# Use of Data-Driven Simulation Modeling and Visual Computing Methods for Workplace Evaluation
## 5 Discussion and Conclusions  
In the manuscript, we present a new innovative way of using visual computing methods and data-driven simulation models for the investigation of manufacturing capacities, costs, and ergonomic analyses of workplaces. The main aim is to evaluate workplaces in terms of faster, cheaper, and more ergonomic processes, which was presented with the proposed approaches. The presented use of the economically accessible spherical camera for capturing static images and video recordings enabled the construction of a detailed three-dimensional model of the workplace and the acquisition of real-world parameters' values captured directly from the manufacturing process. The static images used to construct the three-dimensional model were supplemented by video data concerning realistic quantitative and terminological data. The use of a spherical camera, static images and video to create data-driven simulation models represents a completely new approach to the evaluation of manufacturing systems in Industry 4.0. Since the validation was carried out with the simulation scenario method, in which the reference scenario was extended by two additional proposals for research problem solutions, the simulation results represent advantages and limitations when using different optimization solutions. The optimization approaches in S1 and S2 define the enhancement or reorganization of the workplace with an additional manual assembly workplace, or with the introduction of a cooperative robot. To examine the suitability of the workplace from the point of ergonomic justification, a three-dimensional model taken with a spherical camera and appropriately computed visual was used and transferred to a software environment for carrying out ergonomic analyses. The RULA and OWAS methods used showed the possibilities for improving the manual assembly workplace and, at the same time, demonstrated clearly the high degree of justification for the introduction of a collaborative workplace. The main scientific contribution of the article refers to a new approach for the use of spherical cameras to collect data from real-world manufacturing systems. The captured data were used for workplace validation, the construction of a data-driven simulation model, as well as for ergonomic workplace analysis. The results prove that the presented evaluation approach allows a fast, efficient, and satisfactorily accurate application of visual computing methods in the comprehensive consideration of the investigation of performance and justification of manufacturing processes. Such an evaluation approach has not been proposed in the literature so far. Other researchers have been concentrating on the investigation of individual methods [1; 2; 24] but have not used them in the way presented in the manuscript. The limitations of the presented research are related to ensuring the accuracy of the recorded spherical camera data. According to the literature, the accuracy of data acquisition is approximately 2 mm, and this accuracy depends on the illuminance of the evaluated object and the distance between the camera and the acquired objects. A higher data accuracy can be achieved by using professional three-dimensional scanners or by increasing a constantly high illumination level of the scanned object. In the presented manuscript, we have not examined the accuracy of the data of the captured object compared to the real-world object, because the model for performing the evaluation is satisfactory, and the terminological and quantitative values are completely realistic. However, when performing more detailed analyses, it would be useful to examine the accuracy of the data. It would also be useful to focus further research on the development of a software environment that would allow real-time communication between the data collected by a spherical camera and a data-drive simulation model. With the current camera software, communication via the internet can only take place via a commercial, public platform for publishing video content.