For the past few decades, consumers have rewarded companies that customize their products and services to individual tastes and needs.

Due to rising labor costs and a shortage of skilled inspectors, today’s manufacturers are facing intense pressure to automate processes that rely on the senses of experienced human workers.

Today’s manufacturers are under pressure to be more flexible, reduce downtime and costs and increase efficiencies.

An object hanging from a string, moving back and forth, is more than something used to entertain cats or hypnotize patients in old horror movies. It’s called a pendulum. 

A study by McKinsey & Company found that AI-driven quality testing can increase productivity by up to 50% and defect detection rates by up to 90% compared to human inspection.

Today’s manufacturers are under pressure to be more flexible, reduce downtime and costs and increase efficiencies.

Artificial intelligence (AI) is one of the most hyped technologies of recent years, and while it promises new cost and process benefits for inspection applications, deployment remains a challenge.

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.

Autonomous Mobile Robots (AMRs) are the latest innovation that have been transforming traditional robot tasks through increased flexibility and diversified applications, including their unique ability to navigate in an uncontrolled environment with a higher level of understanding. 

Machine vision is a key technology for highly automated and seamlessly networked processes in the context of Industry 4.0, a.k.a. the Industrial Internet of Things. The use of new artificial intelligence processes such as deep learning is gaining in importance. A great many benefits make the technology attractive, but it also has limitations.