Three Applications of LPWAN for Industrial Fleet Management
LPWAN-enabled sensor networks collect information about equipment usage, speed, emission, location and more. These data are then forwarded to the cloud for long-term diagnostics and predictive analysis. Actionable insights can be distilled to help companies optimize productivity, compliance and safety, and ultimately improve their bottom line.
1. Condition Monitoring and Predictive Maintenance
Predictive analytics enables fleet operators to stay on top of maintenance by anticipating and correcting failures before they even occur. Built-in sensors transmit key health and operational parameters of tires, hydraulics, engine and other components of mobile equipment. Using automated alerts, operators are informed of any intolerable deviations that hint at impending or abnormal conditions. This allows for advanced planning of oil and part replacements, along with reparation scheduling to avoid costly downtime.
2. Optimizing Asset Utilization
Underutilized machinery with excessive idling time results in wasted fuel while incurring additional fixed equipment costs. Data about idle times captured by telematics sensors allow operators to make informed decisions about the optimal size and composition of their fleets, and whether to buy or lease. Unauthorized usage outside operational hours can be additionally detected to avoid any tampering or theft attempts. Overall, asset utilization data contribute to improving OEE and ultimately, net profit margins.
3. Emission Control and Fuel Consumption Management
As climate change continues to become a top global concern, fleet operators are facing increasing regulations and pressure to curb their carbon footprints. In underground mines, emission control is also critical in sustaining a secure work environment for miners.
With connected equipment powered by Underground Fleet Management System, operators can monitor exhaust emissions to ensure compliance with environmental and safety regulations. Likewise, information about vehicle status and operating patterns, reveals bottlenecks and enables optimization of fuel usage. For example, low tire pressure can increase fuel consumption and reduce gas mileage.
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