Quality in manufacturing is mission critical. AI-powered quality inspection is nothing new, but a joint venture from two big players in manufacturing could markedly improve outcomes and reduce barriers to entry.
The new venture is called Lean AI. The technological secret sauce is what's known as unsupervised AI, which is a cutting edge deep learning technology that doesn't require massive datasets, months of setup time, or known inspection paradigms to function. The new company is a collaboration between Johnson Electric, which has knowledge and experience in manufacturing, and Cortica Group, which has pioneered unique autonomous AI technology for visual inspection.
"With the power of Cortica's Autonomous AI technology, and JE's vast knowledge of the market, Lean AI will deliver a product that reduces the cost of human error when it comes to quality inspection in manufacturing and address the vulnerabilities in the current market," says Karina Odinaev, CEO of Lean AI.
The problem is that conventional Deep Learning-Based Quality Assurance Systems can take weeks or months, to deploy and rely on a data scientist or AI experts feeding large manually tagged training sets with thousands of defect image examples. These systems require constant maintenance and re-training for product variations or new cameras.
Lean AI is leveraging a newer generation of unsupervised deep learning-based quality assurance technology to get past existing challenges. Its unsupervised system uses unlabeled data, applies predictive quality assurance, and compiles data that increases the speed of deployment and scaling. It's an open platform, meaning it's agnostic to camera, defect type, and product. That flexibility marks a big evolution in AI-driven inspection, which is a massive and growing market, particularly with renewed emphasis on efficiency as supply chains are stretched thin.
By some estimates, the global machine vision market is currently valued at US$11 billion and is forecast to increase to US$15.5 billion by 2026.
"Cortica has developed self-learning AI that is fundamentally different from traditional deep learning systems. Autonomous AI Technology operates like a human brain — it's not a fixed system; instead, it continuously adapts itself to various scenarios and learns online in real-time. Its technology requires far less computing power, can be deployed at a fraction of the cost, and provides far superior performance outcomes," says Igal Raichelgauz, Founder and Chairman of Cortica. "Our technology is robust and generic and applicable within a multitude of signal domains such as visual, audio, time series and other domains; visual inspection is only the beginning. Autonomous AI technology is quickly becoming the benchmark for the industry."