By Celina Kübel, project leader EMMI, product manager; Ben Schmidt, senior sales manager; and Martin Froese, service sales, Kampf GmbH

A new approach to machine operation will be introduced, offering modal machine interaction designed to reduce complexity, enhance safety and support intuitive use regardless of the operator’s skills or experience. It integrates features such as context-sensitive error analysis, real-time process guidance and automated documentation. In addition, the system architecture allows for seamless integration of production data, contributing to operational transparency and quality assurance. The initiative is motivated not only by skilled labor shortages but also by the limited training many operators receive in working with modern control systems. A tiered training framework further supports diverse user needs, promoting process stability and minimizing onboarding time.

Industrial production environments increasingly are shaped by demographic and technological change. Rising automation complexity, an aging workforce and increasing digitization have created new demands for operator support systems. In many sectors, there is a growing disconnect between advanced machine functionality and the experience level of the available workforce.

At the same time, there is increasing pressure on manufacturers to ensure high process reliability, minimize errors and maintain consistent product quality, even with inexperienced personnel. Addressing these challenges requires not only smarter machines but also smarter interaction concepts.

Simplifying machine operation for all users

The core of the concept is a multi-modal machine interaction that actively supports the user. The system is designed to reduce the mental workload associated with machine operation by providing support. For example:

• Process guidance: Step-by-step support tailored to the current machine status (see Figure 1).
• Error analysis: Identification of deviations with root cause suggestions and recommended actions.
• Dynamic interface scaling: Adjustment of displayed information and functions based on the user’s experience level or role.
• Integrated learning tools: Embedded tutorials and visual aids for each function or error state.

This aligns with human-centered design principles in industrial automation, where usability and error-tolerance increasingly are considered key to system effectiveness.

Easy Multi-Modal Interaction (EMMI) offers appropriate interface elements. For instance, inexperienced users might see a simplified mode with just essential functions, while expert users can access advanced features for optimization or parameter adjustment.

A response to structural workforce changes

The design of the EMMI concept is a direct response to two interrelated issues:

1. Skilled labor shortage: A shrinking pool of experienced operators has made it difficult for companies to ensure consistent machine performance.
2. Limited exposure to modern systems: Many newer employees lack formal training in contemporary digital interfaces and automation environments.

These factors can lead to reduced system use, safety risks and production variability.

Instead of expecting users to adapt to complex machines, this concept promotes machines that adapt to users. By embedding process knowledge into the interface, the system becomes a knowledge carrier and real-time assistant, thereby increasing accessibility and reducing onboarding time.

System architecture and key functions

The interface is built on a modular software architecture that supports integration with machine control systems, external sensors and enterprise platforms. Its main components include:

• User management module: Allows for role-based access and interface personalization.
• Diagnostic engine: Uses historical and real-time data to provide contextual suggestions during faults or abnormal operations.
• Data layer: Collects operational data, system events and performance indicators in real time.
• Documentation engine: Automatically logs relevant events and process states for traceability and quality control.

The architecture is designed to comply with cybersecurity standards and can be deployed either locally or with cloud-based services, depending on operational requirements.

Integration of production data and analytics

Integration with broader production IT systems enables:

• Real-time process monitoring
• Performance benchmarking
• Anomaly detection
• Process optimization recommendations

The combination of contextual data capture and intelligent HMI feedback creates a closed-loop system in which operator decisions can be continuously informed by machine behavior and historical insights. Additionally, all data is stored in standardized formats that support regulatory documentation, predictive maintenance and future AI model training.

Modular training programs

Given the variety of user experience levels, a one-size-fits-all training strategy is no longer sufficient. This concept incorporates multi-level training programs, aligned with the complexity of tasks and the user’s existing knowledge (see Figure 2). Levels include:

• Main: System introduction, basic machine operation
• Main Plus: Job setup
• Extended: Adjustments and tuning
• Extended Plus: Troubleshooting and training

Training content is available directly through the HMI or via a connected platform and includes interactive media formats, such as videos, quizzes and simulations. This approach ensures that operational knowledge becomes embedded in the system itself, rather than being solely dependent on individual experience.

Implications for operational safety and efficiency

By supporting users with proactive error handling, contextual help and adaptive interfaces, the system significantly reduces the likelihood of operator error. This contributes to:

• Improved process stability
• Shorter machine downtimes
• Faster onboarding of new personnel
• Higher compliance with operational guidelines

In addition, automated documentation reduces administrative effort and supports audits, while the modular architecture ensures compatibility with a wide range of machine types and configurations.

Conclusion

Rather than replacing the human role, the proposed system aims to augment it by aligning machine functionality with real-world operator capabilities. In doing so, it addresses both technical and demographic challenges, providing a path toward safer, more inclusive and more efficient machine operation. The EMMI concept, combined with modular training and real-time analytics, enables safe and intuitive machine operation across varying user expertise levels. It addresses both the labor shortage and the lack of training in modern systems, offering a scalable and resilient solution for industrial environments facing demographic and technological transitions. 

Kampf GmbH has been been the technology leader when it comes to slitting and winding technology for over 100 years. Headquartered in Wiehl near Cologne, the company employs over 800 people. The EMMI project was particularly exciting because it was based on global customer surveys, providing insights from users around the world. The interdisciplinary teamwork played a crucial role in shaping the solution, demonstrating how collaboration across different fields is essential for creating user-centered and impactful innovations. For more information, call +49 2262 81 0 or visit www.kampf.de.