## 1 Introduction
The same is often true for the processes within the manufacturing systems. These were usually not designed for information sharing and collaborative production. The idea that a machine performing a specific process within a chain of processes might have to change its working parameters during operations based on another machine's condition/performance was not part of the design of these processes and, in fact, the overall systems. This legacy aspect of most manufacturing systems is also reflected in the overall composition of the systems. Usually, companies possess equipment from various suppliers [6; 15]. Often, these machines come with interfaces and programming, which makes connecting them and retrieving necessary information more difficult. It also complicates the implementation of decentralized steering and control. The approaches to address these challenges are, e.g., OPC-UA (Oper Platform Communications-Unified Architecture) or ROS (Robot Operating System). While ROS is a set of open-source libraries and tools for building robot applications, OPC-UA offers platform-independent communication in a multi-layer approach. OPC-UA contains integrated encryption, authentication, and auditing and offers expandability by integrating new features without compromising existing applications and comprehensive information modeling. It further allows for event management, enabling the definition and notification of important data and information, and supports numerous protocols JSON over websockets [16; 17]. Even though OPC-UA offers a reliable transportation and communication solution that enables a much easier connection of machines and various outer systems, it only addresses a small (but important) part of the greater picture. In order to offer a holistic model for the entire concept of Industry 4.0, the Reference Architecture Model for Industry 4.0 (RAMI 4.0) was developed. It is a three-dimensional model aimed at systematizing, structuring, and mapping the complex relationships and functionalities required for Industry 4.0 application. [18]. The RAMI 4.0 model is composed of three dimensions (see Figure 1). These are life cycles and value streams, hierarchy levels, and multiple IT layers (information technologies), ranging from the asset layer at the bottom to the business layer at the top. Each layer represents different tasks and processes. The lowest layer represents physical objects like machines, sensors, actuators, or technological documentation [18]. On this level, the CPSs are located. The information generated within the asset layer is then provided to higher layers in a structured way via an administrative shell that organizes the asset information. This takes place in the integration layer. Functions in this layer further integrate information from products and processes and other logistical information relevant to the identification of objects within the system [18]. The communication layer connects the two basic layers with the upper layers and all elements within the IIoT network. This is where communication protocols like OPC-UA are located. The information layer processes the upcoming information, checks it for integrity, and then summarizes and repackages it in a new information model. It thus provides a standard interface or communication model for the functional and business layer. The functional layer hosts' aspects, like production planning rule generation, represent the runtime environment for the manufacturing system. RAMI 4.0 provides a solid framework for the hierarchical classification of objects, functions, and tasks across the Industry 4.0 vision. It gives companies a guideline for where specific tasks occur, how information is provided, and how additional assets might be integrated. However, in the context of this work, there are two aspects worth mentioning. The first aspect is in the context of production planning and control, located on the functional layer.