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Machine Learning and Artificial Intelligence to reduce Vehicle Recalls

Damodar SahuBy Damodar Sahu, Consulting Partner & Head – IoT | Digital, Manufacturing & Technology SBU, Wipro Limited

Traditionally, Vehicles are purely mechanical, and not designed to provide digital solutions. OEMs are investing in the improvement of the quality of the engines and chassis, focused on improving safety and productivity. But the growth of internet technologiesi.e IoT and the results that have been achieved in the fields of AI, machine learning, and big data analytics are transforming the auto industry. With these technologies, OEMs are improving the driving experience, meeting customer expectations, and are well positioned to call it a Digital Vehicle or Digital Car.

The world is getting hyper-connected. Many factors are fueling this, such as the Internet, wired and wireless network connectivity and quality reaching far corners of the world, ubiquity of smartphones, as well as the emergence of Internet of Things. With such breakthrough advancements in technology along with societal demand, transportation is on the verge of a major transformation. Major technology players along with auto manufacturers are taking note. In a recent interview with the Wall Street Journal, Apple CEO Tim Cook stated that the auto industry is in for a “massive change” with software becoming “an increasingly important part of the car of the future.” Connected cars are a key result of this industry disruption, and will become mainstream globally by 2025.

Think about Vehicle Recalls, which are complex and have serious consequences if mishandled. The initiation of a recall is no time for an introduction to the many logistical and compliance challenges at play. Numerous supply chain partners and some regulators now require manufacturers to have a recall plan in place and this is the need of the hour to prepare.

Vehicle recalls and withdrawals impact many Auto OEMs every year – putting both people and brands at risk. If managed poorly, a recall can have devastating consequences on a company’s reputation, market share, and bottom line. But with the proper planning and systems in place, a recall event can be effectively managed to mitigate financial and legal risk, increase customer loyalty, and prevent irreparable brand damage.

Major Concerns?

Some frightening news has been brought up to light with recent research conducted by Auto Express. The research includes figures obtained from the Driver Vehicle Standards Agency (DVSA) which demonstrates the gloomy state of affairs for the automotive industry. Roughly 2.2 million vehicles were affected by recalls, with the top 10 list of recalls since 2012 led by Takata Corporation, an automotive parts company based in Japan, recently involved in a wide scale airbag recall.

What makes the situation worse is that millions of potentially dangerous vehicles have been affected by recalls, but just 47.7 per cent went back to dealers for repairs. That’s a lot of dangerous, faulty vehicles are still on road.

In June 2007, one major Auto OEM was forced to recall more than 400,000 vehicles over safety issues, affecting vehicles that were built in the company’s one plant. Problems included loss of motive power while driving, or unintended movement when the parking brake is applied, presenting obvious safety concerns for drivers.

This Auto OEM is not the only case. A South Korean OEM recently recalls over 240,000 vehicles due to defects in parking brake warning lights.

AI and machine learning to the rescue –

Recalling faulty products are difficult in any industry. The fallout can be horrific, and have serious implications for companies of all sizes. Controls in the automotive industry are of the utmost importance, as the fallout goes further than financial and reputational damage – people can get hurt as a result of product failures.

When it comes to safety issues, the sooner they are discovered, the better. The advanced data analysis can help identify the early warning signs. Using multiple databases, complaints can be tracked and researched to pinpoint patterns with specific parts and performance. By investigating potential safety concerns and developing campaigns earlier, automakers can perform outreach to vehicle owners more effectively to protect both the public and their brands.

Automotive manufacturers can reduce recalls and improve driver safety by applying machine learning and other technologies. These advancements can make sense of troves of data and help test potential problems before they go out with the use of “digital twins”.

Imagine being able to predict something going wrong before it does, to pre-empt failures and proactively take corrective actions. This is where artificial intelligence and machine learning come into play.

We are in the fourth industrial revolution (Industry 4.0) in which smart and connected devices, powered by machine learning and AI, are able to predict faults and anomalies in the manufacturing process. With the recent explosion of data and the increasing volume of sensors on every day devices, these technologies that have been around for decades are now becoming a reality.

The ability to create a full digital copy of an engine is achieved through the creation of ‘Digital Twins’, granular virtual copies of parts in the manufacturing process, which are enabled by deep learning and artificial intelligence. By creating ‘Digital Twins’, insights can be garnered to address the tiniest of issues that would otherwise be missed during a manual inspection process.

Another way in which AI and machine learning can help the automotive industry is by analysing the flood of manufacturing data received by machines. By analysing this data thoroughly and looking for anomalies via machine learning, you are able to predict catastrophic failures earlier, avoiding total breakdown and saving businesses large amounts of revenue and brand equity. By employing machine learning properly, businesses can prevent costly and reputation damaging recalls. This in turn minimises the need for businesses to issue recalls routinely, or for consumers to suffer the potentially dangerous fallout from faulty equipment.

Better Information, Better Recall 

Accurate owner information is what drives every step in the auto recall process. With enhanced data, the right customers are notified, repairs can be appropriately tracked, and compliance and regulatory reporting can be offered with the utmost confidence.

Conclusion

An effective recall not only keeps potential adversaries at bay, it fosters the goodwill needed to maintain strong brand affinity. It’s not the recall itself that differentiates a brand, but rather how well it is handled.When customer notification is done right, customer loyalty isn’t just protected, it’s enhanced.

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