# Use of Data-Driven Simulation Modeling and Visual Computing Methods for Workplace Evaluation
## 3 Methods
### Visual Computing  
The method of visual computing was carried out with the aim of building a three-dimensional model of the workplace. In the described research problem, only the three-dimensional model was not sufficient, and it was also necessary to analyze the workplace regarding the real-world manufacturing process operations' processing times (recording the normative assembly time deviations) and the realistic number of finished products. The hardware used was a spherical Samsung Gear 360 camera mounted on the workstation, where it was used for three-dimensional model capturing of the workstation, and for continuous recording of the workstation manufacturing characteristics in three shifts in one working week (the individual worker was under the evaluation for one shift of eight hours). Figure 3 shows a real-world manufacturing workplace with manual product assembly and automated testing operations. During assembly, the worker always has access to individual components and the necessary tools. The workstation, with one worker, shown represents only half of the entire manual assembly process, as this workstation is mirrored on the \(y\)-axis, where the work is performed by another worker. Workers in the manual assembly workplace are adequately educated by the employer's internal training. No formal education prior knowledge is required. An investigation is presented of the appropriateness of workplace mirroring in relation to the ergonomic efficiency of the workplace. The presented visual computing method of recording a workplace with spherical camera lists two areas as results. The first area deals with the acquisition of a three-dimensional workplace model and the transfer of real-world dimensions into a simulation environment, shown in Figure 4. The second area deals with the manual evaluation of the recorded workplace parameters. In this case, presented approach does not deal with computer-aided evaluation and automatic parameter acquisition, but withmanual monitoring, time standardization and detailed evaluation of the manual assembly operation of a real-world manufacturing system.  
The workplace capture, which was performed with a low-cost spherical camera, was initially computed visually with Autodesk ReCap software, which allows the creation of a captured object point cloud, including the \(x,y\) and \(z\) positions. Given the literature [24] and the characteristics of the research problem, the accuracy of the point cloud capture is satisfactory. When comparing the real-world dimensions and the generated point cloud data, the deviation range was approximately 2 mm. In the case of a need for very accurate data, the low-cost spherical camera may not achieve the desired results. Based on the point cloud data, a mash structure was generated in Agisoft Metashape [25], on which the build texture was stretched, and together, they formed a three-dimensional model as shown in Figure 4. The workplace visually computed model shown in Figure 4 also contains data that was captured during the three shifts, a one work week assembly video recording process. During the continuous recording of the workplace and the operations' execution, the employees were aware of this and agreed to it. According to the average values of the operations' evaluation, it was found that the processing time of manual assembly operation is 30 s, and the processing time of the automated testing stage is 25.5 s. Based on the numerical values obtained by visual computing analysis, we can assume that the manual assembly operation is a bottleneck in the manufacturing process. The analysis of the additional video validation confirmed the initial problem of 8% of the insufficient quality of  
Figure 4: Three-dimensional model made from spherical camera data capturing.  
Figure 3: Real-world workplace under consideration.  
assembled products is present in manual assembly operations. This numerical result also relates to reducing the final number of properly manufactured products.