Machine learning can help organizations improve manufacturing operations and increase efficiency, productivity, and safety by analyzing data from connected machines and sensors, machine.

Standard sensors and equipment won’t survive for very long in automated welding environments where high temperatures, flying sparks and weld spatter can quickly damage them. 

About 18 months ago, one of the major automotive companies came to the Indicon Conference looking for a way to decrease mistakes on the assembly line. They found a solution in a concept named the Error Proofing Platform Station (EPP).

Three options come to mind for determining which contactless sensor to use when measuring objects at a distance: photoelectric sensors, ultrasonic sensors, and radar detection. Understanding the key differences among these types of technologies and how they work can help you decide which technology will work best for your application.

Photoelectric sensors have been around for more than 50 years and are used in everyday things – from garage door openers to highly automated assembly lines that produce the food we eat and the cars we drive.

Standard sensors and equipment won’t survive for very long in automated welding environments where high temperatures, flying sparks and weld spatter can quickly damage them.

With more and more customers getting onboard with IIoT applications in their plants, a new era of efficiency is lurking around the corner. 

Both M18s and flatpacks are inductive or proximity sensors that are widely used in mechanical engineering and industrial automation applications.

What is the first thing that comes to mind if someone says “proximity sensor?” My guess is the inductive sensor, and justly so because it is the most used sensor in automation today.

A recent study by the Packaging Machinery Manufacturers Institute (PMMI) and Interact Analysis takes a close look at packaging industry interest and needs for Condition Monitoring and Predictive Maintenance.