| | October 20179CIOReviewthe collaboration with worldwide leaders in IT and networking equipment. Hyundai announced the introduction of the Autonomous Ioniq concept during its press conference at the 2016 Los Angeles Auto Show. With a sleek design resembling the rest of the Ioniq lineup, the vehicle is one of the few self-driving cars in development to have a hidden LiDAR system in its front bumper instead of on the roof. This enables it to look like any other car on the road and not a high school science project.Consumer mobility behavior is changing, with a significantly increased appetite for car sharing, which is seen by several major brands as a profitable business opportunity. Hyundai and WaiveCar, the world's first all-electric car-sharing program that runs on advertising dollars, have a partnership that will expose millions of shoppers to the all-new Hyundai Ioniq electric compact car for free.From the Engineering and Quality perspective, Hyundai Motor America is deeply immersed in understanding the details of the technology roadmaps related to these major trends, and is preparing for their aggressive deployment into the market. One of the common denominators of all these trends is the increased need and opportunity for Big Data Collection and Analysis, which they create at an unprecedented rate. The Big Data capability we're building at Hyundai benefits also the quality, safety, cybersecurity, and delivery process of the vehicle.In the automotive industry, one of the main metrics used to assess vehicle quality is the feedback provided by the owners and prospective buyers of the various models. This feedback is captured through many channels, including structured data such as service, repair, warranty information, and unstructured data coming from surveys, social media (blogs, forums), customer call centers and other sources. The Big Data Analysis techniques and tools are used at Hyundai Motor America to understand customer perceptions related to vehicle quality. Using these techniques we drive continuous improvements in vehicle design, manufacturing, distribution and service. The strategies employed include: · Showing different levels of data aggregation· Identifying changes for each product iteration· Comparing with peers· Tracking ranking over time· Creating cumulative metrics for trend analysis· Observing data in a time series to help with signal confirmation, and mining the text data across a time series.The related tools and skills required in order to materialize these strategies are a blend of established and emerging disciplines. Traditional SEQUEL queries along with fast and easy blending of disparate data sources are used. The strategy of automating tedious "data wrangling" tasks such as transforming, transposing, cross tabbing, dynamic calculations, deliver strong results. Various text mining tools along with user friendly environments that support on-the-fly calculations and fast, powerful visualizations are part of the Big Data Analysis package. An extremely important aspect remains the subject matter expertise, which saves significant time and effort and avoids drawing spurious correlations in the data.Other applications of the Big Data Analysis capability include the information generated by the battery and fuel cell electric vehicles already deployed in the market. This application helps tremendously with the understanding of consumer behavior and driving patterns, influencing positively the future developments of the vehicle and charging/fueling infrastructure. As an example, the Ioniq EV battery capacity was selected to satisfy over 98 percent of the American new vehicle buyers commuting needs and the emphasis was placed on the efficient operation of the vehicle to maximize its range. One of the main metrics used to assess vehicle quality is the feedback provided by the ownersDr. Mircea Gradu
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