Volume 21, Issue 1, 2026/Journal Proceedings in Manufacturing Systems

¹⁾ Assoc. Prof. PhD, Eng. Department of Robotized and Mechatronics Intelligent Systems, Institute of Robotics - Bulgarian Academy of Sciences, Sofia, Bulgaria

²⁾ MSc., Eng., Department of Communication and Computer Systems, Institute of Information and Communication Technologies – Bulgarian Academy of Sciences, Sofia, Bulgaria

https://doi.org/10.5281/zenodo.21809043

Abstract: Robotics is an interdisciplinary scientific field that integrates mechanics, electronics, sensing technologies, control systems, biomedical engineering, and software solutions. Due to its significant advantages, robotics has found extensive applications in medicine, particularly in surgical practice. Digital Twins are virtual, dynamic representations of real physical objects or processes that are continuously updated using real-time data or simulation-based parameters. This paper investigates the role of digital twins in engineering, robotics, and surgical robotics. A digital twin-based architecture for a surgical system is proposed. Furthermore, simulation scenarios based on digital twins for surgical robotics are analyzed. A Use Case Diagram of digital twin-assisted surgical interaction is also presented, illustrating the relationship between the surgeon, the digital twin modeling module, and patient-related surgical actions. The main objective of this study is to demonstrate the application of digital twins in surgical robotics for enhancing simulation realism, enabling the development of personalized training protocols, and improving the efficiency of healthcare delivery through virtual testing of surgical scenarios prior to real clinical procedures, ultimately leading to improved patient outcomes.

Key words: Digital Twins, Robotics, Surgical robots, Training, Simulating, Real-Time Data, Virtual Models.

pp. 09-16 View full text

Development of α two-material robotic gripper with variable compliance using additive manufacturing

Nefeli ANDREOPOULOU¹ and George-Christopher VOSNIAKOS^2,*l

¹⁾ MSc Graduate Student, School of Mechanical Engineering, National Technical University of Athens, Athens, Greece

²⁾ Prof., Manufacturing Technology Laboratory, School of Mechanical Engineering, National Technical University of Athens, Athens, Greece

https://doi.org/10.5281/zenodo.21821559

Abstract: A two-material soft robotic gripper based on the Fin Ray Effect is presented. The gripper was developed to combine the shape adaptability of compliant fingers with the structural reliability required for repeated pick-and-place tasks. The design uses thermoplastic polyurethane (TPU) for the deformable finger frame and joints and polylactic acid (PLA) for the crossbeams that guide deformation. A sliding male-female joint was introduced to allow assembly and disassembly without screws or adhesive while maintaining controlled rotational freedom. The gripper is actuated by a lead-screw mechanism that transforms rotation into linear motion and closes (or opens) the two fingers around the object. CAD-based kinematic checks, finite-element simulations for finger deformation checks and prototype tests were used to evaluate the design. The models confirmed the ability of the gripper to handle cylindrical objects up to 60 mm in diameter, weighing up to 400 g, with a maximum targeted gripping force of 8 N. The prototype was fabricated by material-extrusion Additive Manufacturing and was tested with objects of different hardness, mass, shape and sensitivity. The results show that a low-cost, modular two-material Fin Ray gripper can provide practical adaptive grasping while being easy to customize and manufacture.

Key words: soft robotics, Fin Ray Effect, additive manufacturing, multi-material gripper; TPU, PLA, finite element analysis.

pp. 17-34 View full text

From 2D drawings to 3D solids in FreeCAD: an LLM-based pilot study on performance and prompting strategie

Diana POPESCU^1,*l, Robert IACOB²

¹⁾ Prof., PhD, Robots and Manufacturing Systems Dep., National University of Science and Technology POLITEHNICA Bucharest, Romania

²⁾ Lecturer, PhD), Robots and Manufacturing Systems Dep., National University of Science and Technology POLITEHNICA Bucharest, Romania

