Gopakumar Pioneers (CONT’D FROM PAGE 22)
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This new feature harnesses current sensor information along with historical downtime data to provide not only an up-to-date picture of the state of your equipment, but ac- tionable information about future functioning – so opera- tors can make proactive decisions about their machines. The algorithms no longer simply provide diagnostic infor- mation about past machine performance: they’re now pro- viding a picture of ongoing and future performance. An initial case study found that 74 percent of machine break- downs were accurately forecasted within a 30-minute win- dow using this new technology. This gives operators the chance to make decisions in advance before a possible interruption occurs. The ability to provide these kinds of advanced predic- tions was previously only theoretical. But now these ma- chine learning models are fully operational and live on the platform for select Helios customers. Early adopters of this powerful new technology are already reducing main- tenance costs by 30 percent and eliminating equipment breakdowns by 70 percent. When you consider that the average box plant can expect to save $122,000 per year per machine with just a 20 percent reduction in downtime, the savings potential is truly vast. Don’t miss Gopakumar’s “What’s New Session” presen- tation at Corrugated Week 2022, where he’ll be offering a glimpse at Helios’ new failure prediction capabilities.
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WORLD–CLASS NETWORKING & CONNECTIONS CUTTING–EDGE TECHNOLOGY & TRAINING
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September 12, 2022
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