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Open AccessArticle
Implementation of an Industry 4.0 Smart Factory: IT/OT Network Integration, MES-Based Control, and Offline Production Optimization Using Discrete Event Simulation
by
Hisham ElMoaqet
Hisham ElMoaqet *
and
Yazan Eltobgy
Yazan Eltobgy *
Department of Mechatronics Engineering, German Jordanian University, Amman 11180, Jordan
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2026, 16(18), 9356; https://doi.org/10.3390/app16189356 (registering DOI)
Submission received: 10 August 2026
/
Revised: 15 September 2026
/
Accepted: 17 September 2026
/
Published: 20 September 2026
Abstract
Connecting IT and OT in manufacturing has become a core requirement for realizing Industry 4.0 smart factory architectures. This paper reports on the implementation of a smart factory built on the Festo CP Factory platform, covering three main contributions: IT/OT network architecture, MES-driven production control, and offline production optimization using Discrete Event Simulation (DES). The system comprises four stations—an Automatic Storage and Retrieval System (ASRS), a Robot Assembly Station (RASS) with a Mitsubishi RV-4FRL six-axis robot, a Magazine Station, and a Muscle Press—linked through a LINEAR conveyor network. A layered communication stack was deployed: PROFINET at the field level, OPC-UA for MES4 connectivity, and MQTT via Node-RED for IoT monitoring. An offline DES model was built in Siemens Siemens Tecnomatix Plant Simulation Environment (version 2302; Siemens Digital Industries Software, Munich, Germany) to study how carrier count affects throughput and station utilization across three carrier configurations. Station processing times were taken directly from the physical line: 86 s for Robot Assembly, 15 s for ASRS, 4 s for Magazine, and 6 s for Muscle Press. The Robot Assembly Station reaches near-full utilization (94.49%, event-based) at three carriers, confirming it as the system bottleneck. Two carriers offer the most practical operating point, delivering 35.8 pallets per hour while keeping the bottleneck station below full saturation. Fuse count also affects cycle time. Zero-fuse assemblies complete production up to 9.3% faster than two-fuse runs due to the shorter Robot Assembly cycle. Testing on the physical CP Factory to validate the developed simulation model covered 27 configurations combining three carrier counts, three batch sizes, and three fuse levels, with simulation errors ranging from 2.9% to 10.0%. The mean error stays close to commonly cited manufacturing DES validation thresholds at low carrier counts, reaching 4.78% at one carrier. It rises at higher carrier counts, reaching 8.64% at three carriers. This progression is consistent with carrier-queuing effects that intensify with carrier count. The results confirm that complete Industry 4.0 implementation is achievable on a modular CP Factory platform and provide a practical reference for similar deployments.
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MDPI and ACS Style
ElMoaqet, H.; Eltobgy, Y.
Implementation of an Industry 4.0 Smart Factory: IT/OT Network Integration, MES-Based Control, and Offline Production Optimization Using Discrete Event Simulation. Appl. Sci. 2026, 16, 9356.
https://doi.org/10.3390/app16189356
AMA Style
ElMoaqet H, Eltobgy Y.
Implementation of an Industry 4.0 Smart Factory: IT/OT Network Integration, MES-Based Control, and Offline Production Optimization Using Discrete Event Simulation. Applied Sciences. 2026; 16(18):9356.
https://doi.org/10.3390/app16189356
Chicago/Turabian Style
ElMoaqet, Hisham, and Yazan Eltobgy.
2026. "Implementation of an Industry 4.0 Smart Factory: IT/OT Network Integration, MES-Based Control, and Offline Production Optimization Using Discrete Event Simulation" Applied Sciences 16, no. 18: 9356.
https://doi.org/10.3390/app16189356
APA Style
ElMoaqet, H., & Eltobgy, Y.
(2026). Implementation of an Industry 4.0 Smart Factory: IT/OT Network Integration, MES-Based Control, and Offline Production Optimization Using Discrete Event Simulation. Applied Sciences, 16(18), 9356.
https://doi.org/10.3390/app16189356
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