-dimension object layer-by-layer. The shape of each layer can be dynamically controlled by computer-aided design (CAD).

Connected manufacturing and digitization technologies are spurring many of the major innovations in CNC machine controls that help machine shops cut metal and create parts as quickly and efficiently as possible.

Sensors are making their way deeper into process manufacturing where they monitor PH levels in vinegar, ensure towering bins of sugar aren’t overfilled and measure humidity in bakeries. Sensors are even helping power better mousetraps.

With great power comes great responsibility, the saying goes. And with greater laser power being used to weld sheet metal, tubes, copper and aluminum, operators have a greater responsibility to deliver that power with a precision that avoids defects.

When drilling a well, clearing a forest or excavating a building site, experienced operators count on their toughest equipment to help them get the job done.

Machine vision is proving ideal in helping humans perform tedious but crucial manufacturing tasks. That is why it is poised to grow significantly in the next few years.

Road to maturity involves safeguarding supply chains, treating security with the same urgency as safety, for starters.

Aging assets have long been the culprits behind common supply chain disruptions like unexpected downtime and production delays. They can have a direct impact on revenues and service levels, and the older they get, the more costly the risks they pose are.