Jidoka Technologies, among the pioneers in the field of automated cognitive inspection for manufacturing, is happy to announce the launch of its innovative self-training software designed to revolutionise AI-based object detection techniques. In the era of rapidly evolving technologies, visual quality in manufacturing is not always binary – OK or NOK, and is highly subjective. It relies on people’s experience and expertise for decisions that need to be taken within seconds despite the presence of rules and SOP.

The criteria for accepting or rejecting defects in components can fluctuate due to factors like environmental conditions, the influence of external elements such as oil and dust on the part, and changes in standards based on the part’s functionality and its intended user. Although these variations are in the acceptable range, automated machine systems that rely on rule-based approaches would be rejecting the parts leading to a high percentage of false positives.

For over three years, Jidoka Technologies has been deploying its AI-driven software to address complex visual inspection tasks, with a track record of over 40 success stories spanning across automotive, consumer goods, print, and packaging industries. Customers have been asking for self-training for two use-cases, where there is a change in environment or variations for existing lines or where there is a high mix-low volume eg: the PCB industry where the requirements are dynamically changing. By building on this rich experience, the organisation is now introducing its self-training software, empowering customers with the ability to independently train and deploy AI models on the go.

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