A case-study in the introduction of a digital twin in a large-scale smart manufacturing facility

In the field of industrial engineering the knowledge produced by newly obtained data is driving business forward. Automating the process of capturing data from industrial machines, analyzing it and using the knowledge gained to make better decisions for the machines is the crux of the digital twin. Sensor technology, Internet of Things platforms, information and communication technology and smart analytics allow the digital twin to transform a physical asset into a connected smart item that is now part of a cyber physical system and that is far more valuable than when it existed in isolation. The digital twin can be adopted by the maintenance engineering industry to aid in the prediction of issues before they occur thus creating value for the business. In this paper the authors look to introduce a maintenance digital twin to a large-scale manufacturing facility. Issues that hamper such work are discovered and categorized to highlight the difficulty of the practical installation of this concept. To aid in the installation process a digital twin framework is presented that simplifies the digital twin development process into steps that can be completed independently. With the framework in place the authors commence the task of completing these steps. (C) 2020 The Authors. Published by Elsevier Ltd.