ANALIZA I PRIMENA OPC UA ZA DIGITALNU TRANSFORMACIJU MAŠINE ZA BRIZGANJE PLASTIKE

Milica Milić

doi:10.24867/34BE08Milic

Electrotechnical and Computer Engineering

Vol. 41 No. 02 (2026): Proceedings of the Faculty of Technical Sciences

ANALYSIS AND IMPLEMENTATION OF OPC UA IN THE DIGITAL TRANSFORMATION OF AN INJECTION MOLDING MACHINE

Milica Milić

34BE08Milic.pdf (Serbian)

DOI:: https://doi.org/10.24867/34BE08Milic
Submitted: February 12, 2026
Published: 2026-03-09

Abstract

This work addresses the application of the OPC UA specification in the plastic processing industry, aiming to implement a production facility in accordance with Industry 4.0 principles. The scope of the paper includes the configuration of the OPC UA Server using the EUROMAP 77 information model, as well as the evaluation of OPC UA security aspects on the example of an injection molding machine. The key advantages of OPC UA compared to traditional production plant implementations are presented.

References

[1] M. Schleipen, H. S. Gilani, T. Bischoff, and J. Pfrommer, ‘OPC UA & Industrie 4.0 - Enabling Technology with High Diversity and Variability’, Procedia CIRP, vol. 57, pp. 315–320, 12 2016.
[2] A. Martins, B. M. L. Silva, H. Costelha, C. Neves, J. Lyons, and J. Cosgrove, ‘An approach to integrating manufacturing data from legacy Injection Moulding Machines using OPC UA’, 09 2021.
[3] F. Tayalati, I. Boukrouh, A. Azmani, and M. Azmani, ‘Implementation of Digital Twin and Deep Learning for Process Monitoring: Case Study in Injection Molding Manufacturing’, 08 2024, p. 8.
[4] M. R. Ristanović, ‘Arhitektura sistema industrijske automatike’, Mašinski fakultet Univerziteta u Beogradu, 2020, p. 3–4.
[5] O. Antons, J. C. Arlinghaus, ‘Distributed control for industry 4.0 - a comparative simulation study’, IFAC-PapersOnLine 54 (1) (2021) 516–521, 17th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2021.

[1] [1] M. Schleipen, H. S. Gilani, T. Bischoff, and J. Pfrommer, ‘OPC UA & Industrie 4.0 - Enabling Technology with High Diversity and Variability’, Procedia CIRP, vol. 57, pp. 315–320, 12 2016.

[2] [2] A. Martins, B. M. L. Silva, H. Costelha, C. Neves, J. Lyons, and J. Cosgrove, ‘An approach to integrating manufacturing data from legacy Injection Moulding Machines using OPC UA’, 09 2021.

[3] [3] F. Tayalati, I. Boukrouh, A. Azmani, and M. Azmani, ‘Implementation of Digital Twin and Deep Learning for Process Monitoring: Case Study in Injection Molding Manufacturing’, 08 2024, p. 8.

[4] [4] M. R. Ristanović, ‘Arhitektura sistema industrijske automatike’, Mašinski fakultet Univerziteta u Beogradu, 2020, p. 3–4.

[5] [5] O. Antons, J. C. Arlinghaus, ‘Distributed control for industry 4.0 - a comparative simulation study’, IFAC-PapersOnLine 54 (1) (2021) 516–521, 17th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2021.