An Innovative Software Interface Solution for Industrial Aplication of Machine Vision on a Smart Assembly/Disassembly Mechatronic Line

• Published in: The scientific bulletin of Electrical Engineering Faculty Vol. 25; no. 1; pp. 20 - 27
• Main Authors: Păun, Marius-Adrian, Mincă, Eugenia, Duca, Octavian, Gurgu, Valentin, Iliescu, Sergiu Stelian
• Format: Journal Article
• Language: English
• Published: Targoviste Sciendo 01.06.2025; De Gruyter Poland
• Subjects: Industry 4.0; Industry 5.0; Machine Vision; Quality Test Management System; SMART Assembly / Disassembly; Vision systems
• Online Access: Get full text
• ISSN: 2286-2455; 1843-6188; 2286-2455
• DOI: 10.2478/sbeef-2025-0004

This paper presents a revolutionary approach to image analysis, specific to quality testing (QT) processes performed in industrial manufacturing processes, which integrates specific concepts of Industry 4.0 and Industry 5.0. The results of the research were translated into an innovative software interface, finally customized for testing the manufacturing quality on the mechatronic assembly and disassembly lines. The QT control structure, subordinated to the new technologies of Industry 4.0 and Industry 5.0, proposes that the acquisition sequences, analysis, decision -making and historical recording of quality data, be implemented through a server application (SA) and remotely through client applications (CA). Additionally, the system’s hardware configuration and embedded software components function analogously to an Internet of Things (IoT) sensor, providing a framework for real-time process analysis and control. The QT system is structured as a Machine Vision (MV) framework, leveraging advanced image processing techniques to extract relevant information, thereby enhancing the reliability and detail of quality assessments. In this setup, the mechatronic line is seamlessly integrated with cutting-edge analytical and control functionalities, enabling robust production monitoring and remote-control capabilities through the SA. Concurrently, the CA software offers enhanced flexibility for customizing production orders in response to customer demands. Following the implementation of this MV-based control structure, which utilizes the developed software interface for image analysis, a series of performance tests were conducted to validate system efficacy and adaptability within an automated production environment.