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AI functionalities in cobot-based manufacturing for performance improvement in quality control application

Moor Madis, Sarkans Martins, Kangru Tavo, Otto Tauno, Riives Juri

Journal of Machine Engineering

2024

Vol. 24, No. 2

44-55

Modern manufacturing faces vastly changing challenges. The current economic situation and technological developments in terms of Industry 4.0 (I4.0) and Industry 5.0 (I5.0) force enterprises to integrate new technologies for more efficient and higher-quality products. Artificial intelligence (AI) and Machine Learning (ML) are the technologies that make machines capable of making human-like decisions. In the long run, AI and ML can add a layer (functionality) to make IoT devices more interactive and user-friendly. These technologies are driven by data and ML uses different types of data for making decisions. Our research focuses on testing a cobot-based quality control (CBQC) system that uses smart fixture and machine vision (MV) to determine the cables inside products with similar designs, but different functionality. The products are IoT modules for small electric vehicles used for interface, connectivity, and GPS monitoring. Previous research describes the methodology of reconfiguration of existing cobot cells for quality control purposes. In this paper, we discuss the testing of the CBQC system, together with creating a pattern database, training the ML model, and adding a predictive model to avoid defects in product cable sequence. Preliminary testing is carried out in the laboratory environment which leads to production testing in SME manufacturing. Results, developments, and future work will be presented at the end of the paper.

Digital Twin: industrial robot kinematic model integration to the virtual reality environment

Kuts Vladimir, Cherezova Natalia, Sarkans Martins, Otto Tauno

Journal of Machine Engineering

2020

Vol. 20, No. 2

53--64

Digital Twin (DT) concept nowadays is shown via the simulations of the manufacturing systems and included those production processes and parametric 3D models of the product. It is the primary method for planning, analysing and optimising the factory layout and processes. Moreover, work on management via the simulation in real-time is already done using Virtual Reality (VR) tools from a safe and remote environment. However, there is a list of limitation of such kind of digital systems, as connectivity speed and precision of the digital environment. The primary goal of this study is to access second listed limitation and on the example of the fully synchronised physical with its digital replica industrial robot, increase the level of precision of the developed DT environment. The proposed approach introduces transfer of the mathematical model to the virtual environment, thus creating a precise and scaled visual model of the Industrial Robot.