Digital Twin for Smart Factory Network QoS Enhancement Experiments

Abstract

Smart factories of Industry 4.0 have challenging network layer requirements. Any changes in the network elements or topology of a smart factory can cause deterioration of the Quality of Service (QoS). Experimentation on the design changes in the network causes disruption of the smart factory operation. In this paper, the concept of digital twin is applied for conducting QoS enhancement experiments of a smart factory network without disrupting the regular process of monitoring and management of the factory. The “digital twin” is a key concept involving digital replication or representation of physical machines, processes, people in cyber-space. Existing work on digital twin for smart factories focuses on modeling a factory, with its physical space, the various robots at work, the manufacturing processes, etc. Primary contribution of this paper is a novel digital twin architecture using NetSim—the network simulator in conjunction with Node-RED, a programming tool and a real-time database consisting of the current sensor data from the physical objects. This paper also describes a QoS enhancement experimental setup for real-time monitoring of induction motor health, using the proposed architecture, with results showing the visualization of latency and jitter of sensor data object monitored by a client across the network using 100 Ethernet and 1 Gbps Ethernet.