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In factory operations, measuring equipment is often used without automatic storage or further processing possibilities of the measured value. In this case, employees must capture and process the measured values manually. In this article, an approach for the optical detection and digitization of measured values with the help of machine learning methods is presented. This aims to reduce the workload of the employees, avoid reading errors and enable automated documentation.

The realization of reorganization projects represents a complex and independent planning task within the framework of factory layout planning. Only little methodical knowledge exists, which considers the temporal, spatial and organizational restrictions in the creation of a schedule. This paper aims to present the interdependencies in the planning and execution of realization projects and thus to provide a basis for discussion for further investigations in the field of scheduling factory relocations for the reorganization of factory objects.

Many departments have already recognized the enormous increase in efficiency and personnel relief from routine activities through process automation. These digital thought leaders have begun to automate office processes using new technologies such as Robotic Process Automation (RPA), low code in the Microsoft Power Platform or in SAP. However, the positive experiences often remain in individual departments. Due to the lack of a strategic superstructure, companies as a whole have not yet succeeded in systematically transferring the added values to all areas. The organizational solution for this is called a "Center of Automation". Sometimes it is enough for the team to consist of two members to bring an overarching, digital process mindset into a company. (Only in German)

The digitization of processes is complex and error-prone. That is why manufacturing processes are monitored using statistical process control methods. The aim of the presented project was to answer the questions how the data basis for the use of the quality control chart (QRC) can be extended from random samples to near real-time data and how the implementation of the solution should be done. The software solution was developed and tested in the Fischertechnik learning factory. It could be shown that the data from the learning factory is suitable to be displayed in a closely timed manner and to be evaluated by means of process indicators of the QRK. In this way, errors can be avoided and capacities saved. (Only in German)

The logistics industry is currently being confronted with various challenges, such as the lack of drivers, global disruptions to supply chains and the environmental impact of freight transport. In a comparison between the modes of transport, this speaks for a greater shift in freight transport from road to rail. In this article, the challenges for this shift are examined and it is shown to what extent data models can simplify the transport planning and economic assessment of regional freight tram transports. (Only in German)

Technical cleanliness as a quality feature in the automotive industry is continuously growing in importance. In this context, particularly high cleanliness requirements are placed on battery cells for electric vehicles, which must be adhered to along the value chain. This paper will introduce an assessment method for the analysis of technical cleanliness in the production process of lithium-ion- cells as well as revealing potential failure causes.

The application of blockchain and smart contracts also enables the building and operation of decentralized autonomous organizations (DAOs). While DAOs are already regularly in use in other areas – e. g. the financial sector − there has hardly been any application in an industrial environment, although, digitalisation and the upcoming of the "Internet of Things" have created a fruitful environment. This article looks at possible economic approaches to adaptation and explores potential business models that could result from the establishment of DAOs in Industry 4.0. (Only in German)