In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the
analysis of acoustic data to detect and understand previously unknown errors in the …

We present ManuKnowVis, the result of a design study, in which we contextualize data from
multiple knowledge repositories of a manufacturing process for battery modules used in …

Abstract Random Forests (RFs) are a machine learning (ML) technique widely used across
industries. The interpretation of a given RF usually relies on the analysis of statistical values …

Electrical engines are a key technology all automotive manufacturers must master to stay
competitive. Engineers need to analyze an overwhelming number of engine measurements …

The conversion between tacit and explicit knowledge remains an often-discussed and highly
relevant topic in organizational knowledge creation. Although prior research addresses this …

Numerical simulation has become omnipresent in the automotive domain, posing new
challenges such as high-dimensional parameter spaces and large as well as incomplete …

Due to the increasing digitalization of production processes, more and more sensor data is
recorded for subsequent analysis in various use cases (eg predictive maintenance). The …

Künstliche Intelligenz (KI) kommt zunehmend im Alltag, in der Wissenschaft, aber auch in
verschiedenen Bereichen der Automobilindustrie zum Einsatz. KI ermöglicht intelligenter …

The 21st century will be heavily impacted by the capability to create value from recorded
data of all kinds. In this regard, industrial manufacturing intuitions increasingly rely on new …