Abstract
Cyber-physical systems (CPS) generate huge amounts of data during the usage phase. By analyzing these data, CPS providers can systematically uncover hidden product improvement potentials for future product generations. But many companies face difficulties starting industrial data analytics projects as they cannot rely on experience and miss orientation. Following the canonical action research methodology, this study aims to investigate the definition and specification of data analytics use cases. The results show a clear need for supporting methods and tools for defining and specifying use cases in usage data-driven product planning.
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