Autor: Jochen Deuse

The increasing heterogeneity and complexity of industrial plant components from different manufacturers make it difficult to handle technical documentation consistently. In addition, the flexibility required for system changes challenges the long-term usability and legally compliant design of this documentation throughout the entire life cycle of cyber-physical production systems. This article contributes to the discussion on Technical Documentation 4.0 by systematically analyzing existing specifications and approaches and by proposing a concept for a holistic documentation framework.

Correctly recycling obsolete refrigeration devices plays an important role in environmental and climate protection efforts. Recycling plants are subject to regular audits to ensure their compliance with strict environmental regulations. However, the collection of audit-related data is a challenging and time-consuming task, as it is usually done manually and is prone to errors. One solution for more sustainable and efficient monitoring is to automate digital data collection using sensors and artificial intelligence. This enables a direct estimate of the expected level of pollutants. This paves the way for continuous performance monitoring and efficient management of refrigeration appliance recycling plants.

n the automotive industry, preventive quality actions are applied to ensure the quality of the end products. During production ramp-up the occurrence of nonconformities can be a critical issue. Nonconformities with new and innovative products can be especially challenging due to limited experience of previously unknown processes. To address this challenge, an IT application has been developed to capture the organization's existing knowledge and use this to support the problem- solving team in applying an enhanced 8D method.

Customers are increasingly demanding electronic components with high quality, which forces companies to continuously fulfil these requirements. This leads to a high number of inspection gates with high inspection severity and a high number of pseudo defects. Double inspections by process experts reduce these defects but generate high inspection costs. Autonomously acting inspection systems meet this challenge. Within this article, a machine learning algorithm was integrated into the solder paste inspection process to form an autonomous quality inspection system.

The quality of injection-molded components is becoming increasingly important in polymer technology due to extended areas of application with higher mechanical loads. As established methods of quality assurance are increasingly reaching their limits, the digital twin as a basis for cross-process and cross-company data analysis opens up new possibilities in plastics technology for proactive and predictive monitoring and improvement of process and component quality when processing plastics into technical components.

Internal and external communication is a key success factor for Industrial Data Science (IDS) projects. In particular, complex issues must be prepared and presented comprehensively. Visualization contributes to a uniform and deep understanding of data, processes, models, and results by all parties involved. This article shows the practical benefits of different visualisations for communication and documentation in the respective phases of IDS projects.

The advancing digitization leads to new possibilities for the design and digital support of business processes. In particular, non-R&D-intensive, mostly small and medium-sized enterprises, face great challenges in realizing these potentials. In the context of this article, various application scenarios are outlined. A detailed example of a non-R&D-intensive company shows how the procurement can be supported by the analysis and forecasting of relevant data, e.g. process data or the availability and costs of components, as well as the creation of the offer.

In order to deal successfully with the increasing complexity of production systems, the deve-lopment of system and problem-solving competencies is increasingly important. This paper presents an innovative learning concept that combines “on-the-job” student training with company training: „Multi real - multi-perspective learning in a real production factory“. Especially the company’s role and benefits are described.

Ensuring healthy, safe and competitive work is a major challenge in industrial production particularly regarding the demographic change in Germany. Especially work systems with a high amount of manual tasks require appropriate solutions. The article discusses the potential of hybrid human-robot work systems in manufacturing focusing assembly tasks.