Manufacturing Systems

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.

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.

The toolfree production of parts using 3D printing technology enables dynamic use of the production area. On the one hand, this makes it possible to react flexibly to changes and, on the other hand, to achieve a high level of efficiency in the production units. The blockchain technology enables a common database between the participants. This leads to a verifiable collaboration in the case of the relationship between customer and manufacturer. This paper describes how available additive manufacturing resources can be identified and offered in a decentralized production network.

A newly developed hand guided collaborative robot system will be used for manual mechanical joining process in the final assembly of aircrafts. The tool can be moved quickly and precisely to reach all joining positions avoiding physical effort for the operator. Special focus was given on the integrated handling of the entire system. The interlinked sensory of all subsystems ensures a smart control of the system. A mobile device was implemented to increase the usability and to foster the employees’ acceptance of the solution. It enables significantly improved process documentation, reproducibility and transparency.

Existing factories face multiple problems due to their hierarchical structure of decision making and control. Cyber-physical systems principally allow to increase the degree of autonomy to new heights. But which degree of autonomy is really useful and beneficiary? This paper differentiates diverse definitions of autonomy and approaches to determine them. Some experimental findings in a lab environment help to answer the question raised in this paper.

The performance of assistance systems, especially in the automotive sector, has become an unique selling point. The trend toward Autonomous driving represents the expected impact of innovation resulting from the exploitation of the latest technologies. Besides autonomous driving, other areas of application for autonomous systems could trigger social change - the prime example being industrial production. The following article presents a planning approach tailored to the complex engineering task of planning and designing autonomous systems for industrial applications.

Fast-pacing technologies force companies to improve their flexibility. Fluctuating demand and volatile markets require high reactivity. Due to Industry 4.0 and globalization, communication in companies is becoming increasingly important. Social networks can be used to improve the efficiency of in-house communication and create a connection to partners and customers. This paper discusses how social networks can support corporate communication internally as well as externally, with a focus on logistics and production. In this context, practical examples are shown and a self-developed model is presented.

The large number of systems offered on the market makes a well-founded selection process necessary from the requirement survey to the final system selection. A comprehensive model that systematically supports and simplifies this process is the subject of this two-part article. The methodology goes beyond a questionnaire-based query and verifies system capabilities using structured case studies. The first part of the article [1] describes the process steps from the survey and collection of requirements of the customer to the system to their structuring in customer specifications. The present second part outlines the process steps of the system rough selection up to its fine selection. The individual selection steps are methodically supported by practical references as well as by the use of concrete tools. Using the described methodology selected systems can be objectively compared - a prerequisite for effective and efficient system selection for industrial companies.