Filipescu Adrian, Simion Georgian, Ionescu Dan, Filipescu Adriana
Department of Automation, "Dunărea de Jos" University of Galați, 800008 Galați, Romania.
Doctoral School of Fundamental Sciences and Engineering, "Dunărea de Jos" University of Galați, 800008 Galați, Romania.
Sensors (Basel). 2024 Nov 22;24(23):7451. doi: 10.3390/s24237451.
The monitoring and control of an assembly/disassembly/replacement (A/D/R) multifunctional robotic cell (MRC) with the ABB 120 Industrial Robotic Manipulator (IRM), based on IoT (Internet of Things)-cloud, VPN (Virtual Private Network), and digital twin (DT) technology, are presented in this paper. The approach integrates modern principles of smart manufacturing as outlined in Industry/Education 4.0 (automation, data exchange, smart systems, machine learning, and predictive maintenance) and Industry/Education 5.0 (human-robot collaboration, customization, robustness, and sustainability). Artificial intelligence (AI), based on machine learning (ML), enhances system flexibility, productivity, and user-centered collaboration. Several IoT edge devices are engaged, connected to local networks, LAN-Profinet, and LAN-Ethernet and to the Internet via WAN-Ethernet and OPC-UA, for remote and local processing and data acquisition. The system is connected to the Internet via Wireless Area Network (WAN) and allows remote control via the cloud and VPN. IoT dashboards, as human-machine interfaces (HMIs), SCADA (Supervisory Control and Data Acquisition), and OPC-UA (Open Platform Communication-Unified Architecture), facilitate remote monitoring and control of the MRC, as well as the planning and management of A/D/R tasks. The assignment, planning, and execution of A/D/R tasks were carried out using an augmented reality (AR) tool. Synchronized timed Petri nets (STPN) were used as a digital twin akin to a virtual reality (VR) representation of A/D/R MRC operations. This integration of advanced technology into a laboratory mechatronic system, where the devices are organized in a decentralized, multilevel architecture, creates a smart, flexible, and scalable environment that caters to both industrial applications and educational frameworks.
本文介绍了基于物联网(IoT)云、虚拟专用网络(VPN)和数字孪生(DT)技术,使用ABB 120工业机器人操纵器(IRM)对装配/拆卸/更换(A/D/R)多功能机器人单元(MRC)进行的监控。该方法整合了工业/教育4.0(自动化、数据交换、智能系统、机器学习和预测性维护)以及工业/教育5.0(人机协作、定制化、鲁棒性和可持续性)中概述的智能制造现代原则。基于机器学习(ML)的人工智能(AI)提高了系统的灵活性、生产力以及以用户为中心的协作性。使用了多个物联网边缘设备,它们连接到本地网络、局域网 - Profinet和局域网 - 以太网,并通过广域网 - 以太网和OPC - UA连接到互联网,用于远程和本地处理及数据采集。该系统通过无线局域网(WAN)连接到互联网,并允许通过云及VPN进行远程控制。物联网仪表板作为人机界面(HMI)、监控与数据采集(SCADA)以及开放平台通信统一架构(OPC - UA),便于对MRC进行远程监控和控制,以及对A/D/R任务进行规划和管理。A/D/R任务的分配、规划和执行使用了增强现实(AR)工具。同步定时Petri网(STPN)被用作类似于A/D/R MRC操作的虚拟现实(VR)表示的数字孪生。这种将先进技术集成到实验室机电一体化系统中的方式,其中设备以分散的多级架构进行组织,创建了一个智能、灵活且可扩展的环境,适用于工业应用和教育框架。