## 3 Results
### Systematic Evaluation of the Identified Literature
#### 3.4.5 Decentralized Applications  
A total of 25.00% of the identified papers were assigned to the cluster \"decentralized applications\". In this context, a trend toward decentralized applications and the use of CPS can be observed in production and logistics [3]. Due to decentralized decisions, the simulation of these systems becomes more difficult. Some authors address this problem by integrating the control mechanism of these entities in their simulations. [PERSON] et al. propose a holistic structure to create a DT for manufacturing processes. Each entity is represented by a holon to enable holarchic (distributed) control. To represent each holon in the VM, an agent-based simulation (ABS) is used, where each holon is an agent. A case study is conducted in a laboratory environment including a conveyor belt, cobots, and seven workstations. With a predefined logic, the DT controls the different holons via the ABS considering real-time information from the physical entities. It is stated that the DT can make predictions and control the production line, considering malfunctions of the holons [43]. AGVs are increasingly finding their way into the industry to enable flexible material supply within the production system. Existing fleet management systems for AGVs are mainly focused on routing and localization, without considering the real-time information on manufacturing processes. Therefore, [PERSON] et al. combine the AGV simulator with a DES to create a VM for a DT. To evaluate this method, a case study was conducted in a laboratory environment, including weight scales at workstations and AGVs. With an OPC UA interface, the physical entities communicate with the VM and the service system. Information about the progress of work at the workstations is derived from the weight scale data. The controlling mechanism of the material supply is also predefined [46]. In addition to this, [PERSON] et al. address this problem by integrating the operational software code of the AGV into the DES of the production system. In a simulation study, a traditional pre-planning policy is compared with two different optimization policies (min. production time, min. logistics time) of the DT. In addition, three different scenarios are investigated in terms of selling price and demand variation. The simulation results show that different strategies could handle different scenarios better than others. It is suggested that DT should change its strategies depending on the current situation of a manufacturing system [47]. Another paper deals with the integration of RTLS information as well as with the integration of control mechanisms and other information on AGVs and cobots in a DT. The concept is tested in a laboratory environment and the game engine Unity is used as a virtual environment to create the VM. Applications for workstation design by using IMMA (Intelligent Moving Manikins), for picking processes, routing, education, and monitoring are described; service systems need to be implemented and more experiments are necessary to evaluate the potential benefits of this approach [38]. Nevertheless, predefined control mechanisms can lead to suboptimal results, and, in the case of material flow systems, long waiting times and wasted energy may be the result. To tackle this problem, [PERSON] et al. designed a proactive material handling system based on DT. The concept focuses on discrete manufacturing shop-floor systems and was exemplarily implemented into tire mold production. A time-weighted multiple linear regression model is used to predict the energy consumption and travel distance for the current situation. Therefore, different real-time information from various sources is considered. An NSGA 2 algorithm (a multi-objective genetic algorithm) is used to optimize these parameters and, in comparison to the legacy passive material handling system with predefined control mechanisms, leads to a 52.7% and 66.7% reduction in energy usage and travel distance, respectively [42]. [PERSON] et al.