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Digitalization opens up new forms of operational training. A growing focus is on smart services, which allow for proactive engagement with customer demands and empower businesses in times of digitalization. While traditional learning environments are rarely tailored toward individual needs, smart services offer new opportunities. Decentralization, previously only a utopic vision, is becoming the reality now.

In remanufacturing, used goods are brought up to the quality level of a new product. This distinguishes it from recycling, which recovers materials and converts them into new units or products. Various uncertainties, such as the condition, quantity and time of return, can be minimized with Industry 4.0 approaches and artificial intelligence. A special learning concept ensures that employees have the required competence profiles in this context.

In the course of digitalization, collaboration between humans and machines is inevitable. This should be considered as early as possible in further training. There’s a major obstacle to this in mechanical engineering: the lack of access to the knowledge needed for success. This can have a negative impact on the acceptance of digitalized processes. A teaching and learning platform teaching digitalization on real machines does important work here.

In order to cope with growing customer requirements and the associated increase in complexity, companies are opening up their value chains, reducing their vertical integration and increasingly entering into collaborations. Cross-company data exchange along the supply chain is thus becoming a key component for competitiveness and the realization of customer-specific solutions. For this reason, the European Union has launched the GAIA-X project, which aims to create the next generation of data infrastructure for Europe and its companies. The GAIA-X maturity model offers an approach for classifying companies into different development stages and provides concrete requirements for further development along a predefined development path towards becoming a fully-fledged participant in the federated GAIA-X data infrastructure.

Digital transformation processes have a high tendency for delay, exceeding costs, and failure. This poses a significant risk in competitive global markets and shifting business models of entire industries. Successful companies have a different approach to new technologies than more traditional incumbents. Including the workforce in the transformation via change leadership in a digital transformation coaching process can reduce fear and resistance and can lead to a paradigm shift of approaching the digital transformation itself: as an agility driven, infinite game with high potential gain.

Establishing “smart” production processes that are focused on sustainability and based on aggregated data requires a great deal of exchange at various levels. The vertical integration of different production components provides companies with an important basis for achieving their sustainability goals. Digital twins can play a decisive role in driving this process forward.

The planning and implementation of automated warehouses is characterized by high investments and risks. The FMEA (Failure Mode and Effects Analysis) currently used to reduce risks requires a great deal of effort to conduct, as it has deficits in terms of design and implementation support. These deficits include a predominant focus on the process view without linking this to the design FMEA for automation objects, an insufficient structure for the use of similar repetitive processes and technologies, a lack of automated, parameterized generation of activities, failures and causes, and a lack of integrated test scenario derivation. These deficits lead to unrecognized failures and increase the effort required to carry out the FMEA and develop test scenarios. In this article, we present a generic FMEA model which, among other things, is able to access extensive practical data in the form of knowledge bases and thus resolve the aforementioned deficits.

Digital product passports are becoming increasingly mandatory for monitoring saving targets within the framework of EU-wide emission reductions. DPPs can enable a standardized exchange of emissions data along the entire product life cycle. A framework for systematic introduction and targeted use can simplify their often difficult practical integration, especially for small and medium-sized companies.

The crises of recent years have highlighted the importance of robust business processes. Even if the concept of robustness is often not clearly defined in the context of entrepreneurial activity, it can certainly be defined on the basis of various factors such as agility, adaptability and resilience. A systematic analysis of robustness and its prerequisites in the corporate context is therefore highly relevant, especially in times characterized by uncertainty.