3 questions for Matthias Weigold on cross-company data usage in production

Prof. Dr.-Ing. Weigold, Head of the Institute for Production Management, Technology and Machine Tools, TU Darmstadt

Copyright: © PTW | TU Darmstadt
München, 12 November 2025

Cross-company cooperation and the shared use of production data open up enormous potential for efficiency, resilience and labour productivity in industrial value networks. Trustworthy data exchange not only makes production processes more transparent, but also more adaptive. Companies can respond more quickly to disruptions, bottlenecks or fluctuations in demand, while at the same time increasing their resource efficiency. Furthermore, we can increase labour productivity by giving employees access to new, context-related information via collaborative platforms and by increasingly relying on data-driven decisions in our manufacturing operations.

In my view, new value creation potential is opening up, particularly in collaborative service businesses, in the measurable recording and reduction of CO₂ emissions throughout the product life cycle, and in digitally supported quality processes.

The insights gained in the GAIA-X flagship project EuProGigant clearly show that open, decentralised and sovereign data ecosystems form the necessary basis for a trustworthy industrial data economy. Such approaches ensure data sovereignty for those involved, promote innovation across company boundaries and, at the same time, strengthen Europe’s digital and industrial sovereignty.

The shared use of production data based on open standards is therefore not only a technical but also a strategic tool for ensuring the competitiveness, sustainability and future viability of European industry.

Interoperable infrastructures, uniform interface standards and trustworthy governance models are the basis that guarantees data sovereignty and information security. While large companies usually have their own IT departments and proven security architectures, the starting point for small and medium-sized enterprises (SMEs) is much more heterogeneous. In medium-sized mechanical engineering companies, specific knowledge of IoT infrastructures, data architectures and IT security is often not available in-house. Therefore, cooperation with specialised partners from the IT and digital economy is a crucial prerequisite for building and operating sovereign data solutions.

The first hurdle here is often at the cultural and communicative level: it is important to find a common language between manufacturing companies and IT partners, to understand different perspectives and to unite them into a common goal. If this is successful, high added value can be created – both through efficiency gains and through the development of new data-based business models.

Small and medium-sized enterprises in particular have considerable potential for innovation. The seamless exchange of data across company boundaries can give rise to completely new forms of value creation. Cross-company data usage can be a decisive lever, especially for SMEs, for securing their competitiveness, strengthening their own innovative power and tapping into new markets in the context of Industrie 4.0. One example of this is component manufacturers who can offer additional services and analyses by digitally connecting their products to machine tools or production facilities. This transforms a traditional product supplier into a data-driven solution provider that generates added value throughout the entire life cycle of its products.

In my view, not all approaches to artificial intelligence are energy-intensive per se. We have been able to demonstrate that data usage in production can unlock great potential. However, this requires large amounts of data and a multitude of processing applications. Targeted solutions must therefore be developed. For me, digital efficiency encompasses three main areas that are important for manufacturing companies. Firstly, economy in terms of data volumes and storage times; secondly, economy in terms of data processing and data analysis; and thirdly, the optimal choice of storage and computing capacities. In the so-called edge-cloud continuum, various locations with different technical conditions and resource consumption are available today, ranging from local edge systems to factory-owned servers to large cloud-based server centres.

When it comes to edge solutions in particular, I see considerable opportunities in Germany and Europe to combine our technological strengths in mechanical engineering with innovative edge applications, thereby promoting sustainable, sovereign value creation. Today more than ever, it is about our digital sovereignty, but also about Europe’s industrial sovereignty!

Finally, on the path to climate-neutral production, I would like to highlight two aspects: energy efficiency and energy flexibility. In our research work and in the practical implementation of this in industry, we have been able to show that data-driven approaches open up new solutions – for example, for the optimal control of production systems and their energy supply.

Used correctly, AI can not only reduce energy consumption, but also help to better integrate renewable energies into industrial processes – an important step towards sustainable and future-proof production.