Multi‑Level Communication and Computation Middleware in MODUL4R
Author: Maria Tassi
May 30th 2025
The MODUL4R project is transforming industrial manufacturing by creating adaptable, resilient, and reconfigurable production systems. The backbone for this transformation is a distributed control framework for modular "Plug & Produce" (PnP) systems, the development of which was successfully completed in April 2025.
CORE IC led these research activities and developed the Multi‑level Communication and Computation Middleware (MCCM) - a fundamental innovation in MODUL4R - that bridges the gap between Cyber‑Physical Systems (CPS) and modular data exchange frameworks, allowing for smooth interoperability across edge, fog, and cloud layers.
The Role of MCCM in Modular Manufacturing
The MCCM was developed to tackle the challenges of modern manufacturing where agility, real‑time decision‑making, and scalability are essential, optimizing industrial operations through dynamic task distribution. By integrating edge, fog, and cloud computing, the MCCM ensures efficient data processing, low latency communication, and dynamic resource allocation. Its architecture is in line with the RAMI 4.0 reference model, supporting Industry 4.0 standards and enabling vendor‑agnostic communication.
Some of the key features of MCCM include:
Hybrid Computing Platform
Edge Layer: Serves as the entry point to the asset layer, ensuring low latency communication and direct interaction with physical systems, enabling real‑time interaction with shopfloor devices.
Fog Layer: Acts as an intermediary for intensive computation, edge orchestration, and near real‑time execution, minimising the latency for critical decision making while reducing cloud dependency.
Cloud Layer: Provides security, scalability, and robustness while enabling external communication with third‑party services.
Dynamic Reconfiguration
Enables real‑time adjustments to workflows, ensuring adaptability to changing production demands.
Supports Infrastructure‑as‑a‑Service (IaaS), allowing third‑party applications to be deployed via containerization (e.g., using Kubernetes).
Service‑Oriented Architecture
Facilitates modular deployment of microservices, ensuring flexibility and scalability.
Uses MQTT, REST APIs or seamless data exchange between layers.
Orchestration Across Layers
The Orchestration Controller offers dynamic service allocation, across different levels, to optimize resource usage across different levels optimizing resource usage.
Enables multi‑cluster management, ensuring efficient workload distribution.
Orchestration within the MODUL4R hybrid computation environment
In more detail, MCCM establishes a service‑oriented, hybrid computation platform designed to orchestrate communication and computation within Cyber‑Physical Systems of Systems (CPSoS) networks. On the shopfloor, data generated by individual CPS components is acquired through industrial communication protocols such as OPC‑UA at the edge layer. This data is then transmitted via MQTT message brokers to corresponding MODUL4R services, where it is processed.
These services, along with the brokers, are typically deployed across the fog and cloud layers, depending on latency requirements and computational needs. MCCM facilitates seamless deployment of services and brokers across the appropriate layers and physical locations, enabling modularity and adaptability. This architecture ensures that each system component can operate on the most suitable computational resource, enhancing efficiency, reducing latency, and supporting scalable system operation.
By enabling dynamic orchestration and real‑time reconfiguration, MCCM provides a flexible infrastructure that supports near real‑time production optimization. The fog layer plays a critical role in enabling low‑latency data processing and rapid decision‑making, essential for responsive manufacturing systems.
Furthermore, MCCM supports third‑party application deployment in an Infrastructure‑as‑a‑Service (IaaS) model using containerization technologies such as Docker and Kubernetes. This approach not only enhances scalability and flexibility but also allows for real‑time system updates and adjustments without production downtime. To maintain system integrity and continuity, MCCM incorporates version control and traceability mechanisms, allowing manufacturers to roll back or update services and algorithms as needed—ensuring both operational stability and adaptability.
Implementation in MODUL4R Use Cases
The MCCM has been successfully deployed across MODUL4R’s pilot cases, demonstrating its versatility and impact:
FFT Use Case: The Quality Check station transmits capacitor inspection data via MQTT to the fog layer, where it is processed and forwarded to the cloud for analytics.
SSF Use Case: A soldering production system uses the MCCM to synchronize data from multiple stations, ensuring real‑time quality monitoring and control.
EMO Use Case: A CNC milling machine streams sensor data through MCCM to the cloud for predictive maintenance analytics.
NECO Use Case: MCCM orchestrates robotic arm coordination and metrology data.
Benefits for the Industry
The MCCM delivers transformative advantages for manufacturers:
Reduced Latency: Fog computing minimizes delays for critical decision‑making.
Scalability: Containerized services allow easy expansion to meet production needs.
Interoperability: Standardized protocols such as MQTT ensure compatibility with legacy and modern systems.
Resilience: Dynamic reconfiguration enhances system robustness against disruptions.
Security: Frameworks and tools such as cloud‑message‑brokers (Kafka, MQTT) and GAIA‑X policies ensure secure data management & distribution, all the way from edge sensors to cloud services
Conclusions
The MCCM delivers transformative advantages for manufacturers, by improving responsiveness, scalability, interoperability, and robustness in production systems. Using fog computing, MCCM minimizes latency through localized data processing, allowing for quicker, real time decision‑making.
Its support for containerized services enables rapid reconfiguration and seamless deployment, making it simple to grow operations as needed. Standardised protocols such as MQTT and REST‑APIs enable interoperability with both legacy and modern systems, whereas dynamic reconfiguration capabilities improve system resiliency, allowing operations to respond easily to disturbances or changing production requirements.
