Lasting Transformation: why digital sophistication is going to be a competitive advantage

Traditional mechanical engineering is undergoing a transformation. Digital technologies have become increasingly important, and alongside product quality, digital sophistication has been the emerging competitive advantage.
Digitalization in globalized supply chains is shifting the boundaries of production as well as the way in which companies monitor and control their manufacturing processes. A forward-looking concept in this context is Remote Operation Support – the remote assistance and control of production systems.

The machine tool industry in particular can use this to enhance the efficiency, availability, and flexibility of highly complex machinery and systems. Crucial for its success are convincing benefits, compatible eco systems, a solid cyber security concept and a scalable business case.
 

With modern sensor technology, IoT platforms, and AI-based monitoring systems, machine tools can operate autonomously while being monitored from a central location. This allows night shifts to be carried out worldwide without on-site personneland allows expertise to be integrated into the production process regardless of geographical availability. Highly skilled technicians and engineers can support machines worldwide from a central location. This reduces the need for expensive and time-consuming travel, particularly in regions where specific know-how is not readily available.

In the future, such services will become even more successful through the integration of technologies such as augmented reality and digital twins.
 

Recent research ideas have led to industry-driven initiatives such as CatenaX (automotive industry) and ManufacturingX (mechanical and plant engineering), which will become the foundation for data-driven business models.

The global success of the European automotive industry over the past decade forms the basis for the future cyber-physical ecosystem of manufacturing networks. Together with VDMA and CECIMO (the European Association of the Machine Tool Industries), machine manufacturers initiated Factory-X for plant engineering based off of CatenaX. Similar to the successful implementation of umati [umati - universal machine technology interface - connecting the world of machinery] as the globally standardized language for mechanical engineering, these efforts will lay the foundation for future business models.
 

Connectivity in production systems drives the requirements for data protection and cybersecurity. Production data is among a company’s most sensitive information because it not only reflects internal processes but also strategic decisions. Protecting this data is essential to keep economic and legal risks to a minimum. It will require significant efforts from all industry associations in shaping the Cyber Resilience Act (CRA). Modern remote solutions must meet the highest security standards. This includes encrypted data transmission, strict access policies, and the implementation of zero-trust architectures. Furthermore, continuous audits and real-time monitoring are necessary to detect and close potential security gaps early on.
 

Remote Operation Support is not only a technological advancement but a milestone of fundamental transformation in the manufacturing industry. The ability to monitor and control machines around the clock and independent of geographic location opens up new dimensions in terms of efficiency, flexibility, and globally networked collaboration.

A central theme for the future will be the business case of remote services. Companies must clearly define how these technologies can be refinanced and integrated into existing business models. The shift from traditional machine sales to data-driven “Everything-as-a-Service” (XaaS) models requires not only technical innovation but also new approaches to cost structures, pricing and sales strategies. This creates recurring revenue streams, such as subscription-based service packages, pay-per-use models, or data-driven value-added services like predictive maintenance.