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Applied Sciences
Volume 15
Issue 17
10.3390/app15179375
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Smart Manufacturing Workflow for Fuse Box Assembly and Validation: A Combined IoT, CAD, and Machine Vision Approach

by
Carmen-Cristiana Cazacu
1,*,
Teodor Cristian Nasu
2,
Mihail Hanga
2,
Dragos-Alexandru Cazacu
3 and
Costel Emil Cotet
1
1
Robots and Production Systems Department, The Faculty of Industrial Engineering and Robotics, National University of Science and Technology POLITEHNICA Bucharest, Splaiul Independenței 313, 060041 Bucharest, Romania
2
Department of Machine Construction Technology, The Faculty of Industrial Engineering and Robotics, National University of Science and Technology POLITEHNICA Bucharest, Splaiul Independenței 313, 060041 Bucharest, Romania
3
Education Team, PTC Eastern Europe SRL, Splaiul Independenței 319, 060044 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(17), 9375; https://doi.org/10.3390/app15179375
Submission received: 2 July 2025 / Revised: 13 August 2025 / Accepted: 24 August 2025 / Published: 26 August 2025
Versions Notes

Abstract

This paper presents an integrated workflow for smart manufacturing, combining CAD modeling, Digital Twin synchronization, and automated visual inspection to detect defective fuses in industrial electrical panels. The proposed system connects Onshape CAD models with a collaborative robot via the ThingWorx IoT platform and leverages computer vision with HSV color segmentation for real-time fuse validation. A custom ROI-based calibration method is implemented to address visual variation across fuse types, and a 5-s time-window validation improves detection robustness under fluctuating conditions. The system achieves a 95% accuracy rate across two fuse box types, with confidence intervals reported for statistical significance. Experimental findings indicate an approximate 85% decrease in manual intervention duration. Because of its adaptability and extensibility, the design can be implemented in a variety of assembly processes and provides a foundation for smart factory systems that are more scalable and independent.
Keywords: smart manufacturing; digital twin; IoT integration; computer vision; CAD-IoT Interoperability smart manufacturing; digital twin; IoT integration; computer vision; CAD-IoT Interoperability

Share and Cite

MDPI and ACS Style

Cazacu, C.-C.; Nasu, T.C.; Hanga, M.; Cazacu, D.-A.; Cotet, C.E. Smart Manufacturing Workflow for Fuse Box Assembly and Validation: A Combined IoT, CAD, and Machine Vision Approach. Appl. Sci. 2025, 15, 9375. https://doi.org/10.3390/app15179375

AMA Style

Cazacu C-C, Nasu TC, Hanga M, Cazacu D-A, Cotet CE. Smart Manufacturing Workflow for Fuse Box Assembly and Validation: A Combined IoT, CAD, and Machine Vision Approach. Applied Sciences. 2025; 15(17):9375. https://doi.org/10.3390/app15179375

Chicago/Turabian Style

Cazacu, Carmen-Cristiana, Teodor Cristian Nasu, Mihail Hanga, Dragos-Alexandru Cazacu, and Costel Emil Cotet. 2025. "Smart Manufacturing Workflow for Fuse Box Assembly and Validation: A Combined IoT, CAD, and Machine Vision Approach" Applied Sciences 15, no. 17: 9375. https://doi.org/10.3390/app15179375

APA Style

Cazacu, C.-C., Nasu, T. C., Hanga, M., Cazacu, D.-A., & Cotet, C. E. (2025). Smart Manufacturing Workflow for Fuse Box Assembly and Validation: A Combined IoT, CAD, and Machine Vision Approach. Applied Sciences, 15(17), 9375. https://doi.org/10.3390/app15179375

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