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Using Technology to Improve Efficiency

Traditionally, machinery maintenance requires regular manual servicing, routine checks, extensive repair work, and frequent replacement of worn and nonfunctional parts. This isn’t only time-consuming — it’s costly.

Predictive maintenance — evaluating the condition of equipment by performing periodic or continuous (online) equipment condition monitoring — is now possible for enterprises. Using Internet of Things (IoT) devices and sensors, alongside digital management platforms, system components can be monitored remotely, while predictive algorithms allow enterprises to prevent machine failures and reduce traditionally-high maintenance costs.

Huawei uses new technologies, including acoustic-, infrared-, and vibration-based sensors, to collect a machine’s data then monitor its working status. By constantly monitoring the machine during normal operations to accumulate big data, the application of statistical algorithms allows enterprises to predict and detect machine failures before they happen. And in many cases, when an equipment issue is found, it can be repaired in a way that minimizes impact on production.

Predictive maintenance is flexible: real-time data can be uploaded over operator networks (wireless service providers or mobile network carriers) to minimize latency; non-real-time data can be locally uploaded to mobile phones through Wi-Fi networks when network coverage is poor. Meanwhile, cloud-based IoT platforms can be deployed on a public cloud that supports flexible terminal access (desktops, smart phones and tablets), enabling machinery monitoring in real-time anywhere, anytime.

For vehicle maintenance, Huawei provides terminals that collect data at 250 kbit/s using Controller-Area Network BUS (CANBUS). The vehicle-specific terminals support wireless Long Term Evolution (LTE) data backhaul, and report vehicle locations using Global Positioning System (GPS). A rugged industrial design allows terminals to withstand high-vibration working environments — common at manufacturing sites.

Elsewhere, predictive maintenance is used by the railway, manufacturing, oil and gas, and battery supplier industries. These industries (and their respective customers) require safety, limited downtime, early fault detection, increased system (and fault) visibility, and intelligent analysis to ensure the delivery of high quality services. Huawei — in collaboration with partners — provides the flexible, customizable predictive maintenance services enterprises need.

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  • Reduced Fault Rate

    Using predictive system warning, a system’s fault rate falls by 70%.

  • Remote Troubleshooting

    Two-way communication enables remote troubleshooting, while maintenance costs are also reduced, with the impact on production minimized.

  • Reduced Fault Resolution Time

    Faults are quickly resolved in real-time using a cloud-based management platform, while system downtime is also significantly reduced.

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