In recent years, Industry 4.0 - with the aim to combine production processes with state-of-the-art communication and information technologies - has led to significant changes in the industrial environment. Due to the appearance of new challenges, companies need to adapt to upcoming demands, by implementing Industry 4.0 enabling technologies, such as simulations and innovative modelling approaches. Thereby, Simulation and Modelling refers to the application of models, representing a product, system, or process, to predict model behavior and further, to extend knowledge of the model. In the metal forming industry, simulations show great potential in the design and optimization of forming processes. Through the targeted use, expensive, and time-consuming experiments can be reduced. Furthermore, the process of decision making is supported and the efficiency of forming processes can be increased. During this thesis, models are developed to reproduce the entire upsetting process, starting at the heating of the cylindrical specimen to the transport and to the upsetting in the hydraulic press. Subsequently, an automated simulation sequence is implemented by using Python, which enables to create, run, and evaluate simulations with variable input parameters. For the calibration and validation of the developed simulations, upsetting tests with cylindrical specimen from aluminum alloy EN AW-6082 were conducted. Thereby, experiments, differing in process settings, such as temperature, transfer time, specimen geometry and upset height, were performed. The furnace and the hydraulic press at the Chair of Metal Forming represent two Cyber Physical Production Systems (CPPSs), providing sensor data of the conducted experiments. Furter, a concept is introduced, to visualize and process the sensor data to directly compare experiments and simulation.