Flexibility in mass-customized manufacturing can be supported significantly by the introduction of Cyber-Physical Production System and the connection of production modules to AI (artificial intelligence) Cloud services. Even though there exist standardized protocols from device to IT system, there are still challenges for the synchronization between cyber-model and physical object, and the application of decision making in the cyber-model. Although high performance machine learning services make the Cloud a preferred computation node, possible unstable connection with manufacturing resources enforce new service distribution approaches in the network. This paper proposes an Edge Computing architecture which is the mediator between machines, by providing local Cloud services with fast response time and preprocessing resources for a vast amount of data. As an illustrative example the selected Edge service pre-processes data form an augmented reality device in order to communicate with the cyber-model in real time. The Edge platform controls the computing resources and prioritizes all processes of Edge Services for a dynamic update of production lines and human-machine-interaction.