Turck at MODEX 2026: Decentralized Automation, IO-Link and Edge Control Systems

Decentralized Industrial Automation and the Shift Beyond the Control Cabinet

Industrial automation is moving away from centralized control architectures. At MODEX 2026, Turck demonstrated a decentralized model where intelligence is distributed closer to field devices rather than concentrated in control cabinets.

This shift improves system responsiveness and reduces commissioning complexity. It also aligns with modern factory automation strategies where edge-level decision making complements PLC and DCS coordination layers.

In many implementations, decentralized architectures still communicate with core systems such as Siemens PLC platforms, but execution logic is increasingly pushed to field devices.

Decentralized MDR Control in Conveyor Systems

Traditional conveyor automation relies on centralized motor control centers. This introduces long wiring runs and slower response times during cyclic motion tasks.

Turck’s motor-driven roller (MDR) solution shifts control directly into IP67-rated field modules. These modules integrate I/O, motor control, and sensing functions in a single decentralized unit.

This architecture improves response time for conveyor synchronization. However, engineers must carefully evaluate thermal load distribution and network latency in high-throughput environments.

Decentralized MDR control reduces cabinet wiring complexity and improves real-time conveyor response behavior.

Platforms such as Turck Automation Suite (TAS) allow engineers to configure and monitor field devices without extensive rewiring, reducing commissioning time in large-scale logistics systems.

Multiprotocol Communication in Industrial Networks

Modern automation environments rarely operate on a single communication protocol. Facilities often mix PROFINET, EtherCAT, Modbus, and IO-Link systems within the same production line.

Turck addressed this fragmentation through multiprotocol I/O blocks that adapt to different network standards. This simplifies integration across heterogeneous automation systems.

In distributed control environments, similar communication strategies are widely used in industrial networking architectures, where interoperability defines system scalability.

Multiprotocol IO-Link systems simplify integration across mixed industrial communication standards.

From an engineering perspective, this reduces gateway dependency. However, it also requires disciplined network segmentation to avoid latency conflicts in high-density sensor networks.

RFID-Based Inventory Intelligence Systems

Accurate inventory tracking is essential for modern logistics automation. Without reliable identification systems, even advanced robotic systems lose operational efficiency.

Turck demonstrated UHF RFID systems capable of reading multiple tags simultaneously without line-of-sight constraints. This significantly improves tracking reliability in fast-moving warehouse environments.

These systems are often integrated with automation platforms such as industrial sensing and detection systems, where real-time data supports warehouse execution logic.

RFID systems enable non-line-of-sight tracking for high-speed logistics operations.

In mobile automation demonstrations, RFID and optical tracking were combined to synchronize product flow between autonomous transport systems and warehouse management software.

Engineering Perspective: The Value of Decentralization

Decentralized automation improves scalability and reduces wiring complexity. However, it introduces new engineering challenges related to system diagnostics and distributed fault handling.

Engineers must now evaluate system performance across multiple layers, including field devices, communication networks, and supervisory control systems.

This architecture works best when paired with structured control hierarchies such as PLC-based coordination systems and standardized industrial communication protocols.

Author Insight

“Decentralization does not remove control complexity; it redistributes it. The real engineering challenge is maintaining deterministic behavior across distributed field intelligence systems.”

— Michael Brown, Industrial Automation Engineer (experience in PLC modernization, IO-Link integration, and warehouse automation systems using ABB and Siemens platforms)