Digital Twin framework for material handling and logistics in Manufacturing: Part 1

Abstract

A Digital twin for the Automated Guided Vehicles (AGVs), Collaborative Robots (COBOTs), and other material handling systems will improve the logistical efficiency in manufacturing. To design the characteristic features of AGVs and the charging stations required (for a given number of pick-up and delivery nodes), a digital twin will be critical to simulate and obtain the information. A digital twin for a fleet of AGVs can dynamically update the system in the virtual platform along with its Physical counterpart. However, it demands modularity, accuracy, localization, and a layered framework of Internet of Things (IoT) nodes in the Industrial Internet of Things (IIoT) platform. In this article, the aim is to design and develop a digital twin framework for a fleet of AGVs providing modularity and concurrent processing capability. The concurrency and real-time computation are validated using machine vision. The performance and optimal usage of the AGVs are also simulated before deployment.