Patrik Vlašić
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Patrik Vlašić has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Hrvoje Cajner
Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lucica 5, 10000 Zagreb, Croatia
1 shared publication - Ložar Viktor
Department of Industrial Engineering, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lucica 5, 10000 Zagreb, Croatia
1 shared publication - Maja Trstenjak
Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, Croatia
1 shared publication - Matija Golec
Department of Industrial Engineering, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lucica 5, 10000 Zagreb, Croatia
1 shared publication
Latest Publications
- Open Access
- 19 March 2026
- Published by MDPI AG in Applied Sciences
- Vol. 16 (6) , 2974
Robotic Welding Technologies for Intersecting and Irregular Pipes and Pipe Joints Toward Automated Production Line Integration: A Review
Robotic pipe welding represents a key and rapidly evolving technology for the automation of pipe and pipe-joint welding processes with standard, intersecting, and complex geometries. This review analyses 84 studies published over the past three decades, categorising them into four primary research areas: general pipe welding, intersecting pipes, boiler and tube-to-tubesheet welding, and control and modelling. Two separate comparative analyses were conducted: one within intersecting pipe research and another within the control and modelling category. The aggregated findings reveal consistent, complementary patterns: simulation and laboratory experiments clearly dominate validation methods, while industrial-scale evaluations remain scarce. The results further demonstrate that control strategies, sensor integration, and validation levels are strongly interconnected, collectively determining system performance, reliability, and practical applicability. Despite significant progress, challenges remain, including system integration complexity, limited robustness in variable industrial environments, insufficient real-time adaptive control, and inconsistent quantitative performance evaluation. Further research should prioritise the development of digital twins, human–robot collaboration, multi-sensor fusion, reinforcement learning-based adaptive control, and scalable industrial deployment. This review provides an overview of current progress and outlines key directions for developing intelligent and reliable robotic pipe welding systems.
- 19 March 2026
- Published by MDPI AG in Applied Sciences
- Vol. 16 (6) , 2974
Open AccessRobotic Welding Technologies for Intersecting and Irregular Pipes and Pipe Joints Toward Automated Production Line Integration: A Review
Robotic pipe welding represents a key and rapidly evolving technology for the automation of pipe and pipe-joint welding processes with standard, intersecting, and complex geometries. This review analyses 84 studies published over the past three decades, categorising them into four primary research areas: general pipe welding, intersecting pipes, boiler and tube-to-tubesheet welding, and control and modelling. Two separate comparative analyses were conducted: one within intersecting pipe research and another within the control and modelling category. The aggregated findings reveal consistent, complementary patterns: simulation and laboratory experiments clearly dominate validation methods, while industrial-scale evaluations remain scarce. The results further demonstrate that control strategies, sensor integration, and validation levels are strongly interconnected, collectively determining system performance, reliability, and practical applicability. Despite significant progress, challenges remain, including system integration complexity, limited robustness in variable industrial environments, insufficient real-time adaptive control, and inconsistent quantitative performance evaluation. Further research should prioritise the development of digital twins, human–robot collaboration, multi-sensor fusion, reinforcement learning-based adaptive control, and scalable industrial deployment. This review provides an overview of current progress and outlines key directions for developing intelligent and reliable robotic pipe welding systems.