Integration of Sensor Technology in Brownfield Applications

An industrial factory setting with large, rusted machinery prominently featured in the background. The warehouse has tall ceilings with overhead beams and large windows that allow ambient sunlight to filter in, creating a slightly hazy atmosphere. In the foreground, several worn, green machines with intricate gears and dials are arranged on a concrete floor. Surrounding them are transparent screens displaying digital icons and schematics, indicating advanced technology and data analysis features. An orange safety railing runs along the upper level of the factory, where additional machinery is partially visible. Dust particles can be seen in the light, enhancing the industrial ambiance.

Integration of Sensor Technology in Brownfield Applications

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Summary

This study presents a simple guide for integrating sensors into existing (brownfield) production for Industry 4.0, addressing interoperability, synchronization, response times, and environmental reliability. A Fraunhofer ILT use case—choosing a temperature sensor to control laser power in deposition welding—demonstrates the guide’s usefulness and its limits due to generalization. Because each project is unique, conflicting criteria often require an iterative process to reach technically and economically feasible solutions. A structured, sensor-specific approach can improve efficiency, and the guide could be implemented as a chatbot to support practical adoption.


Topic Fields	Sensor Systems
Published	2025
Involved Institutes	ILT
Project Type	ICNAP Community Study
Result Type	Report
Responsibles	Andrea Lanfermann

Description

This work defines a structured approach for integrating sensors into brownfield production systems to support Industry 4.0 use cases. Its purpose is to translate heterogeneous operational requirements into implementable sensor solutions while preserving real-time behavior, interoperability, and reliability in demanding environments. Core functionality includes requirements capture, criteria mapping, sensor and interface selection, feasibility analysis, iterative fit–gap resolution, deployment planning, and validation. The method can be operationalized as an edge-centric architecture with a conversational assistant that guides users through each phase.

The architecture is layered: sensors connect via existing fieldbuses or industrial Ethernet to PLCs or I/O modules; an edge gateway performs protocol translation and semantic enrichment; middleware exposes standardized interfaces to SCADA, MES, and analytics. Data flow begins with acquisition and hardware timestamping, followed by synchronization using IEEE 1588 PTP, filtering and calibration, quality tagging, buffering, and streaming via OPC UA or MQTT Sparkplug B to time-series storage and higher-level systems. Deterministic control loops remain on PLC/edge, while noncritical analytics may run on-premises or in the cloud.

Key technologies and standards include OPC UA (including Companion Specifications), MQTT Sparkplug B, Profinet/EtherCAT/Modbus-TCP, TSN where available, Asset Administration Shell and RAMI 4.0 for semantics, ISA‑95 for hierarchy mapping, and IEC/ISA 62443 for security. Deployment favors containerized edge services (e.g., Docker or K3s) with optional cloud extensions. Target users are OT engineers, controls engineers, maintenance, and data engineers.

Performance considerations focus on bounded latency, low jitter, and local failover; security encompasses network segmentation, DMZs, certificate-based authentication, TLS, and role-based access. Notable constraints include legacy device limitations, environmental robustness, budget trade-offs, and interdependent criteria that may be infeasible in combination, requiring iterative convergence. The approach scales by adding sensor adapters, topics, and assets, and horizontally scaling brokers and time-series databases. External integrations cover MES, ERP, CMMS, and SCADA via REST, OPC UA, or message buses. A Fraunhofer ILT use case—temperature sensing for laser power control—validated the method and highlighted its iterative nature.

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