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Despite a strong media presence and proven potential benefits, Industrie 4.0 is not yet established in many companies. Industry 4.0 projects often remain in a prototype status and do not deliver long-term added value. The solution is an integrated digital system landscape consisting of a connected, digital infrastructure and a business organization oriented towards Industrie 4.0. Through a four-step approach, this paper presents the foundations that need to be created to enable scalable solutions and realize long-term benefits.

Urban logistics has to change to become more silent and eco-friendlier. Off-peak delivery is regarded as an effective measure to cut carbon emissions. Implementing this concept will require the deployment of electric trucks to comply with noise regulations. This article provides an overview of current research themes in this field and uses McKinnon’s “Analytical framework for green logistics”to illustrate off-peak delivery as a concept, its benefits and limitations as well as the key requirements to make this concept work.

Reducing CO2 emissions to lower the global warming impact and protect the environment is a central objective of environmental policy. Climate neutrality shall be achieved by 2045 and a cross-sectoral reduction of greenhouse gases is only possible if fossil energy can be replaced by a sustainable alternative. In this context, green hydrogen and its derivatives have a high potential and could contribute to a more sustainable future. The city of Bremerhaven has recognized the potential of hydrogen and is currently establishing itself as a test region for hydrogen production and mobile applications.

The article addresses the digital transformation in international corporations. Using the example of the MANN+HUMMEL group, it will be shown how the digital maturity level can be measured in a group with several production locations and how the transformation process can be simplified and accelerated by identifying and using group-wide best practice solutions.

The main goal of assembling a self-sufficient microgrid is to integrate all technical equipment into an autonomous energy supply system as a virtual power plant (VPP). The system integration focuses on the power electronic devices and the combination of gas and electrical supply chains. The developed microgrid structure is fed from renewable energy systems (green hydrogen), the electrical grid and the H2 gas grid with a liquid or gaseous energy source. In comparison to an island grid, the microgrid can be operated in parallel mode with the common public grid. The associated challenges of transient energy flows and the holistic view of a regulated microgrid based on an electrical grid and an H2 gas network are part of this article.

Deep learning-based error detection methods outperform traditional methods because of the continuously increasing complexity of technical systems and inherent flexibility and scalability of Deep Learning techniques. This article introduces the KrakenBox – an autonomous Deep Learning-based error detector for industrial Cyber-Physical Systems (CPS). It exploits a lightweight, Long Short-Term Memory (LSTM) network capable of online error detection that can be deployed on an embedded platform such as NVIDIA Jetson AGX Xavier or even Google Coral Edge TPU. This article describes the architecture of the KrakenBox and demonstrates its application with two case studies.

In the project ARAS (Advanced Robot Assistance Solution) a robot programming assistant was developed, which allows for automated generation of robot programs for assembly processes. By using a multimodal approach for human-machine-interaction, assembly steps are recognized with machine learning algorithms while a worker is showing the robot how an assembly process is performed. Afterwards, a robot program is generated automatically. This way, new robot programs are created within minutes without the user having any knowledge about programming or robotics.

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.