https://doi.org/10.5281/zenodo.21818956

Abstract: The paper presents a pilot study investigating how prompting strategies affect a multimodal large language model (LLM) 's ability to interpret dimensioned 2D technical drawings and generate executable FreeCAD Python scripts for direct 3D solid reconstruction. The test set included nine prismatic mechanical parts with different geometrical features and difficulty levels to evaluate the interpretation of orthographic views and sections, positioning of holes, difference between through, blind, and counterbore holes, reconstruction of pockets, slots, cut-outs, inclined faces, and local edge features, as well as the valid and correct generation of subsequent 3D solids. Two prompting strategies were tested for each part: a simple prompt with minimal constraints and a moderately structured prompt with general rules for multi-view interpretation, feature separation and modelling order. The evaluation considered script execution, valid solid generation, structural and dimensional correctness, and run-to-run stability. Three runs were conducted for each independent prompt-part configuration. The results showed that, for both prompts, the generated scripts were all executed successfully, producing valid FreeCAD solids. The minimal prompt generated 5/9 fully correct parts (55.6%), whereas the moderately structured prompt generated 6/9 fully correct parts (66.7%). All low-complexity parts were reconstructed correctly with both prompts, the structured prompt producing a small improvement in the results for medium-complexity parts. None of the complex parts was correctly reconstructed. These results indicate that the main limitation is not FreeCAD script generation by the LLM, but the interpretation of complex 2D drawings into a correct 3D feature structure.

Key words: 2D drawings, CAD, Large Language Models, FreeCAD, prompting strategies.

pp. 35-41 View full text

Structured text and industrial Internet of Things convergence for smart manufacturing

Roxana Florina BOANDĂ^1,*l, Aurel FRATU²l

¹⁾ PhD, Student, Department of Automation and Information Technology, Transilvania University of Brașov, Brașov, Romania

²⁾ Prof. Dr. Habil. Eng., Full Professor, Department of Automation and Information Technology, Transilvania University of Brașov, Brașov, Romania

https://doi.org/10.5281/zenodo.21823766

Abstract: In the current context, where the concept of Industry 4.0 is gaining momentum, the separation between operational control (OT) and information technology (IT) is becoming decreasingly visible in the automation industry. This paper will explore the compatibility between one of the programming languages of programmable logic controllers (PLC), namely Structured Text (ST), and Industrial Internet of Things (IIoT) ecosystems to improve production and the transition to intelligent processing (Smart Manufacturing). While traditional PLCs were designed as isolated systems, this study proposes a hybrid architecture in which deterministic control logic is augmented with Edge Intelligence capabilities and asynchronous communication via OPC UA. Exploring the modernization of industrial architecture achieved by introducing Digital Twin inside of PLC code, the proposed solution will integrate this through the implementation made with Structured Text. The method involves filtering data from the physical field directly at the source, by implementing the logic for processing and selecting information from controllers and not at the Cloud level, so that redundant information is not transmitted. It is desired that this implementation will reduce data traffic and decrease network latency, but without compromising the accuracy of monitoring or the integrity of the industrial process. Finally, the study substantiates the concept of a resilient factory. By establishing bidirectional and coherent data flows between the Cloud and the PLC, the systems become capable of self-optimization in real time.

Key words: Structured Text, IIoT, Smart Manufacturing, PLC, Edge Computing.

pp. 43-55 View full text

A review of the current state of research in quality assurance in the nuclear industry

Senis HAGIMEMET¹, George CONSTANTIN^2,*l

¹⁾ PhD Student, National University of Science and Technology POLITEHNICA Bucharest, Romania

²⁾ Prof., PhD, Robots and Manufacturing Systems Department, National University of Science and Technology POLITEHNICA Bucharest, Romania

https://doi.org/10.5281/zenodo.21824003

Abstract: This paper reviews quality assurance and supplier evaluation in the nuclear industry, with particular attention to the shift from traditional audit-based approaches toward technology-enabled methods. Drawing on the literature, it examines how artificial intelligence, digital twins, blockchain, and the Industrial Internet of Things (IIoT) may improve traceability, automation, and predictive analytics. The review indicates that current practice remains limited by fragmented implementation, the absence of integrated frameworks, and barriers to adoption within stringent regulatory environments. In response, the paper identifies priorities for future research, including risk-based supplier assessment, integration of digital technologies, and the development of unified evaluation models. It also introduces 3D-Q (Data-Driven, Defense-in-Depth Quality) as a proposed framework for moving quality assurance from reactive defect detection toward proactive defect prevention through real-time monitoring, predictive analytics, and enhanced traceability. Overall, the review suggests that more integrated and interdisciplinary approaches are needed to improve efficiency, reduce risk, and strengthen the safety and reliability of nuclear supply chains.

Key words: Nuclear industry, Quality assurance, Supplier evaluation, Risk management, Artificial intelligence, Digital Twin, Blockchain, IIoT, Traceability, Predictive analytics, Supply chain.

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