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Private 5G networks
Revolutionizing the role of predictive maintenance in industrial machinery .
By Jan Diekmann
Downtime for equipment maintenance – whether planned or unplanned – will always be an unavoidable issue for manufacturers . When businesses are losing an average of 20 hours a week to unscheduled maintenance ( according to a recent Industry in Motion report from RS ), however , they need to rethink how to keep their heavy machinery and equipment in check . Traditional maintenance strategies , typically based on predetermined schedules or reactive repairs after failures , are often inadequate ; leading to operational inefficiencies , unexpected breakdowns and costly unplanned downtime . RS ’ report estimates the annual cost of breakdowns to be $ 6,776,113 to the average manufacturer – a staggering cost that many businesses simply can ’ t afford , when margins are being squeezed at every opportunity .
Given the intense demand to maximize asset lifespan and enable more sustainable use of machinery , manufacturers are pivoting towards predictive maintenance to supercharge their assembly lines . This technique uses data collected by Industrial Internet of Things ( IIoT ) sensors to monitor equipment conditions and pre-empt issues
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