The Car Battery Just Called…

This was originally posted on LinkedIn.

Analytics and device connectivity continue to transform vehicle maintenance and the automotive parts sector

We expect all of our devices to be reliable and always available. And it’s annoying when one of them fails; especially when you had a hunch it needed a check-up, but had put off booking a repair. 

When a car breaks down it can feel like the end of the world. Technologically, it is probably the most sophisticated device you own, lease or increasingly–share.  

But as well as being the most sophisticated device, it can also be the most frustrating, impactful and expensive object to fix when it breaks down. So how can data help?

Most modern vehicles have some element of onboard, digital self-diagnosis and will alert drivers as they occur. Breakdown cover providers like the AA in the UK are beginning to offer a ‘belt and braces’ approach and provide an additional layer of diagnostics to give their customers additional peace of mind. So what’s next?

In the future, your car will predict the future

Imagine if your car--or its electric battery--could not only predict an issue, but begin to resolve it by booking itself in for a service, request a technician stop by your home or even drive itself to the garage or charging station.

Smart analytics capabilities put the vehicle driver in a position where they can choose the most convenient time for the predictive maintenance to be applied.

Pick the right timing, the right location and ensure the service technician is equipped with the right knowledge and material to fix the problem in the shortest possible time with guaranteed first time right completion.

This can also be woven into your fleet example. If you combine the predictive information from the asset with social data (the preferred grocery store is in a location where the service agent could do the fix better and faster) guide the user to the grocery store and make an appointment for the fix whilst the user does his/her groceries.

Sounds far-fetched? At GE we are already doing this on industrial devices from wind turbines to jet engines and even elevators.

Customer requirements for assured availability and the introduction and adoption of autonomous and electric vehicles mean that automotive OEMs have already started making this scenario a reality.

Applying the power of advanced predictive analytics to vehicles’ existing onboard diagnostics makes it possible for OEMs and other providers to connect connected vehicles directly to the spare parts suppliers and ratchet up repair and service provision up a notch. 

Reinventing service and repair on the driveway

Every day thousands of home visits are made by mechanics and technicians to fulfill simple tasks, such as fitting replacement windshields and tires and fixing dents and scratches. 

As vehicles and batteries become more advanced, field service management in the automotive industry has also evolved significantly. Using advanced analytics, technicians are now able to address and solve a wider, newer array of issues and complications. This helps them anticipate customers’ demands for value and a rapid response to their specific problem as well as manage parts inventory and supply chain more efficiently. Unplanned break-downs will increasingly become a thing of the past.

While there will always be times when a vehicle needs to go into a traditional garage, in the future we foresee that more complex and increasingly digital repairs will take place on the driveway by a mechanic who has all the information at the tips of his fingers, just they do in other industries.  

The field service technician will still come perhaps directly from OEM, the dealership or a third-party breakdown service. However, what changes is that he or she will arrive ready equipped with diagnostic reports and analytical tools to remedy the problem there and then, traditional mechanical skills and any replacement parts. Remote connectivity will enable the engineer to order or eventually 3D print parts in advance of the call out–instead of waiting weeks for ‘that spare part’ to be shipped. (We’re working on that, too.)

Providing a 360 degree view of maintenance

Predictive maintenance and analytics is already providing improved service for private car owners, but where it comes into its own is when it is applied at scale for managers of large commercial fleets.

Often managing hundreds of vehicles, these managers need analytics to monitor the overall health and performance of the fleet to ensure it is running optimally. Real-time data also informs business critical and financial decisions around depreciation and asset performance management, meet regulatory requirements–important in the haulage industry--and streamline waste and battery management.

The change in customer preferences and the rise of car/ridesharing and commuting to work in cities means that the number and size of fleets will only continue to grow in the coming years. 

The one thing that doesn’t change is our expectation that transport will always be available, reliable and safe.

Extending predictive analytics across the automotive value chain

In order to ensure that availability and keep people on the move, it’s imperative that the huge volume of data being created by connected cars, the components themselves and service technicians can be quickly analyzed and directed seamlessly across the entire automotive value chain to parts manufacturers and suppliers.

The good news is that predictive maintenance and the use of advanced analytics is already widely implemented throughout this part of the industry.  GE has been providing software services to the automotive industry for decades, and we continue to work with many major OEMs and Tier 1 suppliers such as Pirelli and Brüggen to increase production efficiency and quality.

We are also collaborating with innovators like Bosch to ensure connected devices can communicate more easily. Bosch is also using augmented reality to reinvent the automotive maintenance and repair industry to help technicians provide top quality service, efficiently.

Just one great example where our partners in the automotive sector are already applying the potential of connecting predictive maintenance, advanced analytics and IIoT technologies in response to the shifting trends in mobility.

So, the first time your battery sends a message to your smartphone, you can probably presume everything is already under control.