E-Journals

Artificial intelligence is transforming knowledge work. Diagnosis, decision-making, and optimization are increasingly shaped by the interaction between humans and AI. As a result, AI proficiency is becoming a competitive factor, although technical expertise—the foundation of industrial performance—must not be lost. This issue explores the potential of AI in manufacturing as well as the skill requirements for AI-based knowledge management.

Digital platforms and data spaces are transforming industrial value creation and creating new opportunities for cross-organizational collaboration. At the same time, new requirements are emerging regarding data sovereignty, security, and governance. This issue of Industry 4.0 Science provides insights into the DynaVer research program, in which 15 interdisciplinary projects are investigating the dynamics of digitally networked value creation systems.

Immersive technologies are fundamentally transforming manufacturing. VR, AR, MR, and XR merge physical and digital worlds into interactive work environments. In Industry 4.0, they enable more intuitive access to planning, production, maintenance, and training. This issue of Industry 4.0 Science shows how immersive technologies are becoming a central building block of resilient, flexible, and innovative production systems.

In recent years, learning factories have evolved into key experimental environments in the context of the Fourth Industrial Revolution. In addition to their role as training centers for skilled workers, they also serve as real-world research laboratories. This issue of Industry 4.0 Science examines learning factories as venues for exploring new approaches and technologies—whether digital assistants, cobots, serious games, or digital twins.

AI ethics in the workplace is everyone’s responsibility. It requires accountability from companies as a whole and conscious action from individuals—whether developers or users, managers or employees. Key issues revolve around ethical AI skills and questions of governance and employee representation. How will the world of work change, from radiology and speech therapy to assembly and quality control?

Manufacturing is leaving Earth: what was once science fiction is becoming a strategic field for the future. Falling launch costs and new space industry players are enabling production and services under conditions that are impossible on Earth—from in-orbit maintenance to novel manufacturing processes in microgravity. This issue highlights opportunities, business models, and technological hurdles on the path to value chains in space.

Demographic change, skills shortages, and stagnating productivity are threatening the competitiveness of German industry. At the same time, AI and digital assistance systems are opening up new opportunities: they make work more efficient and support skilled workers. But while they have long been part of everyday life, their potential in industry remains largely untapped—this is where this issue comes in with innovative concepts.

Logistics is entering a new era. Climate change and geopolitical uncertainties are shifting the focus to resilience and sustainability. The concept of smart logistics is gaining importance. But what exactly makes logistics smart, and how can it help us organize our societies and the economy? Approaches such as predictive analytics, demand analysis, and machine learning show why smart logistics is more than just a technological trend.

In the connected world, digital twins open up completely new possibilities: they virtually replicate physical systems, processes, or products. However, key challenges remain, including the collection of current product data. This issue of Industry 4.0 Science covers a wide range of topics, from the basic concept of the digital twin to its benefits in procurement and its use in supply chain management.

Artificial intelligence, collaborative robotics, and virtual worlds, such as the metaverse, are fueling visions for new forms of industrial value creation. However, innovation alone is not enough—given that these technologies only develop their full potential through intelligent business models. How can companies efficiently integrate AI-supported automation, cobots and digital twins into their processes?