Warehouse Inventory Detection with Airship Drones

Generative Artificial Intelligence (GenAI) offers new opportunities for organizational knowledge management, particularly when it comes to learning processes at the interface between explicit, firm-specific, and tacit knowledge. Its use is therefore of particular interest for application areas such as industrial maintenance. Based on a mechanical engineering case study, this article demonstrates that augmenting both processes and employees with GenAI requires AI literacy combined with professional skills.

Can artificial intelligence be used to assess the validity and credibility of simulation models and data for production and logistics? And what requirements must AI assistance meet to effectively support experts in verification and validation while simultaneously safeguarding their competence? In an online survey, simulation experts were asked regarding their expectations and needs.

Companies are increasingly challenged to address shortages of skilled workers while meeting rising demands for productivity, flexibility, and innovation. Because labor supply can only be expanded to a limited extent, there is a growing focus on designing work systems with productivity in mind. Autonomous systems offer significant potential in this regard. Their implementation requires not only technical adjustments but, above all, changes in organization, skills, and work design. This article analyzes empirically grounded change requirements in existing work systems as well as associated economic potential.

Industrial supply chains must repeatedly reconfigure sourcing strategies in response to disruptions, yet supplier capability information remains heterogeneous and difficult to operationalize. Existing research addresses supplier selection, simulation, and interoperability standards separately, treating discovery, evaluation, and optimization as disconnected steps requiring manual data transformation. This paper presents a framework for a data-driven industrial platform integrating three components: Asset Administration Shell-based supplier profiles structured by an Actor-Service ontology for semantic discovery, automatic discrete-event simulation model generation from layout data for performance evaluation, and KPI-driven configuration using optimization algorithms. The main contributions are an end-to-end interoperable workflow, a two-tier supplier profile concept separating semantic descriptions from simulation parameters, and a standardized KPI interface maintaining consistency ...