The famous quote "Adapt or die" applies to businesses like Kodak and Blockbuster, which missed out on opportunities by not embracing new technologies. This concept also applies to industries like manufacturing and logistics today.
Quality managing editor Michelle Bangert talked with Justin Newell, CEO of Inform North America, who recently wrote an article for Quality on trustworthy AI.
GigE Vision has been widely adopted in various machine vision applications, including manufacturing, robotics, traffic surveillance, medical imaging, and more.
GigE Vision® sets the standard for high-performance industrial cameras, leveraging Gigabit Ethernet for fast, cost-effective image transfer. Introduced in 2006, it enables the transmission of digital images and video over Ethernet networks up to 100 meters. With version 3.0 on the horizon, GigE Vision remains the top choice for long-distance camera setups, offering unmatched performance and affordability.
AI is revolutionizing quality control in manufacturing, driving us into Industry 4.0 and beyond. Manufacturers can streamline processes, boost efficiency, and deliver top-notch products globally. Embracing AI isn't just advantageous; it's essential for thriving in today's economy. Businesses must invest in AI to empower their workforce and stay ahead in the rapidly evolving manufacturing landscape.
Discovering, evolving, and sometimes unsettling, artificial intelligence mirrors our human learning. Yet, as it integrates further, questions arise: Can it handle quality assurance? What's in the future? And crucially, how much control are we comfortable relinquishing to it?
In this article we survey key considerations when making a lens selection. Of course, your lensing professional will be happy to advise – but they’ll ask you some of these questions anyway, so it’s helpful to make notes relative to your planned application.
If we can bridge the confidence gap between underperforming legacy vision systems and manufacturers’ needs today, the rate of adoption is sure to grow exponentially.
Labor shortages continue to pressure manufacturers, with some dedicating up to 20% of their workforce to manual inspection. Embracing Quality 4.0 with automated in-line inspections and AI process analytics could provide significant value.
Reverse engineering is the process of taking apart a product to understand its design and functionality. This knowledge is helpful for creating similar products or improving existing designs.
In the rapidly changing and expanding landscape of imaging hardware components and software solutions, the job of systems integration is as important as ever.
System integration strategies vary by industry and project scale. Success relies on thorough planning and execution, especially in machine vision technology. Here are key integration elements for success with vision technologies.
Automating testing and inspection requires careful consideration of tools, including robot type, end-of-arm tooling, and ancillary systems. While cobots are popular for quality tasks, their full collaborative capabilities may not be utilized in some applications, leading to higher costs without maximizing benefits.