An IIoT Architecture for an Industrial Plant: Case Study of the Learning Factory of an Industrial Engineering Laboratory

Industry 4.0 has driven digital transformation in industrial environments by integrating technologies like the Industrial Internet of Things (IIoT), enabling process automation, product traceability, and data-driven decision-making. However, its adoption in small and medium-sized enterprises (SMEs) and educational contexts is limited by challenges such as a lack of interoperability between systems, budget constraints, and insufficient technological infrastructure. This situation highlights the need for accessible, replicable, and technically feasible solutions for resource-constrained environments. In response to this issue, an IIoT architecture was developed and applied to a didactic industrial plant in a university Industrial Engineering laboratory. The solution integrates sensors and actuators, including Near-Field Communication (NFC) for traceability, with Fischertechnik TXT 1.0 controllers, an Enterprise Resource Planning (ERP) system –specifically, Odoo v18–, an Odoo broker, and a visualization platform based on Node-RED, all connected through the Message Queuing Telemetry Transport (MQTT) protocol. This architecture was experimentally validated as a technically viable and replicable model for automation and traceability in educational environments related to logistics and manufacturing processes within the framework of Industry 4.0.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.02.247
Primary Topic
Digital Transformation in Industry
Type
article
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article

An IIoT Architecture for an Industrial Plant: Case Study of the Learning Factory of an Industrial Engineering Laboratory

Eugenio Tamura, Hader Alberto Madera-Bermeo, Juan Sebastián Parrado-Muñoz
Procedia Computer Science
Digital Transformation in Industry
article

An IIoT Architecture for an Industrial Plant: Case Study of the Learning Factory of an Industrial Engineering Laboratory

Eugenio Tamura, Hader Alberto Madera-Bermeo, Juan Sebastián Parrado-Muñoz
article en

Abstract

Industry 4.0 has driven digital transformation in industrial environments by integrating technologies like the Industrial Internet of Things (IIoT), enabling process automation, product traceability, and data-driven decision-making. However, its adoption in small and medium-sized enterprises (SMEs) and educational contexts is limited by challenges such as a lack of interoperability between systems, budget constraints, and insufficient technological infrastructure. This situation highlights the need for accessible, replicable, and technically feasible solutions for resource-constrained environments. In response to this issue, an IIoT architecture was developed and applied to a didactic industrial plant in a university Industrial Engineering laboratory. The solution integrates sensors and actuators, including Near-Field Communication (NFC) for traceability, with Fischertechnik TXT 1.0 controllers, an Enterprise Resource Planning (ERP) system –specifically, Odoo v18–, an Odoo broker, and a visualization platform based on Node-RED, all connected through the Message Queuing Telemetry Transport (MQTT) protocol. This architecture was experimentally validated as a technically viable and replicable model for automation and traceability in educational environments related to logistics and manufacturing processes within the framework of Industry 4.0.

Procedia Computer ScienceVol. 277
Pontificia Universidad Javeriana (CO)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Digital Transformation in Industry
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An IIoT Architecture for an Industrial Plant: Case Study of the Learning Factory of an Industrial Engineering Laboratory — Eugenio Tamura, Hader Alberto Madera-Bermeo, et al. · Procedia Computer Science (2026) | TGRS Research Map | TGRS