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    Using data to optimize industrial operations

    How data can help industry work smarter, faster, and more efficiently


    Connected systems, with their ability to collect and crunch massive quantities of data, are transforming industry and business.

     

    For one thing, they’re changing the role of flesh-and-blood human beings in industrial settings. For most of the long history of how we make things, humans have been forced to attend to minutiae—for example, to the question of what machine parts required replacement, and exactly when.

     

    That’s coming to an end. Today’s tech is liberating humans to do the cerebral work machines will never be capable of. Machines, for their part, are taking over from people, and excelling at, the rote but crucial tasks—monitoring wear and tear on ball bearings and the like.          

     

    Here are four ways that data is helping industry work smarter, faster, and with greater efficiency: 

    Condition-based monitoring


    Data-driven industrial methods keep developing. Condition-based monitoring (CBD) is a new maintenance trend that uses real-time data to improve on traditional predictive maintenance practices.

     

    Predictive maintenance uses sensor-supplied data to discern with precision how a machine will function (or not function) in the future. In CBD, by contrast, real-time data enables the performance of repair and replacement work at the right moment. As soon as sensors detect that a generator is running hot, for example, the system prompts intervention.

     

    Predictive maintenance forecasts the future, while CBD keeps an eye on what’s happening in the present. And as we all know, predictions are less reliable than observations.

    Making big systems comprehensible


    A digital twin is what it sounds like: A computer-based model of a real-world object or system, in particular one of a size or complexity that defies the human ability to comprehend it as it is. Think of a nuclear reactor, a container ship, or even an entire city.
     

    A digital twin puts that object or system in front of human managers, in forms that they can work with and study, from numerical datasets to 3D imagery. Those managers can, among other things, tinker with inputs, extrapolating from current conditions to test what might happen to the object or system given increased workloads or extreme temperatures.
     

    Data, of course, is what makes the twin tick: The connected sensors that monitor the original item feed real-time information simultaneously to the twin.
     

    One major strength of a digital twin is its ability to deliver information contextually—that is, according to users’ roles, use cases, and desired outcomes. As PTC business analyst David Immerman explains in a September 2019 article, a digital twin can deliver insights that go well beyond the repair and maintenance of industrial machines or systems. A service executive could use predictive maintenance to identify a product defect and take action to remediate it. An operations manager can use performance metrics to improve production processes. And an engineer can take the lessons learned from both to create better iterations of a product’s design.

    Making the factory floor more efficient—and safer


    Manufacturing and other industrial facilities are also getting safer thanks to data.

     

    Sensor tech can trace how humans and machines (like forklifts) interact on crowded shop floors, generating data that can inform planning. In light of how employees move from their workstations to exits and rest rooms, what’s the best way to structure the floor? Which spaces in a facility remain underutilized, and which can be put to better use?

     

    In the always-on environment of today’s automated manufacturing or logistics facility, answering such questions won’t just boost efficiency: it could also cut down on injuries and save lives.

    Integrating data to make supply chains work


    Never has the logistics expert’s craft been as important as it is today. Globalized “just-in-time” supply chains leave no margin for error. A container ship can’t sit in port an hour longer than it needs to. A fleet of trucks can’t idle at the docks, waiting for the ship to offload.

     

    The IoT enables visibility along an entire supply chain—a visibility that can prevent breakdowns. If technical problems at a manufacturing facility in China are slowing production of a key export component, the maritime operator tasked with transporting it to the US will know that in real time. That operator can then scale back the space assigned to that facility’s products, or assign it elsewhere. The US distribution facility can adjust its capacity as well.

     

    Sensor-enabled freight lots can indicate precisely what time they’ll arrive at a train depot, so that trucks can materialize exactly when they’re needed—no sooner, no later.

     

    Connected IoT tech, collecting and analyzing data, will be the orchestrating mechanism for the supremely complex and productive industrial system of tomorrow. It will make industrial operations safer, faster, more supple, and more efficient, changing dramatically how we make and distribute to each other the things we need.

    About the author

    Headshot of Ton van de Wiel
    Ton van de Wiel is the global segment lead for industrial end-users within Signify and co-founder of Interact. With over twenty years of business experience, he now works to shape tomorrow’s world of smart manufacturing and warehousing as enabled via connected lighting.

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