A Solution Architecture for Energy Monitoring and Visualisation in Smart Factories with Robotic Automation

Abstract

In today's manufacturing landscape, digital twin-enabled smart factories are revolutionising traditional practises by leveraging cutting-edge technologies such as Internet of Things (IoT) devices, advanced analytics, machine learning, and artificial intelligence (AI). These factories create virtual replicas, or digital twins, of their physical counterparts, enabling real-time monitoring, analysis, and control of manufacturing operations. One area of innovation within smart factories is the role of energy condition monitoring and data analytics, which has gained significant attention due to the challenges of interoperability in industrial environments and the emerging need for sustainable manufacturing systems. This paper proposes an energy monitoring and visualisation solution architecture and example data visualisation dashboards at multiple user levels. The proposed solution architecture is deployed on a case study that included robotic material handling, and the results showed that the proposed solution can provide valuable insights to the users regarding the energy consumption of shop-floor components and provide a cost-efficient solution for energy analytics that can be used within SMEs.