Manufacturers in the automotive industry are striving to make the most of the current trend towards electric vehicles and low fuel consumption by building lighter-weight vehicles and favoring aluminum over iron.

The automotive industry depends on consistency and predictability. From the color of the paint to the stiffness of the brake, car manufacturers devote significant amounts of time and money into making sure their products look immaculate and feel safe to drive.

As developments in machine learning and the Internet of Things (IoT) impact how manufacturers run their businesses, automation can support these changes and boost productivity.

Robots in manufacturing is not a new idea. But today an increasing number of collaborative robots are joining the ranks, working alongside their human coworkers.

Artificial intelligence is here, and it is can improve quality in a number of ways. It can prevent bad parts from being made, discover trends, and monitor machine performance.

Electroless nickel (EN) is industry’s most common plated finish. It’s widely used for applications that demand wear resistance, hardness and corrosion protection—particularly if parts have complex geometries. It is also used in PCB manufacturing within a process known as ENIG, electroless nickel immersion gold. 

In these strange times, every industry around the globe has been affected by the coronavirus. And manufacturing is no different.

Machine vision quality assurance systems have excelled at automating the location, identification, and inspection of manufactured components through computational image analysis.