Automated generation of digital twin for a built environment using scan and object detection as input for production planning

Abstract

The simulation of production processes using a digital twin can be utilized for prospective planning, analysis of existing systems or process-parallel monitoring. In all cases, the digital twin offers manufacturing companies room for improvement in production and logistics processes leading to cost savings. However, many companies, especially small and medium-sized enterprises, do not apply the technology, because the generation of a digital twin in a built environment is cost-, time- and resource-intensive and IT expertise is required. These obstacles will be overcome by generating a digital twin using a scan of the shop floor and subsequent object recognition. This paper describes the approach with multiple steps, parameters, and data which must be acquired in order to generate a digital twin automatically. It is also shown how the data is processed to generate the digital twin and how object recognition is integrated into it. An overview of the entire process chain is given as well as results in an application case.