How can augmented reality (AR), virtual reality (VR), and digital twins support service and training in print production?

The printing industry, particularly small and medium-sized enterprises, is currently facing a number of challenges. The shortage of skilled workers is growing, and modern production systems are becoming increasingly demanding. Many processes can no longer be carried out manually and complex systems require a high level of technical knowledge. To address these issues, companies are increasingly turning to digital technologies such as augmented reality (AR), virtual reality (VR) and mixed reality (MR), as well as digital twins. These technologies support training and qualifications, help retain knowledge, reduce downtime and support stable and reliable production processes.

Many companies lack qualified personnel, particularly in technical services, further processing, and machine operation. The consequences are clear: production delays, bottlenecks in order processing and reduced capacity utilisation. Traditional training methods, such as classroom-based training or digital training videos, often prove inadequate when conveying detailed operational knowledge. Even remote support alone is insufficient to safeguard everyday operations in networked production environments. This is why they need solutions that impart knowledge in context, structure processes and deliver consistent results.

In addition, many companies are choosing to automate everyday processes. This frees up employees to focus on more critical technical responsibilities and enables more reliable planning. This is particularly important given the scarcity of resources.

Technologies such as AR, VR, and MR allow complex machinery to be simulated and operated in virtual environments without disrupting real systems or posing production risks. At drupa 2024, a variety of systems of this kind were on display and could be experienced first-hand. These applications are based on digital twins, i.e. virtual images of real machines created using design data. Employees can use this digital environment to familiarise themselves with machine layouts and components, to understand assembly processes, and to simulate typical error scenarios.

Since these workflows can be repeated as often as desired, new employees can gradually become familiar with their tasks. This shortens the training period while increasing safety and independence when working with the equipment.

However, digital twins are useful not only for training purposes, but also for ongoing operations. They form the basis of a new approach to maintenance, diagnosis, and error analysis. For instance, they can serve as an interactive spare parts catalogue, directly linked to the physical machine, in mixed reality applications. Technical staff are shown the necessary steps visually, directly on the relevant component. This speeds up troubleshooting and simplifies rare interventions, as the necessary information is immediately available in context.

Such systems also significantly reduce the day-to-day workload of the workforce. Step-by-step instructions stored in the system can be accessed at any time. This makes processes more clearly structured, and technical tasks easier to prioritise. Consequently, specialised technicians can devote more time to complex activities, while routine tasks can be performed safely and reliably by personnel with basic technical training.

Another important area of application is predictive maintenance. By evaluating operating data, signs of wear can be identified early on, before any failures occur. Automation platforms developed by major manufacturers combine traditional maintenance processes with data-driven analysis. This enables maintenance intervals to be tailored to the actual load on individual components. This improves planning and reduces unexpected downtime.

The design of service contracts is another key factor in ensuring the economical operation of a plant. Even the best technology is ineffective if timely support or spare parts are unavailable. It is therefore important to consider the following questions carefully: How quickly can technical support be reached? Are there reliable escalation levels? To what extent can remote diagnostics help avoid travel and minimise downtime?

The supply of spare parts also plays a central role. It is important to consider which components are kept in stock, and how reliable the supply chain is. Automated reordering processes for wear parts, for example, help prevent bottlenecks and minimise production interruptions.

Internal staff training is another critical factor. If employees can perform simple maintenance tasks themselves, this strengthens operational independence and speeds up problem solving. Digital twins and immersive training environments make an important contribution here, as they present knowledge in a comprehensible and practical way.

Targeted measures can also reduce operating costs. Modular machines allow individual components to be replaced without dismantling entire assemblies. This makes repairs simpler, maintenance cycles more predictable, and helps ensure systems operate efficiently throughout their entire life cycle.

The ultimate goal is not to replace skilled workers, but to support them more effectively. Digital assistance systems, automation, and immersive technologies make technical knowledge more accessible, streamline training processes, and help ensure long-term retention of operational knowledge. At drupa, many companies demonstrated that they are already adopting this approach. Investing in digital infrastructure today strengthens production reliability and gives companies a competitive advantage, not least because it enables new employees to be trained more quickly.