“Garbage in, garbage out” serves as a simple reminder that successful machine vision systems must start with quality data. Current challenges require flexible machine vision systems and models that can keep up with the speed of technology.

A lot has changed since March 2020.  That’s when the last Quality State of the Profession survey was conducted. The survey was fielded March 9-10, 2020. The next day, WHO declared COVID-19 a pandemic, and it was declared a national emergency in the U.S. a few days after that.

There is no question that the COVID-19 pandemic dramatically impacted business practices across industry segments worldwide. Manufacturing was no exception and 2021 will be the year of reinvention through an emphasis on transforming business models.

CoaXPress (CXP) has developed into a new standard in industrial image processing in recent years. The CXP interface, which is particularly relevant whenever high data rates and short latency periods are called for, is now available in a new version with more improvements.

An increasing number of manufacturers are turning to deep learning, a subset of artificial intelligence (AI), to assist in image analysis processing, experts say.

In the year since the COVID-19 pandemic began upending our lives, one change among many was the huge uptick in the global consumption of paper and plastic products. Ecommerce saw rapid expansion in 2020 as restaurants shifted to a takeout model and consumers opted to shop online from the safety of their homes instead of visiting a crowded store.

Over the last couple of decades, stemming from changes in demand, competition, and market pressures, manufacturing has become a more complex and fraught affair requiring increased flexibility with a narrower margin of error. We can sum up this changing environment in three long-term trends affecting how stuff is designed and made: mass customization, increasing SKU proliferation, and shorter product cycles.