From Brownfield to Industry 4.0

Foundation models are increasingly changing the way robots are used in industry. Instead of writing complex programs line by line, programmers will soon be able to collaborate more closely with AI systems, describe tasks, and review generated solutions. This shifts their role from purely generating code to conceptual, supervisory, and validation activities. This article highlights the new possibilities that large AI models create for robot programming and the changes they entail for work and required skills in industrial practice.

Certification for human-centered AI is becoming increasingly important—as a source of competitive differentiation, a response to regulatory expectations, and a mechanism for fostering human-centered work environments. But how can organizations determine whether the underlying requirements are truly embedded in practice? Drawing on expert interviews from established certification domains, this paper shows that the decisive question is answered not during the audit itself, but in the period between audit cycles. Ultimately, it is not the certificate that matters, but the commitment of organizational leadership and the organization as a whole to engage seriously in the certification process and its continuous implementation.

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 ...

From automotive supply chains to smart factories, data ecosystems promise seamless collaboration across company boundaries. But how can industries build the necessary infrastructure without creating new dependencies? This article explores how open-source software can serve as a foundation and impactful tool for sovereign, interoperable technologies and standards. Yet, open-source software is not a silver bullet; rather, it poses challenges for digital sovereignty in burgeoning data ecosystems.

Industrial digital platforms are considered the driving force behind digital value creation, yet legally they largely operate in a gray area. This article examines what defines industrial digital platforms and what legal framework applies to them. Existing platform regulations apply only to a limited extent to industrial digital platforms, which is why these platforms often establish their own legal framework through their terms and conditions. The article also explores the implications of European regulation, power asymmetries, and the opportunities and limitations of private regulation.