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The integration of industrial laser assistance systems for worker guidance into the control layer opens up possibilities of digital transformation for manufacturing companies. These are illustrated using the example of the Digital Factory of the Leuphana University Lüneburg. In a practice project a manual assembly station using an industrial laser assistance system is developed and integrated into the SIMATIC control level of the digital factory. The worker interacts with the assistance system and is guided by the latter through the order-related assembly process. The worker stands in the center of action.

The trend towards customer-specific mass production poses great challenges for the classic production methods of small and medium-sized companies. The combination of flexible robotic solutions and artificial intelligence approaches is promising to enable production efficiency and fast adaptability in modern production systems. This paper presents such a solution in the form of a realized demonstrator setup composed of a collaborative robot assistant. The robotic system independently interprets the activities of a human employee and supports the employee in his or her activities by imitation.

Small and medium-sized enterprises can hardly exploit the potential of digital transformation. In the BMBF research project »ScaleIT« an Industry 4.0 platform was developed with which individual process steps can be improved with the help of apps. There are both ready to use apps and open source tools that make it easy to develop new apps. Companies do not run the risk of a profound change in their IT processes, but can optimize their value chain step-by-step by implementing and installing new Industry 4.0 apps. A methodology helps to uncover the greatest digitization potential in companies.

In this contribution, a method for the implementation of Industry 4.0 projects in production and logistics for small and medium-sized enterprises (SME) is described. This method takes various boundary conditions of SMEs into consideration and has been applied in different projects with SMEs within the “Mittelstand 4.0-Kompetenzzentrum Hamburg” initiative. The method focuses on an integration of new technologies into existing systems and the connection of newly generated data with known information flows.

When digitalising and automating work processes, it is often overlooked that this can trigger serious changes for the organisation. This article shows that such changes can lead to an incongruence between “what an organization does” (practice), “what it can do” (knowledge) and “who it is” (identity). These incongruities must be overcome in order to implement change successfully. If managers are aware of this, many problems such as the collapse of existing routines, knowledge gaps or the departure of important employees can be foreseen and solved.

Many large companies are increasingly facing the pressure to meet rapidly changing customer needs and to respond quickly to new technologies. These companies often suffer from coercive bureaucracy, that is, rule rigidity. For this reason, a huge increase in alternative working practices such as agile working has been noticed lately. While it was firstly found in small business start-ups, more and more traditional companies as DAX-companies have tried to use agile working practices selectively in their development departments. However, can agile working be so simply transferred to development of traditional products?

Management tools are a dime a dozen. The US-American strategy consultancy Bain & Company, for example, analyses regularly the 25 most popular of them worldwide. However, the best tool is only as good as its user. The proper and efficient utilization requires common sense. If a manager has it or not can be identified by the following qualities: He knows that others see him different from how he sees himself. He sets high value on a respectful feedback culture in his company, and he counts on the power of cooperation.

Handling increasing complexity is a major challenge within the manufacturing industry. Methods from Industrie 4.0, e. g. data analytics, can support in reducing complexity. Currently, benefits of implementing data analytics within large scale manufacturing are limited. For this purpose, a study regarding the potentials and obstacles for data analytics in large scale manufacturing was conducted. The results of this study show the necessity of adaptive data availability, strategic prioritization as well as scalable data analytics in order for data analytics to be successful.

The digital twin is supposed to be a major tool for increasing productivity in the age of industrial digitalization. However, there are many heterogeneous definitions about the digital twin. This situation hardly supports the practical digital twin implementation. For this reason, the article introduces a new concept, called the Digital Twin Theory which is a theoretical framework containing several hypotheses about digital twins. The aim of the framework is a better understanding about the digital twin management in practice.

Digitization in engineering promises automated workflows, higher speed and lower costs in the development of automation solutions. The prerequisite for this is not only modularization based on a structured description language, but also uniform, interdependent modeling that ensures automated data exchange across system boundaries. In order to achieve a broad application, the underlying ontology should be based on existing norms and standards and be available in open source applications. However, the collaborative and consistent development of such an ontology requires a structured, methodical procedure and an associated modelling map that serves as an orientation for standardized, work-sharing modelling. A possible approach for the required procedure model and the related map will be presented in this article and validated using AutomationML. The presented approach should point out a possible direction and stimulate further process-controlled modelling efforts of ontologies.