Steve Kinney

Machine vision is vital for industrial automation, providing essential image analysis amid labor shortages. Effective implementation relies on precise lighting to ensure high-quality images, with different applications requiring specific setups, such as backlights for measurements and line scan lights for fast-moving materials.

Due to advancements in sensor technology, shortwave infrared (SWIR) imaging is gaining traction in industrial applications. This growth is expected to drive a 28% annual increase in the machine vision market, enhancing food inspection, waste recycling, and agriculture.

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.

No matter the industry or application, all machine vision systems require light – whether visible or non-visible – to capture images. High quality output relies on high quality images, which require adequate lighting.

Lighting represents a crucial consideration when designing and specifying a system, as it is fundamental to image quality. Understanding how lighting impacts the rest of the system lays the foundation for system success.

Computational imaging technology has found its way into industrial automated inspection, where the creative use of illumination components has emerged as an enabling technology providing valuable imaging capabilities.

One constant in the ever-evolving machine vision space is the need for high-quality, consistent lighting. New challenges in the design and specification of machine vision systems require an innovative approach to lighting selection.

Quality assurance during high-volume production operations, such as the inspection of consumer packaged goods (CPGs), is possible only through the application of high-speed machine vision systems.

The world of machine vision imaging is largely performance driven. We’re looking for features on a part, finding edges, gaging, etc.