Exploitable Results
Leading digital transformation in manufacturing to new heights.
Trusted digital modularity solutions for the complex manufacturing sector.
Explore the project’s key exploitable results, designed to address tough industry challenges and cover your specific needs.
Digital Assistant for process chain in modular manufacturing
The Digital Assistant (DA) helps users decide the most suitable and responsive process chain design, systematically considering the availability and capacity of the process’s modules. It allows for the dynamic reconfiguration of processes in real-time, ensuring adaptation to changing customer demands and operational disruptions.
The Digital Assistant (DA) helps users decide the most suitable and responsive process chain design, systematically considering the availability and capacity of the process’s modules. It allows for the dynamic reconfiguration of processes in real-time, ensuring adaptation to changing customer demands and operational disruptions.
Part of the Digital Assistant UI, in which the results for a specific process design are presented, as well as the values of different parameters for each process machine/station (e.g. operation time, idle time and energy used).
- Improved decision-making and less planning effort. Provides optimal process design based on availability and capacity of process modules.
- Increased responsiveness, flexibility, and resilience. Facilitates rapid process configuration.
- Reduced manufacturing time. Streamlines production through optimal production process design.
Reconfigurable processes in different industrial domains to enable modularity.
Target sectors: industrial manufacturing, logistics, supply chains, energy sector, utility providers.
Data-driven design solutions
A set of digital tools with a strictly defined pipeline for applying Directed Energy Deposition (DED) Additive Manufacturing (AM) on top of existing metal industrial parts, to redesign or reshape them, while optimizing the AM process for the suitable material and minimizing operator interventions, experiments and necessary software.
An overview of various digital and process steps of part re-design, integrated into a unifying solution for tool correction in automotive industry
- Cost reduction due to drastically reduced time spent on engineering, simulation and preparation stage for each AM based iterative redesign cycle.
Tool modifications including carry-over solutions and minor adaptations during development.
Target sectors: automotive, machinery, aeronautical, railway, and other sectors.
Service-oriented middleware
The service-oriented middleware is an independent communication solution that resolves interoperability challenges between legacy and modern machines. It provides real-time tuning and configuration of production lines, offering high availability, scalability, and easy deployment while adhering to common industry standards for smooth and reliable data flow.
- Optimised communication across heterogeneous systems.
- Less operational complexity.
- Real-time production adjustments.
- Flexible, standards-based integration without vendor lock-in.
Machine builders, production facilities, system integrators, automation providers, OEMs, PCB industry, manufacturing companies of aerospace tools, and companies needing scalable, interoperable industrial communication.
Modular Simulation
The Modular Simulation solution provides Digital Twin–based virtual testing and validation of automation logic. It offers composable modelling of manufacturing systems, allowing users to evaluate system behaviour, prevent performance issues, plan productivity improvements, and adapt to changing production needs without requiring access to physical devices.
- Less time-consuming testing.
- Prevention of physical damage risks.
- Virtual commissioning.
- Open, IEC-61499–compliant alternative to proprietary simulation tools.
Ideal for professionals that need flexible virtual testing and 3D simulation solutions.
Target Users: machine builders, system integrators, automation engineers, and automation logic programmers.
Smart HW plug & produce interfaces within IEC61499
The Smart HW plug & produce solution provides IEC 61499–based software with modular southbound and northbound connectors, allowing for the integration of legacy systems, Digital Twins, and cloud platforms. It automatically configures connections from hierarchical IEC 61499 assets and improves simulation fidelity through real machine data.
- Faster integration of legacy systems into IEC 61499.
- Simplified connectivity to Digital Twins and cloud systems.
- Replacement of proprietary, hardware-specific solutions.
Ideal for professionals that need improved connectivity and IEC 61499-compliant plug-and-produce solutions.
Target Users: UniversalAutomation.org partners, system integrators, hardware vendors, and industrial users.
Standards-based distributed plug & control
This result provides an IEC 61499-based plug-and-control software solution that integrates shopfloor automation equipment through modular northbound and southbound connectors. It provides smooth interoperability across state-of-the-art and legacy systems, while enables full production-line simulation and real-time decision-making by executing IEC 61499 control logic directly within the Visual Component’s simulation environment.
- Software testing and validation.
- Visualization of results before commissioning.
- Protocol-independent and hardware-agnostic IEC 61499 control integration across production systems.
Ideal for professionals working on production lines, shopfloor design, cloud-connected control systems, and legacy system integration.
Target Users: system providers, system integrators, and end-users.
Hybrid twins for simulations
The hybrid digital twin is used for the pick-and-place process of capacitors of PCB’s (capacitors). It integrates a mathematical optimization algorithm that improves precision during the pick-and-place movement. The responsiveness to quality fluctuations and the mechatronic modeling of the digital twin enable adaptive execution of the assembly process.
- Provides a self-optimizing, self-controlled assembly process that increases output.
- Handles quality fluctuations effectively.
- Supports small and medium batch production efficiently.
Electrical manufacturing industries with high product variation, such as light-source producers, requiring efficient automated assembly for fluctuating batch sizes.
AR/MR prototypes for training and guidance
This result provides AR/MR training prototypes that create virtual training scenarios to support operator upskilling. Employees can train efficiently, even before real systems are deployed, while ensuring that all sensitive data collected during training is safely managed.
- Enables faster, more precise workforce training through virtual environments.
- Fully integrated with the Visual Components 4.0 platform.
Professionals in the manufacturing sector that are interested in simulation-based training and upskilling.
Target Users: machinery experts, apprentices, and production directors.
Human-centric value-chain knowledge consolidator
This result combines an Industrial IoT data collection platform with an explainable, human-centric decision support system. By exploiting swarm intelligence and x-AI models, it consolidates value-chain knowledge to optimize manufacturing processes, providing transparent recommendations, and enhancing trust in data-driven decisions.
- Transparent, trusted and adaptive decision-making by combining advanced analytics with explainability.
- Improved workflows and resource consumption.
- Greater overall operational efficiency.
Manufacturing production and maintenance departments with the need for process optimization, potential extension to healthcare, supply chain and energy sectors.
Swarm & augmented intelligence algorithms
A decentralized swarm intelligence software that dynamically optimizes robotic Printed Circuit Board (PCB) assembly. Local models learn independently, share insights without centralizing data, and adapt to new component types, improving process speed, efficiency, and quality while preserving data privacy.
Flow diagram illustrating the human-in-the-loop incremental learning and inference workflow of the Swarm Intelligence–based ML model.
Data flow diagram demonstrating the integration of the Swarm Intelligence Module with the eXtended Reality (XR) systems, and customizable UIs/HMIs within the MODUL4R metaverse, aiming to create a flexible, human-centered manufacturing environment.
- Real-time, adaptive automated assembly process optimization.
- Modular integration into manufacturing systems.
- Simulation-based validation.
- Privacy-preserving knowledge sharing across decentralized nodes.
Electronics and PCB manufacturing companies seeking smart manufacturing solutions, efficient robotic assembly, and secure, decentralized process optimization.