by Steven London
Integrated Technology and Predictive AnalysisIn the next 10 years, the biggest challenge to fleet management will be the analysis of huge amounts of data (Big Data) and their application to vehicle maintenance, driver safety, productivity and lower operating costs. Technology developments that increase vehicle complexity will significantly augment fleet management capabilities, providing much greater visibility and access to trends which will prompt proactive maintenance measures. In the future, these new connectivity tools and safety options will ultimately lead to the implementation of autonomous vehicles. In the transportation business, truck breakdowns and other unscheduled events are unavoidable. The possibilities are endless, like a truck part failure, a traffic accident or sick driver, all of which can put a load behind schedule. The reduction of unscheduled events is a key to minimizing operating expenses. Fleets currently use an assortment of technology to view these events when they happen. Applications continuously monitor live data sent from vehicles to transportation management systems. While the event information sent in real time is helpful to fleet operations with current systems, often the damage has already been done, and the impact on the business can be costly. A superior system would be one that provides predictive data instead of just reporting unscheduled events. An example would be a fleet manager who receives real-time data with an alert indicating a potential problem in a truck exhaust treatment system prior to its failure. The manager redirects the problem truck to the closest dealer for repairs and reschedules the load to an alternate truck.
Telematics SystemsExperts predict fleet maintenance will increasingly use predictive analytics, which will convert maintenance into a more proactive and less reactive practice. Telematics systems have the potential to enable predictive capabilities and will most likely be standard equipment on fleet vehicles when shipped from the factory in the very near future. Telematics data can indicate route efficiency, resulting in the use of fewer vehicles and decreased fuel expenses. Driver behavior can be monitored, and predictive analytics can warn of a potential vehicle mechanical breakdown. Furthermore, a utilization analysis feature on a telematics system can provide valuable insight into a vehicle’s overall performance and make recommendations for replacements, helping create an annual budget and predict expenses.
Predictive MaintenanceOEMs and fleets are augmenting current remote diagnostics capabilities to develop predictive maintenance systems that promote cost-effective preventive measures. New remote diagnostics applications and services being developed by OEMs will result in substantial progress toward predictive maintenance. Reliable problem event predictions often require analysis of more than one piece of data. A specific combination of factors can sometimes lead to an unscheduled event. For example, both single fleet and collective OEM data on a specific truck model may well indicate the turbo has a high probability of failure at 270,000 miles combined with such conditions as specific weather patterns, high elevation routes and unique driver behaviors. All major truck manufacturers now provide remote diagnostics services to aid their customers and reduce unscheduled equipment downtime; however, more sophisticated systems are needed to handle more complex circumstances. Dick Hyatt, the chief executive officer of Decisiv, a Service Relationship Management (SRM) platform, foresees the service implementation in the next several years. “When you pull all of this together, you could start to predict component failures with enough certainty to change a $25,000 part before it fails,” Hyatt said.
More Dealer-Based RepairsInnovative remote diagnostic services provided by OEMs should augment their involvement in fleet vehicle repairs. Joy Schnetzka, manager of strategic alliances at Element Fleet Management, in an article for Automotive Fleet, said “In 5 to 10 years, we’ll be seeing more dealer-based repairs of fleet vehicles. Many non-dealer shops will only provide preventive maintenance services, due to more sophisticated technology. We anticipate the service process to become more complex and specialized, resulting in more reliance on dealerships.”
Triggering Service EventsAn important component of the predictive system will be the response time when diagnostic information indicates the need for service. Paccar, Volvo and Hino use a cloud-based platform from Decisiv to manage maintenance and unscheduled service events for their customers. Diagnostic trouble codes (DTCs) generated by vehicles trigger the events. Together, Decisiv and OEMs classify the severity of DTCs and decide what course of action must be taken for each event. When a fault code in the high severity category occurs, Decisiv starts the “PM due” process. All workflow participants, the OEM call center, the dealer network and the fleet are advised via text, email and the online truck dashboard. Faults of medium severity not requiring immediate action are registered in a pending file and remain with the truck. On the next shop visit, technicians can review the pending work file and implement corrective action for the DTCs. Least important, low severity faults are recorded in the asset profile, and they can be addressed during regularly scheduled maintenance. As service progresses, relevant information remains with the Decisiv platform, available to participants should additional action be necessary. To implement predictive maintenance for an anticipated service event, like changing out a potentially failing part before the appearance of a DTC, two important system changes are required:
- Technology suppliers must improve reliability by analyzing diagnostics and repair information from a much bigger database of vehicles.
- Repair data quality will need improvement by using standardized coding like Vehicle Maintenance Reporting Standards (VMRS).