Design

Nowadays, maintenance logistics is considered an integral part of sustainable maintenance management and is now conducted with IT support in many of the fields where it is applied. It can therefore be seen as one of many examples of digitalization in the working world. Both the selected maintenance strategy, the implementation of which is more or less linked to the use of intelligent technologies, and the current level of IT integration are emblematic of the degree of digitalization in this context. In the agricultural sector, the type of maintenance objects in question plays an important role in the use of digital technologies. This article is dedicated to investigating the status quo of digital maintenance logistics in German agricultural businesses at the interface of ICT, technology and business.

Short delivery times are essential in competitive markets. In addition to product selection and quality requirements, customers are also demanding more and more from logistics. However, high product variance complicates the situation, as it involves complex material flows and therefore leads to long throughput times. However, a four-step process analysis and modeling can help to reduce throughput times and strengthen the competitiveness of companies from within.

Alongside sustainability, sustainability management is also gaining in importance. At the same time, digitalization continues to advance, embedded in a complex interplay of economic, ecological and social challenges. A sustainability platform that not only records relevant company data, but also ensures the necessary security, can unleash synergies between transformative trends to foster sustainable and efficient corporate development.

Transformative forces present companies with enormous challenges. At the same time, new forms of collaboration and new roles and responsibilities are emerging. Due to the risks associated with change, many employees hold on to old habits and work processes, which can slow down positive developments. The challenge for managers is to recognize this resistance, prevent it and turn it into acceptance or even proactive support.

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.

Motion-Mining® is a technology that uses motion sensors and pattern recognition to enable automated process mapping and analysis of manual work. This article evaluates the advantages and limitations of its use in manufacturing and logistics processes. To this end, Motion-Mining® is compared with traditional lean management tools used to analyze manual activities. Experiences derived from four use cases provide decision support for selecting the appropriate method for a specific use case.

The decentralized data ecosystem Gaia-X, which is currently under development, supports the future viability of the digital data economy in Europe. But how can relevant use cases be realized in Gaia-X from a service-oriented perspective? To answer this question, this article presents a methodology that describes a structured and interdisciplinary approach to service development in the ongoing Gaia-X 4 ROMS consortium research project [1]. In this project, federated services are realized in five processing steps on the basis of use cases. IT experts, software developers and industry users can leverage the model to efficiently coordinate the joint realization of use cases with Gaia-X and the goal of sovereign data exchange.

Spare parts for older products are often difficult to obtain or cannot be produced in an economically viable way using conventional manufacturing techniques. This article examines whether damping elements for gearbox bearings (in/for the automotive sector) can be manufactured from thermoplastic polyurethanes (TPU) with the same or compatible properties as the original part alternatively using additive manufacturing.

The design of gear pumps causes gap flows, which counteract efforts to achieve exact dosing. However, due to the complex relationships between pressure, temperature, manufacturing tolerances and the material properties of the pumped medium, these gap flows cannot be reliably described in real time using physical equation systems. By using new algorithms and artificial neural networks, it was possible to solve this problem and replace a cost-intensive flow measurement method at the same time. This new approach has been tested on a pilot plant scale, and has already demonstrated that it can achieve the accuracy of a classic flow meter, while at the same time significantly decreasing the response time and increasing the application range of the dosing system.