Melina Panzner successfully completed her doctorate on the topic of "Systematics for the design of ambidextrous innovation management" under Prof Dr. Roman Dumitrescu.
Summary of the doctoral dissertation:
The latest technical developments make it possible to collect and analyse large amounts of data from cyber-physical systems (CPS) during operation. These analyses provide manufacturers with deeper insights into product usage and functionality, which can be used to derive new requirements or product ideas. However, the process of analysing data is a challenge, especially for small and medium-sized companies, as they often lack the necessary bundled expert knowledge in the fields of product, product planning and data analysis. A suitable approach to empower domain experts and citizen data scientists for these data analyses is not yet available.
A system is therefore being developed to analyse data in operational data-supported product planning. The foundation of the system is a reference process for data analysis in operational data-based product planning. An analytics toolkit provides relevant solution components along the process. The procedure for production data-supported product planning enables its users to determine the appropriate solution components of the analytics toolbox using various tools. The aforementioned elements of the system are prototypically implemented in a digital learning assistant. The system is demonstrated using two case studies and its benefits are evaluated in initial approaches.
