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Through data collection, status monitoring, and statistical algorithms, predictive maintenance schedules the right service calls at the right times. Internet of Things (IoT) technology has made it practical to monitor a variety of components in systems ranging from manufacturing machinery to vehicle engines, while predictive algorithms have been tuned to prevent machine failures and reduce overall maintenance costs. To support predictive maintenance efforts, Huawei offers a solution that includes a cloud-based IoT platform and cost-effective networking options.
Solution Highlights:
· Cloud-Based IoT Platforms: Deployed on a public cloud with unique agents supporting flexible terminal access. The IoT platform interconnects with predictive maintenance application layers through open APIs.
· Flexible Networking Solutions: Real-time data can be uploaded over operator networks to minimize latency, while non-real-time data can be locally uploaded to mobile phones through Wi-Fi networks; this is especially useful when operator network coverage is poor.
· Innovative In-Vehicle Terminals: For vehicle maintenance, Huawei’s terminals can collect data at 250 kbit/s through CANBUS using multiple types of interfaces for collecting various sensor data. The terminals support wireless LTE data backhaul and report vehicle location using GPS. A rugged industrial design allows the terminals to withstand high-vibration working environments.
System warnings reduce fault rates by 70 percent.
Two-way communication enables remote fixes and greatly reduces maintenance costs.
Downtime is significantly reduced.
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