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Digital networking via the company and as well, the overall supply chain, can only succeed if digital planning reflects reality as accurately as possible and if production control can react to deviations in real time. In essence, this leads to a development of process control towards process regulation. While longterm production and resource planning is usually mapped by Enterprise Resource Planning (ERP) systems, detailed planning, including short-term deviations and real-time data at the production level, is increasingly supported by Manufacturing Execution Systems (MES) at the production control level. However, in order to bring the underlying system concepts into line with Industry 4.0 efforts in a standardized manner, mutual functional integration within the framework of interoperable production planning and control is of crucial importance. For this purpose, studies were carried out in particular into cause-effect relationships. Thus, the overarching research objective is a valid design model to increase the controllability of production planning and control systems (PPC) in the context of Industry 4.0.
Task-Specific Decision Support Systems in Multi-Level Production Systems based on the digital shadow
(2019)
Due to the increasing spread of Information and Communication Technologies (ICT) suitable for shop floors, the production environment can more easily be digitally connected to the various decision making levels of a production system. This connectivity as well as an increasing availability of high-resolution feedback data, can be used for decision support for all levels of the company and supply chain. To enable data driven decision support, different data sources were structured and linked. The data was combined in task-specific digital shadows, selecting clustering and aggregation rules to gain information. Visual interfaces for task-specific decision support systems (DSS) were developed and evaluated positively by domain experts. The complexity of decision making on different levels was successfully reduced as an effect of the processed amounts of data. These interfaces support decision making, but can additionally be improved if DSS are extended with smart agents as proposed in the Internet of Production.
Blockchain as Middleware+
(2019)
In supporting decision making of manufacturing companies, the added value of cross-domain data exchange for aggregating information is well established in enterprise organization research and is represented, for example, in the reference model “Internet of Production” (IoP). Currently, there is little research regarding the role of Blockchain technology in such a reference model and how specifically the IoP needs to be expanded to address cross-company data exchange. This paper presents a proposal for such an extension to outline the use of Blockchain technology and to elaborate the open research demands for implementation. In particular, desk research and the development of concrete use cases for cross-company data exchange between business application systems were carried out. The results are, on the one hand, extending the IoP by a third dimension, which corresponds to the supply chain, and, on the other hand clarification of the role Blockchain technology can take in this context.
This paper won the John Burbidge Best Paper Award (see Attachment 2).