Business Reporter: Fossil fuel power still dominates our highways: new methods are needed to reduce its impacts
Today, some manufacturers are still checking quality manually and more often than not, these checks are only superficial: to analyse the inside of catalysts, destructive tests are needed. This type of quality control is slow, not 100% accurate, and with precious metal components involved, also particularly costly, says Mr Grilc.
A better approach is to use technology that enables automated, continuous, and precise inspection of every single component during manufacturing. Technology from INEA is helping car-part manufacturers take the inspection of exhaust systems to a new level of accuracy – areas smaller than 1/10th of a square millimetre in distinctive threshold regions can be inspected during production. In those tiny surfaces, plugged channels or possible optical leaks are checked while running the handling conveyors with speeds that can reach cycle times of 2 seconds per part. With such high added value products and this kind of environmental impact “every faulty part and every recalled component is one to many,” says Marko Grilc, Product Manager, inSpect Vision Systems at INEA.
Today, every third car on the road has a catalytic converter or diesel particulate filter that has been inspected by INEA’s industrial vision solutions. But despite this success, the company is constantly developing new in-line quality inspection technologies, such as 3D and X-ray scanning as well as new forms of image processing. Advanced deep learning algorithms can take these type solutions even further in terms of early warning systems and predictive maintenance.
To learn more about how industrial vision can transform quality control, watch the video and read the article.
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•• About INEA ••
INEA’s highly specialized vision inspection technology, with in-house designed machines and algorithms, tackles the most complex challenges in automotive supply chain and other industries. Using line scanners, 3D scanners and X-ray cameras, augmented by robot vision and deep learning, INEA’s technology is used across manufacturing processes, including in sorting, surface quality inspection, part assembly inspection and marking quality control.
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