# Use of Data-Driven Simulation Modeling and Visual Computing Methods for Workplace Evaluation
## 2 Problem Description
### Data-Driven Simulation Modeling  
Simulation methods, such as discrete systems simulations [23], system dynamics, and agent-based simulations, have their main advantage in evaluation efficiency of highly flexible manufacturing systems, where they have to continuously adapt and evaluate real-world systems (preferably in real time) by accessing data bases, documents, spreadsheets, and a central data information service [8]. Such simulation methods reflect the complex decision logics of the interdependence of different model units. Data-driven simulation modeling is defined as a method that enables the user to design and use simulation modeling without detailed knowledge of program codes. The advantage of data-driven simulation models is the simplicity and transparency of the design and use of the simulation model [9]. The user is not necessarily a research specialist but rather an operator who adjusts, controls, and evaluates the simulation model using simulation scenarios. Data-driven simulation models are built in four consecutive steps. * Preparation of data obtained directly from the evaluated system. The data must be relevant, identified, and classified according to the described problem. Information modeling is used to describe the complex interdependencies of the data objects and the connection to the modeled system. Commercial application platforms enable relational or object-oriented data modeling. Relational data modeling with specific syntax allows the construction of an information schema for data transfer and usage. Object-oriented modeling allows objects and entities to be reused in a hierarchical order that allows multiple intersections with each other. Input data can be collected using various approaches, usually using advanced communication protocols via a central data information service. In the present manuscript, the acquisition of input data of a simulation model is performed using visual computing methods and hardware represented by a spherical camera. Figure 1: Two-level architecture model highlighting visual computing methods in Industry 4.0 contexts. Input data from the spherical camera defines three-dimensional model of the workplace and operational parameters of the manufacturing system. The acquisition and processing of the input data play a key role for the relevance and significance of the following three modeling steps. * Design of a simulation model that defines the specificity of the modeled object and ensures the identity of the model with relation to real-world modeled objects. The most commonly used integrated logic of a commercial environment is extended by a specially designed program code that allows a detailed description of a real-world system's characteristics. In addition to static data, the simulation model also uses dynamic data, which influence the continuous change of the model in the process of implementation and testing different simulation scenarios. In the present manuscript, the simulation model design was made using data captured by the spherical camera. * The verification of the simulation model is crucial to achieve credible simulation results. Verification is a process in which the adequacy of a computer-controlled simulation model is verified with data obtained from a real-world modeled system. Conceptual simulation scenarios, where the results describe new derivatives of the modeled object, must be evaluated with parallels to the basic reference data set. In presented manuscript one referential simulation scenario was used and two additional optimization scenarios, describing current manufacturing system state and new solutions proposals. * Simulation of scenarios that enter variable data into the object model dynamically and describe the situation in the existing real-world object or newly proposed solutions of existing parameters. Simulation scenarios represent the final step in the configuration of a data-driven simulation model that is closely related to events happening in the real-world system.