I4S 1/2025: 40 Years of Digital Transformation in Manufacturing

Digital transformation has been a central focus of scientific discussions for years. It not only influences companies as a whole, but also permeates production in particular. Questions about data-driven decisions, the use of artificial intelligence and resilient supply chains are at the heart of current research. The 40th anniversary edition of Industry 4.0 Science—formerly known as Industrie Management—is dedicated to these topics and shows how companies can successfully shape digitalization in the future. The articles explain key trends and present scientific findings as well as practical solutions—from automation and the circular economy to cloud computing.

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I4S 1/2026: Applied AI Ethics in the Workplace A shared responsibility — from radiology and speech therapy to assembly

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?

I4S 3/2025: Digital Twin Innovative concepts for manufacturing, logistics, and learning environments

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.

I4S 2/2025: The Future of Production with AI, Cobots and Virtual Worlds Technology needs innovative, value-adding business models

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?

I4S 6/2024: Machine Learning A technology with optimization potential in terms of efficiency, transparency and sustainability

Machine learning takes automation to a new level. But what does this imply for the role of humans, who seem to remain essential for the effective control of AI systems. The development of energy-efficient and fair algorithms and the optimization of data quality are crucial for the future viability of machine learning and artificial intelligence. The articles in this issue examine the technology's key potential and areas of application.

I4S 5/2024: Double Transformation Integrating digital and ecological change in the world of work

Change is necessary for companies to maintain their competitive edge—both digital and ecological change. But while external support is at hand, the drive for change must come from companies themselves. In this issue of Industry 4.0 Science, experts of the Academic Society for Work and Industrial Organization discuss how the real-world application of innovative technologies lead to resource-efficient manufacturing.