As the pandemic continues to play a role in the changing landscape of machine vision technologies, the machine vision industry had the greatest ever start to a year.

In 2021, the machine vision industry saw record growth, due in part to quality improvement and decreasing costs in manufacturing. According to a recent Association for Advancing Automation (A3) report, the North American machine vision market saw the greatest ever start to a year, with a growth of $1.5 billion from January to June 2021.

Machine vision technologies saw significant growth due in part to the COVID-19 pandemic. The pandemic pushed digital development to support remote work, which triggered a greater need for manufacturers to incorporate automation and machine vision to improve the efficiency of production, including logistics-related applications. Automated technologies allow companies to increase production as demand grows.

Companies Save Money Through Automation

Growth in automation and machine vision applications also assists companies with products that are more intricate and that require automated inspections. By incorporating automation and machine vision, companies save money and improve efficiency while also expanding worker resources. In addition, as nonvisible industrial machine vision applications move from research experiments into real-world products, companies are incorporating new types of inspection. The growth in real-world applications has also pushed the development of high-speed, high-resolution cameras, deep learning, and other advanced software.

Deep Learning Boosts Machine Vision Implementation

Image sensors with higher resolution and faster frame rates continue to develop and improve camera design, allowing for more capable imaging systems. Optics for nonvisible wavelengths, ranging from the UV through the IR, improve the ability to identify items with specific imaging. LED illumination products also offer a variety of wavelengths and form factors. All these improvements offer options for more complex applications.

Deep learning works alongside these imaging improvements to allow humanlike judgment to be applied in a semiautomated system. As these systems improve, so do industrial applications. These developments are pushing the expansion of machine vision implementation and applications.

In a recent A3 article, TECH B2B account executive John Lewis discusses these topics further and what can be expected going forward. Stay tuned to our blog as we continue to track trends in machine vision and automation.