HOW SCALABLE ARE YOUR
VISION SYSTEMS? The first machine vision (MV) system as we might think of it today was launched in 1931. It was a colour sorting machine, using filters and photomultiplier detectors to optically sort products. In the nearly 100 years since this machine, MV has become a staple of industry, used in everything from quality assurance to robotic picking systems. As the need for MV grows, Stephen Hayes, managing director of Beckhoff Automation UK, explains how engineers can simplify vision processing to improve efficiency and scalability. Visual inspection is an increasingly important aspect of modern industrial processes. Whether it is used for assisting in sorting bulk materials in pharmaceutical processing, inspecting the quality of produce in food manufacturing or informing the positioning of a delta robot in packaging, MV significantly increases the efficiency and productivity of various industrial processes. It’s for this reason that the latest figures from MarketsandMarkets estimate the global machine vision market to be valued at $9.6 billion in 2020, with it expected to grow to $13bn by 2025. Even this figure is likely overshadowed by the value it adds to industrial businesses annually, by virtue of increasing throughput, minimising faulty products and reducing labour time for inspection tasks. However, there remains one consistent challenge with MV systems, which is the ease of configuration
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and processing. This, in turn, affects the scalability. Typically, MV systems are connected to a specialised, high performance industrial computer that is separate to a plant’s other automation systems. A setup like this means that specialist knowledge is needed to adjust system parameters and configure cameras, in an environment that is often unfamiliar to many automation engineers.
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