Furthermore, we integrate engineering processes with these new and AI-driven capabilities. Object-Centric Process Mining (OCPM) in Celonis provides a powerful, quantitative view on planning processes — it reveals how often, how long, and in which variants activities are executed across multiple object types. However, in complex automotive production planning (e.g., Mercedes-Benz MO/E), the resulting Process Intelligence Graph remains largely descriptive: it answers "how much?" but not "why?". The goal is to design, prototype and evaluate a concept that links object-centric event data from Celonis with the version- and scenario-semantics from our software, enabling explainable, scenario-aware process intelligence in production planning. * Which structural and semantic gaps exist in the Celonis OCPM representation of the current Mercedes-Benz planning process?
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