By Dirk Wollschläger, IBM
Not long ago, a friend jokingly asked me “What happened to all the "lemons"? He didn’t mean the kind found in the fruit aisle. He was talking about the kinds of cars made in the 1970s that were so poorly built that they needed repairs practically as soon as they rolled off the assembly line.
Due to a steady increase in long-term advances in vehicles' quality, the reliability and longevity of cars has increased tremendously -- on all brands and worldwide. The age of the average vehicle on the road hit a record 11.4 years in 2013, according to research company R.L. Polk in Southfield, Mich.
Longer-lived vehicles go farther now. Service calls are less frequent, too. A generation ago, cars needed routine oil changes every 3,000 miles. Today, advanced lubricants and engine upgrades mean cars can go three to five times farther, according to Edmunds.com.
The average new vehicle today has about 2,000 functional mechanical components, and upwards of 100 million lines of software code. As vehicles become more intelligent, automakers are using software to provide updates for vehicles. Usually the car body is not modified during the vehicle life cycle, but software in the vehicle needs to be updated on a regular basis to ensure the connectivity with its environment or to improve the vehicle's functionality or performance.
Based on all the available sensor data in modern vehicles, our cars are turning into data factories. We see a fast-growing volume of available data, which, when combined with existing manufacturing and development data, can create tremendous value for all players in the automotive ecosystem. Unfortunately most of this data is currently not used to its full potential and is mostly stored as useless heaps of information.
By correlating all available pieces of structured and unstructured data, the industry could employ insights to optimize fleet performance while improving road safety. Or reduce the number of accidents through advanced driver assistance systems. The possibilities are endless and new business models will emerge in this exciting space.
The nature of car problems is shifting.
On average, automakers are discovering faults faster than they did in the past, helping them to issue recalls sooner, and limiting the pool of affected customers. This is achieved through new data analytics tools that assist in identifying issues as early as possible to avoid large warranty claims.
Here’s where these technologies are boosting quality and cutting costs today:
1. Design and manufacturing. Design errors grow more costly as they advance from sketch to assembly into production. Design and workflow software can help find a flaw while a part is still in the blueprint stage, preventing costly do-overs or recalls later.
For example, JTEKT Corp., a Japanese supplier of steering systems, implemented a software-based development process that carefully tracks changes to designs. This cuts the cost of do-overs and helps the parts maker ensure the quality and safety of its products earlier in a product’s lifecycle. For the Tokyo-based company, the effort cut development costs by up to 10 percent.
2. Use and maintenance. Better data is helping us to use our vehicles day to day, as well. Everyday drivers routinely experience the benefits of in-car sensors that monitor the status of everything from brakes to window washer fluid. Early warning helps to replace parts before they fail, leading to less interruption to our lives and businesses.
Big businesses are pushing these efforts most ambitiously, tracking performance data across whole fleets to learn how to better tweak vehicle maintenance to boost mileage and lower repair bills. Hager Spedition GmbH and Co., a German logistics and transport company, combined advanced vehicle performance monitors with location sensors in its fleet of commercial trucks.
Analytics helped route planners cut total miles travelled to simplify the paths that the fleet traveled. This process not only cut the total miles traveled, it also improved vehicle efficiency by 0.5 mpg and trimmed maintenance costs by 5 percent.
3. On-the-fly upgrades and vehicle redesign. As we learn more about how our vehicles perform, engineers are recognizing that data can be a vital resource to help refine how future iterations of the vehicle are made.
By mining data from warranty repairs, big auto companies can do advanced cost-performance analysis. Over tens of thousands of cars, the company may remove a lower-cost part that needs frequent replacement with a costlier upgrade. That may add to the bill of parts, but if the upgrade lasts longer and avoids warranty costs, it will save money in the long run.
Do all of these data-fueled changes mean that someday, we will be able to build a perfect car, free of faults?
Probably not, but we’ll keep getting closer. By shortening design and engineering cycles, optimizing energy use and reducing total development costs, car companies are rolling out new models that are more innovative, reliable and sustainable.
Dirk Wollschläger is General Manager of the Global Automotive Industry at IBM.
