## 4 Application
### Application of the ACSN to Optimize this Process  
Great potential is seen by integrating data from the supply network into decisions on the manufacturing control level [73]. This aims at improving delivery reliability, representing the second most supply network concern in the study on the semiconductor industry by [PERSON] [71] (cf. Section 4.1). Therefore, the semiconductor industry, more precisely its response to supply network events in manufacturing, is a well-suited application for the ACSN. Following this integration approach, the ACSN is designed to directly link events from supply network to manufacturing control in a complex job shop environment. The resulting optimization of the process for responding to events (cf. Section 4.2) is shown in Figure 9 and described below. Assuming that events from the supply network are detected and communicated automatically, the ACSN can complement and partially substitute the described process from  
Figure 9: Optimized process for responding to supply network events by the adaptive control loop for an integrated supply network. the supply network planner to the MES (cf. Section 4.2). For this purpose, the supply network planner continues to be informed about events that occur, but further communication and the decision on countermeasures are taken over by the ACSN. As a first step, events occurring in the supply network are communicated to the ACSN. On the IT side, this is done via an interface between supply chain (event) management and the ACSN controller. Subsequently, the ACSN controller takes over the coordination and decision-making tasks that were previously distributed between the supply network planner and the production planner by automating the information flows as well as the decision-making process. However, the production planner still has the ability to intervene with the ACSN's decisions. In addition to the interface to supply chain management already described, the automated decision-making process requires further interfaces within manufacturing IT landscape (cf. Section 3.4), which must be implemented to enable the ACSN to gain all relevant data enriching the supply network event with relevant context information. The decision-making on countermeasures to adapt the schedule is automated by the RL agent of the ACSN controller. In addition to data on the event from the supply network and on the current situation in manufacturing, which the production planner would also take into account, the agent is also aware of the effects of countermeasures in manufacturing from its training phase. This assumes that the agent's training necessary before deployment to its application has already been completed (cf. Section 3.3). Deploying the agent, the state and action variables of the agent must be mapped to the interfaces to the manufacturing IT landscape as described above. Consequently, a data-driven decision can be made at any time, which is not biased by possible subjective judgments of the production planner. The decision aims to define an adapted schedule for manufacturing, which can be implemented without negatively affecting the overall delivery reliability. Once a decision on countermeasures to adapt the schedule has been made, these measures could be implemented automatically using the MES. Therefore, the interface to the MES in particular must also enable controlling access to implement the adapted schedule for mitigating events' consequences in manufacturing. The coordination process with the line manager in manufacturing is no longer necessary, but the line manager continues to be informed about the changes made and still can intervene. In addition, the ACSN controller receives information about the effects of the implemented measures in manufacturing at any time via the interface to the MES. Future decisions can be further optimized using this feedback in continuous training parallel to operation.