| Cover Story Disruption from big data By Mark Reiter Vice President, Customer Support Navistar (www.Navistar.com) is a holding company whose subsidiaries and affiliates produce International brand commercial and military trucks, proprietary diesel engines and IC Bus brand school and commercial buses. An affiliate also provides truck and diesel engine service parts. Th e Internet of Th ings, and the big data derived from it, represents a huge new opportunity for fl eet maintainers. Th e potential for right-timing maintenance – to avoid both catastrophic breakdowns and excessive downtime for unneeded vehicle maintenance – has never been greater. Neither have the economic stakes. Why? Because today’s new trucks have never been more technologically advanced or more costly. Neither have their cargoes. Some observers estimate that today, every day that a typical over-the-road vehicle is not actually going over the road, its owner loses roughly $1,000. So unnecessary maintenance is as bad, in its own way, as catastrophic breakdowns. Getting trucks off the road only when they need it, and getting them back on the road as soon as possible, are major economic opportunities for fl eets. NEW PARADIGM Maintenance personnel are accordingly moving rapidly to take advantage of the more precise approaches now available through big data. Th e most important source of such data is the vehicle itself. Th e industry is moving to a new paradigm: • Th e historical model is “reactive” maintenance. Based on low visibility into potential problems, fl eets were used to simply reacting when problems arose. If it broke, you fi xed it. • A more recent model is “proactive” maintenance. If there was a problem with a given part, that part was replaced across the board. • Today’s disruptive approach is “predictive” maintenance. Not simply replacing every potentially at-risk part, but using knowledge of the vehicle itself to determine whether a failure is likely, given the way each vehicle is being used and the stresses it is putting on that part. Customers tell us they’ve saved lots of money by taking the predictive approach. What has made this possible are telematics and other connected services that result in a steady stream of data coming from the vehicle – and analytics that make the most of that data. “SYNTHETIC” CODES Analytics help assess the way a vehicle is used and how that may potentially aff ect a given part. Based on a vehicle’s application profi le, truck users can determine whether a given part is likely to break down on that vehicle – thus determining how important and time-sensitive a repair or part replacement might be. Advance notifi cation is likely to come in the form of a “synthetic” fault code – an analyticsbased construct that is designed to trigger a warning, typically before any specifi c failure occurs. Triggers can be based on a vehicle’s presence in a specifi c geographic area, when it reaches certain mileage intervals, when it has spent a given number of hours in service or many other parameters. Based on such precise insight, a given part may not need to be replaced in a given instance. Th e fi nancial impact can be signifi cant because of both reduced maintenance costs and improved uptime. Smart maintenance practices are especially important to uptime. Today’s detailed, advance knowledge can both head off unscheduled, catastrophic maintenance problems, plus prevent overreaction in the other direction, by reducing unnecessary maintenance and limiting repairs to the vehicles that actually require them. Data and analytics remove the guesswork in vehicle maintenance, allowing fl eets to make an educated decision about where and when to take a vehicle out of service for repairs or maintenance, or whether to: 1. Finish the delivery and take care of the issue during the next scheduled maintenance. 2. Deliver the current load and then get the truck serviced aft erward. 3. Stop the truck immediately and get it serviced right away to avoid progressive damage. Th is keeps trucks moving whenever possible. WRITE-UP PROCESS Big data – including vehicle-specifi c big data – is also critical to speeding repairs when they do prove to be necessary. One major area of opportunity is the write-up and diagnostic phase. Today, mobile applications can capture data from the vehicle upfront, including a “health report,” that can be automatically generated using telematics data. Not just before a technician examines the vehicle, but before a service advisor even speaks to the customer. New mobile input tools can also capture information from other sources, including specifi c customer complaints and photographs of the vehicle. When this information is captured more quickly, and analyzed quickly through analytics tools, it speeds the repair process, enhances its eff ectiveness and increases the likelihood that all current issues will be addressed, not just the one fl agged by the customer. Advanced input from telematics systems can also support a service we refer to as “smart repair routing.” Th is is where the combination of data and analytics – including the vehicle’s GPS location – not only enables diagnosis of a problem, but provides the driver and maintenance manager with a list of the best repair options and refers them on to service locations that have: • Th e requisite repair parts. • An open service bay. • A qualifi ed technician at the ready. We can envision a day in the not-too-distant future when a servicer and customer will initiate a dialogue based on a diagnostic trouble code and will be able to accurately diagnose and provide a repair estimate that details the time, parts and labor involved – all before the truck even gets to the service bay. Telematics-based tools are increasingly moving our industry into the predictive approach to maintenance. Th e ultimate goal: Maximize planned maintenance and minimize unplanned breakdowns. Reiter Data and analytics remove the guesswork in vehicle maintenance, allowing fl eets to make an educated decision about where and when to take a vehicle out of service for repairs or maintenance or whether to get it serviced later. Photo courtesy of Navistar 16 FLEET MAINTENANCE ❚ NOVEMBER/DECEMBER 2016 ❚ VehicleServicePros.com
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