Industrial machine vision utilising AI to stem the recall tide
28 June 2019
Vision inspection experts, IVS have witnessed an increasing number of industrial manufacturing customers investing in machine vision systems to reduce product recalls.
Next-generation artificial intelligence (AI) machine vision systems should be used at critical stages of manufacturing to reduce the risk of workplace contamination, helping cut the number of product recalls throughout a host of industries. That is the view of Industrial Vision Systems (IVS), a supplier of vision inspection solutions to sectors such as medical devices, pharmaceuticals, food & drink, automotive, and printing & packaging.
IVS has witnessed an increasing number of customers investing in machine vision systems to reduce recall figures and safeguard their revenue, reputation and brand worth.
In June 2019 alone, well-recognised UK brands such as Tesco, Aldi, Dunelm and Asda have recalled items including sushi salmon, cotton towels, tomato seasoning, and liver & bacon mash. Previously, Samsung was forced to launch a global recall for its flagship phone, the Galaxy Note Seven, after batteries kept exploding, while faulty airbags from car component manufacturer Takata led to the largest recall in automobile history. Moreover, in 2015, General Motors had to recall millions of cars because of faulty ignition switches that led to fatalities, lawsuits and a $900m criminal penalty.
“The impact of issuing a recall can be devastating in terms of cost, reputation and, eventually, market share. Over the past year, unparalleled levels of developments have occurred in artificial intelligence, big data, 3D imaging and robotic process automation – none more so than on the factory floor – and this is crucial in reducing the risk of error and subsequent product recalls,” comments Earl Yardley, Director at Industrial Vision Systems.
Yardley believes that advances in thermal imaging, 3D imaging and hyperspectral imaging are among developments which will play a vital role in assisting manufacturers in reducing the number of product recalls.
Yardley concludes: “Machine vision is used for final quality control inspection, but new markets are opening up with the advent of 3D sensors and deep learning utilising AI. Deep learning within machine vision can detect defective parts traditional vision inspection systems cannot see. Typical applications in hyperspectral imaging include plastic detection in meat production, detection of different recyclable materials and blister pack quality control. While development in automated thermal imaging inspection allows manufacturers to spot problems which can’t be seen by eye or standard camera systems, and provides non-contact precision temperature measurement and non-destructive testing.”
About Industrial Vision Systems (IVS)
Launched in 2000, IVS vision systems are used all over the world in automated production processes for inspection, guidance, identification, measurement, tracking and counting. Its systems are reputed to be some of the most innovative and advanced machine vision solutions on the market today, successfully deployed in thousands of systems around the world.
Based on the prestigious Harwell Science Campus, Industrial Vision Systems represents clients in sectors such as food & drink; electronics; automotive; pharmaceuticals; medical devices; and packaging.
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