## 1 Introduction
Its structure and configuration are the result of a decades-long incremental development process stretching back to the 1960s. Different systems were developed for different tasks and varying functionalities. The systems were then connected via interfaces to move information between them. Each system contains its own set of data, often inconsistent with the data sets in other systems. This makes achieving high operational performance, efficient processes, and quick operational control hard. Furthermore, all of these systems on various levels operate within different timeframes. While data and information on the lower levels are acquired,  
Figure 2: The automation pyramid according to the ISA-95 model [21]. analyzed, processed, and distributed within seconds or minutes, systems on levels 3 and 4 often operate within hours or even days. This further complicates the efficient and effective operational as well as strategic management of a manufacturing company. Due to the shortcomings of these traditional systems, new approaches to operational management or production systems have been developed over the last decade, especially for operational activities like scheduling, sequencing, monitoring, and controlling. In most systems, these tasks take place on the level of the ERP systems or the MES (levels 3 and 4) [26]. Modern MESs (as well as systems for advanced planning and scheduling APS) do a better job concerning the operationalization of the rough capacity plan generated in the ERP system and the operational steering of the production. However, the obstacles associated with their implementation and seamless integration often render the benefits far from achievable [27]. Despite their shortcomings, ERP systems and MESs offer a good foundation for future concepts since they already contain most of the relevant data upon which future solutions can be built. Furthermore, they are the IT backbone of most companies across which all operations are conducted. Any transition towards a new paradigm or operational system/logic has to consider this and offer appropriate compatibility and interoperability within the transition phase. Regarding the increasing need for more flexible, smarter, and faster production control, especially against the abovementioned challenges, decentralized production steering and control have been proposed as one possible solution. Today, cost-effective and powerful CPSs that can easily be connected via communication protocols are widely available. With those, OPC-UA, SOAs (service-oriented architectures), and other agent-based solutions appear more realistic than ever and have received growing attention [28; 29; 30]. In order to differentiate the advantages and challenges, the current developments toward more agile and flexible solutions for production planning and control (PPC) will be discussed in Section 2.2. It would, however, be wrong to put all the blame for the inflexibility and lack of operational control on the different software systems and their inherent limitations. These systems were developed to help with the operational management and control of then-existing production systems. These systems were often decades old, containing machines and processes predating the lunar landing and within even older buildings. Neither the software systems nor the factories were designed on a blank slate for the current economic challenges. However, manufacturing companies must compete and survive in ever-shifting markets with high volatility and unpredictability and new, ever-faster-emerging technologies and improved old ones. Against these challenges, factory planning, operational management, and existing IT infrastructure must be viewed together. This combined view is needed, especially from a data and design point of view. By offering a potential solution for this challenge, the authors hope to contribute to further developing integrated Industry-4.0-level production systems.