In an industry where product quality increasingly determines competitive advantage, the ability to see what you're processing isn't a luxury — it's a fundamental requirement for profitable operation.
COMPASS identifies and removes stones, sticks, plastic, metal and extraneous vegetable matter, as well as discolored or damaged product and large ice or frozen agglomerates in IQF applications.
Designed to overcome barriers to deploying cooled thermal cameras in production environments, the A6450 combines long-life cooling, high-speed MWIR performance and automation-ready integration.
Designed to inspect fresh-cut product straight from the field, this belt-fed system combines high-performance foreign material detection and removal with gentle, hygienic product handling.
By transitioning from legacy single-technology systems to multi-layered inspection processes, manufacturers can minimize recalls, reduce waste and safeguard their brand.
Today’s vision systems are more powerful than their earlier counterparts, and many processors choose to use vision, X-ray and metal detection systems to meet regulatory demands and ensure quality.
Upgrading older vision systems often means an upgrade in control systems as well to get the most out of inspection systems, which now employ AI to make snap quality judgments that humans can’t do time after time.
Califia’s V31 vision inspection system is equipped with three cameras for identification and removal of high caps, damaged caps, broken shrink bands and other closure issues.
The system includes cameras, AI software, a conveyor and automatic ejection mechanisms with dual drops (one for foreign material, one for culls) to ensure only ideal potatoes reach later process stages.
AI looks to be a panacea for making better inspection choices, but knowing specifically what the inspection criteria should be needs to be in place before employing an AI-based system.
AI looks to be a panacea for making better inspection choices, but knowing specifically what the inspection criteria should be needs to be in place before employing an AI-based system.