# Dynamic Scheduling Optimization of Production Workshops Based on Digital Twin
## 2 The Construction of a High-Quality Virtual Workshop
### Workshop Scene Information Acquisition  
The location layout and pipe schematics that accurately depict the actual equipment may be missing or incorrect due to the ongoing iteration and updating of the workshop's equipment. As a result, we need to gather the real workshop setting to create a high-quality virtual workshop. In order to create a virtual workshop environment scene based on the scanning data, a 3D laser scanning system is used to collect information on the location, size, and workshop environment of the actual workshop.  
An optical remote sensing technology called 3D laser scanning actively catches a target's dispersed light to gather pertinent target data. By computing the distance from the device to the scene surface, the horizontal angle, and the vertical angle of the current surface position, it may determine the 3D coordinates of the scene surface points. The system gathers millions of points by continuously scanning the scene's surface, culminating in the formation of high-precision point cloud data.  
The 3D laser scanning system is separated into handheld portable and base station point types depending on the scale differences in the industrial environment. By holding the instrument in one hand, the handheld portable laser scanner scans the entire manufacturing environment. This technique is typically used for quick building of tiny manufacturing line scenarios, and its precision is typically 0.02 mm. Base station point scanners are more complicated to use than handheld scanners, but they can detect bigger spatial areas with a  
Figure 1: Flowchart of the workshop construction process.  
smaller degree of accuracy (2 mm/10 m). Base station scanners are frequently utilized to capture intricate, expansive workshop scenes. When scanning large scale shop floor scenes, it is essential to carefully organize the location of the scanning points due to the enormous amount of point cloud data produced by base station 3D scanners. The measurement points are limited, and the vital information of the scene must be kept as clear of ambient elements as possible while making the comprehensive acquisition of the important sections of the workshop scene. In order to stitch the scanned data at each point while scanning large-scale scenes, it is typically necessary to scan point cloud data at several scanning sites. Therefore, the spatial sceneries between adjacent scanned points are maintained with an overlap rate of 25-35% to simplify the post-processing of point cloud stitching. Additionally, by repeatedly scanning the environment modeling region, the point cloud density can be raised.  
In comparison to conventional mapping plus field measurement techniques, the utilization of 3D laser scanning in manufacturing shop floor environmental acquisition can significantly decrease staff work and boost efficiency. Additionally, the information obtained using 3D laser scanning is more accurate, comprehensive, and informative, and it keeps the geometric topological properties of feature information, resulting in a database that is accurate and trustworthy and can be used to recreate the environment of a shop floor.  
ReCap Pro 2022 from Autodesk, a US company, was used in this study to process the point cloud data that was received after scanning. ReCap is a reality capture and 3D scanning software for building models, and it supports the stitching operation of point cloud data from multiple scanned points, as well as cleaning, sorting, spatial sorting, compression, and measurement. The scanned point locations and stitching effect are shown in Figure 2. Five scanning spots were used to arrange the scene in the figure, then ReCap merged the five scanned data together. After the stitching is finished, the scanned data can be edited using a range of tools, including key location dimensioning, and input settings that affect the size and appearance of the point cloud can be changed. The final processed data is converted to point cloud format.