I4S+ content for subscribers only

The automation of informational logistics processes is already one of the core challenges of manufacturing firms on their way to autonomous logistics systems. It is quite realistic that the majority of informational logistics processes will be running autonomously by the end of this decade. However, the path to this goal is still uncertain. Therefore, this article aims at defining the evolutionary stages of autonomy of logistics processes with the involvement of industry experts, describing prerequisites for reaching individual stages and discussing challenges along the way. In addition, the most important informational logistics processes with high autonomization potential are identified and an estimate is made of when the autonomy levels can be expected to be reached industry-wide.

Efficiency in container terminal operations is key for competitiveness. Many large German terminals use the flexible but relatively risk-laden manned straddle carriers (SCs). The research project STRADegy evaluated the reliability and profitability of automated SCs in northern-German container terminals via a combination of a pilot installation and an emulation at the container terminal in Wilhelmshaven. Parallel to that, rollout-guidelines were developed. This paper introduces central results regarding a successful rollout of auto-SC-systems.

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 “IT’S DIGITIVE” research project developed the prerequisites for collaborative and platform-supported processing of additive manufacturing-based services and thus important building blocks for an additive manufacturing-based service network. The focus was on intellectual property protection and the development of secure and trustworthy order fulfillment processes. Based on the identified inherent risks and threats in this distributed order processing, appropriate security countermeasures were developed using two use cases as examples and implemented as demonstrators.

Plant construction and engineering companies have to go to great lengths to present their highly complex products that weigh tons. Because sales staff cannot take them to the customer. Exhibiting them at trade fairs has proven its worth. But with the Corona pandemic, this sales channel has disappeared. That’s why digital alternatives are needed, such as a virtual showroom that supports salespeople in presenting and selling equipment. An API management platform ensures the smooth flow of data between various source systems and the virtual showroom app.

Einer der Erfolgsfaktoren für die Realisierung von Cloud-Manufacturing-Plattformen ist die Geschwindigkeit, mit der Angebote generiert werden können. Um aus dem Kundenauftrag möglichst automatisiert die Planungsprozesse der Plattform zu unterstützen extrahieren wir Bearbeitungsprozesse aus technischen Zeichnungen mittels eines künstlichen neuronalen Netzes. Dabei werden die Probleme der Multi-Label-Bildklassifikation und eines unsymmetrischen Datensatzes behandelt. Abschließend wird die Leistungsfähigkeit des Datensatzes an den Testdaten demonstriert und ein rekursives Verfahren zur Verbesserung des Systems im laufenden Betrieb beschrieben.

The digital transformation, especially the shift of maintenance to smart maintenance, contains a number of challenges. The management of data plays a significant role in this [1]. The use of sensor technology and devices for mobile data acquisition offers a variety of possibilities for quickly capturing large amounts of data, even in real time. In this context, however, there is also a need for tools that enable efficient data exchange and, at the same time, structured storage of large amounts of data. One of these tools is the digital lifecycle record, which has enormous potential for data-driven services thanks to its special features.

In recent years, the potential of cloud manufacturing in the B2B business fields has evolved enormously due to the increasing utilization of new digital technologies. Digital business processes confront manufacturing companies with new opportunities and challenges. For the digital transformation of these companies, the structured analysis of corresponding platform concepts is essential. In the first step, this can be supported by a framework that analyses basic insights and framework conditions for the development of dynamic cloud manufacturing platforms for the production sector. A corresponding framework is developed and presented in this article.

With a world population of ten billion people by the middle of the 21st century, natural resources must be used sustainably to prevent environmental disasters and wars. Traditional concepts such as recycling alone are no longer sufficient. Instead, we must think in terms of material cycles and transform the traditional production economy into a circular economy. To achieve this, a close link between production and recycling must be established, which is hardly conceivable without digitalization. This article begins with an overview of steps of industrial development towards more sustainability, finally showing how the digital transformation can facilitate the realization of a circular economy.

To be able to use artificial intelligence, a company does not necessarily need a qualified specialist. The Fraunhofer study “Cloud-based AI Platforms - Opportunities and Limits of Services for Machine Learning as a Service” shows how small and medium-sized companies can proceed instead. This article summarizes the arguments and results of the study, citations from it are therefore not marked accordingly.