From Aeris: "How Fleet Managers Minimize Downtime with Predictive, Proactive IoT / M2M Service Support"

Mar 29, 2018
 

Written by Carmi Brandis from Aeris Communications

 

In the world of automotive fleets, downtime most often occurs as a result of mechanical breakdowns or accidents. When a service vehicle is incapacitated through accident or breakdown, a temporary replacement may be difficult to acquire quickly, extending downtime and increasing the likelihood that the vehicle will exceed its allocated operations budget. According to Automotive Fleet, downtime results in an average cost of $79.32 per hour, per driver, without factoring in the expenses incurred by rolling trucks and making repairs.

 

With the costs and operational pressures caused by downtime in mind, IoT developers have sought predictive maintenance solutions through IoT / M2M connectivity. Today’s IoT networks can provide both predictive and proactive reports and alerts to prevent excessive rolling trucks, cut down on manpower needs, and eliminate downtime of business-critical assets. Through proper IoT / M2M implementation, managers can initiate scheduled maintenance, remote servicing, and preventative training so issues that cause breakdowns can be addressed before they occur.

 

How Fleets Utilize Predictive Analytics to Prevent Downtime

In many major industries, such as retail, finance, and insurance, predictive analytics aid in risk management and outcome forecasting. When applied to fleets, predictive models can be a powerful tool for managers to either automate or make more educated and cost-effective decisions in various parts of operations. Using telematics data collected and transmitted by IoT / M2M devices to a management platform, fleet managers can assess driver performance, monitor vehicle health, and provide real-time support to drivers in the field.

 

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Through an automated IoT platform, driver data, such as average speed, braking habits, and signal use, can be collected and assessed to determine the driver’s impact on fuel consumption, vehicle wear and tear, and potential for vehicle breakdown or accident. If the driver is considered a risk based on parameters set by the fleet manager, their profile can trigger alerts to address the issue. With driver data in hand, the driver can be placed in safety training programs that are tailored specifically to address specific behaviors before a collision occurs. If the driver is involved in a collision, the system can send an alert instantly and roll trucks (if needed) to the crash site, as well as provide data to pinpoint a probable cause and assess the extent of any damage.  

Utilizing vehicle performance telematics, an IoT / M2M platform also can predict vehicle lifecycles and determine the likelihood of imminent breakdown. When the system determines that a vehicle is in need of preventative maintenance, it can alert the fleet manager and call the vehicle in for scheduled service or direct it to an in-field servicing station, thereby preventing the costs and manpower needs associated with rolling trucks, in-field vehicle replacement, and unscheduled downtime.

 

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Manage Fleet Health and Safety with Aeris

Aeris provides a reliable mobile network optimized to meet the demands of worldwide fleet management systems. All IoT / M2M telematics data is collected and analyzed in one place for a system that is simple, adaptable, and effective for any fleet management task. Regardless of location, Aeris can provide a solution for telematics and fleet management that lowers costs and improves operational efficiencies with data analytics.

 

Source: https://blog.aeris.com/how-fleet-managers-minimize-downtime-with-predictive-proactive-iot-/-m2m-service-support

 



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