New cars generate huge amounts of data, created in real time from vast numbers of connected sensors, instruments, and an increasing number of cameras – all of which provide great insight into every aspect of vehicle operation. A number of major manufacturers have committed to leveraging this data to inform predictive maintenance of vehicles, allowing remote diagnosis of most vehicle problems before they arrive at the service bar.
According to a new report by the Capgemini Research Institute, Accelerating automotive’s AI transformation: How driving AI enterprise-wide can turbo-charge organizational value, artificial intelligence (AI) technologies are key to the success of this predictive-maintenance approach. Jeff Lemmer, vice president and CIO at Ford Motor Company, explains in the report that AI isn’t just important to the high-profile work of developing autonomous cars, it is also vital to the future of all new vehicles.
“Not only are AI technologies critical for enabling our autonomous vehicles, but they are playing an increasing role in transforming our customer and employee experiences,” he says. He adds that Ford is already using AI to identify supply chain risk and for in-vehicle predictive maintenance.
Predictive maintenance is also a key goal for fleet operators, notably transportation and logistics companies for whom downtime is extremely costly. Global tire manufacturing giant Michelin, for example, announced in 2017 that it was introducing RFID (Radio Frequency Identification) in its commercial truck tires to provide more detailed, accurate reporting and insights and to inform tire-maintenance planning.
It appears obvious that vehicle owners stand to benefit significantly from predictive maintenance solutions that leverage on-board sensors, big data, and AI. What may be less clear, however, is that auto makers and the technology companies that power connected vehicles will also be big winners.
A 2016 white paper from the World Economic Forum suggests that, to start with, predictive maintenance will help a great deal in bringing down the cost of recalls. “Increasingly sophisticated in-vehicle diagnostic systems, smart components, and ubiquitous connectivity allow the vehicle and even some components to proactively signal when they need maintenance or replacement,” the report observes. It concludes that preventive maintenance enabled by continuous data analysis will reduce unanticipated failures and the “frequency and severity” of recalls.
The white paper also points out another key benefit of predictive maintenance: achieving and maintaining a closer relationship with customers. If a manufacturer’s on-board technology keeps a vehicle proactively serviced with greater reliability and at lower cost, the owner’s primary connection around service and maintenance will shift over time to the manufacturer and away from the dealer or local mechanics.
In short, predictive maintenance – built on the devices, machine learning, and AI that powers it – offers a host of potential benefits to vehicle owners and manufacturers. We expect to see ever-broader adoption of it.
To learn more about Capgemini’s automotive practice, contact Mike Hessler, North America Automotive and Industrial Equipment Lead, at email@example.com.