|Title:||Big Data as Enabler for Customer-Oriented Automotive Development||Other Titles:||Big Data as Enabler for Customer-Oriented Automotive Development||Language:||input.forms.value-pairs.iso-languages.en||Authors:||Ehrich, Fabian||Qualification level:||Diploma||Advisor:||Mayrhofer, Walter||Issue Date:||2018||Citation:||
Ehrich, F. (2018). Big Data as Enabler for Customer-Oriented Automotive Development [Master Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2018.55190
|Number of Pages:||110||Qualification level:||Diploma||Abstract:||
In automotive development, there are lots of assumptions made regarding customer needs as well as customer usage of a car. With the introduction of interconnected vehicles, a transfer of data from customers cars to automotive manufacturers will be possible. Access to data from sensors already embedded into the vehicles system can give automakers an insight into customer behaviour and enables them to use this information in their development of new generations of vehicles. When applying appropriate big data analysis tools access to the vast amount of data produced with customer vehicles could help to replace existing development standards, which include various assumptions regarding customer use with requirements based on data analysis. Privacy considerations are a very sensitive topic when it comes to analysing data from customer vehicles. While legal barriers regarding the use of personal data of customers are hardly existent in the US, the European Union has recently introduced strict rules, which regulate the collection and handling of customer data. At the same time, studies show that customers seem not too concerned about sharing their data with corporations they consider trustworthy. Thus, while legal frameworks have to be considered, data privacy seems no major road block for the introduction of analytic tools for data from customer cars. In this study, the potential of using data from customer vehicles as input in different development departments of a car manufacturer is studied. Based on publicly available literature and a series of expert interviews with nine automotive professionals, several use-cases were formulated for which analysing customer data can help to pursue a more customer-oriented development. Seven groups of possible usecases were established and evaluated regarding their potential benefits. All of the applications can offer significant cost saving potential for OEMs and enable the development of vehicles with additional customer benefit. The necessary preconditions as well as the consequences of using customer data as input for automotive development are discussed in more detail in a case study with focus on an OEMs durability department. For this example, a more technical discussion regarding implementation and execution of a system for feeding data from customer vehicles into a development department is showcased.
|Keywords:||big data; customer data; development; connected car; R&D
big data; customer data; development; connected car; R&D
|DOI:||10.34726/hss.2018.55190||Library ID:||AC15203750||Organisation:||E017 - Continuing Education Center||Publication Type:||Thesis
|Appears in Collections:||Thesis|
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checked on Jun 26, 2022
checked on Jun 26, 2022