Simulation

German sea and inland ports are of outstanding importance for Germany as a base for manufacturing and logistics. In the last decades, the port sector underwent several structural changes. Currently, the expected autonomation and digitalization of the entire supply chain create entirely new challenges for the port industry. In this context, the present article describes a planning approach for the development of an automated straddle carrier in northern German seaports. To evaluate both the reliability and the profitability of such an automated system, a planning approach, consisting of two fundamental steps, was chosen: (1) At first, in order to perform prototypical experiments, a pilot installation will be established in the area of the container terminal in Wilhelmshaven (CTW). (2) Based on this, the system’s suitability for the operative conditions in a mega container terminal is evaluated using a simulation and emulationbased planning approach.

Rising challenges of horizontal transports on container terminals and of the transports between various handling companies in the port demand a continuous improvement of processes and strategies to meet the requirements by clients and society. A low-risk method to test possible improvements is discrete event simulation. In this publication, horizontal transport on container terminals is compared to drayage transport between different handling companies in the port area. Similarities and contrasts are analyzed to simplify the transfer of knowledge between the two research fields.

Discrete-event simulation of logistics and production systems plays an important role in the context of digital transformation. Its integration into modern planning and control processes is urgently required in order to realize Industry 4.0 concepts. In addition, simulation models will be an important part of the so-called digital twin in the planning and operation. However, the requirements for simulation models and tools are not yet comprehensively defined, and technical solutions have not been adequately implemented. This article presents the fields of action for the implementation.

The core task of logistics can be described by the so-called “seven R”. IT means that the right product must be available in the right condition at the right time and at the right place. In addition, further key factors of a well-functioning logistics system are the right quantity, the right costs and the right information. Providing right or incorrect information at the wrong time can have a significant repercussion on the entire process. In particular, the human being who is the recipient of the information has the demanding task of correctly select and interpret it. Therefore, the human-machine interface plays a decisive role in the communication success between human employees and the digital systems surrounding the human at work. On that account, new user interfaces that do not burden people and provide information in a way that it can be perceived intuitively are needed in the future. This is where data glasses come into play.

New production technologies have inherent technical risks, but also established production technologies can not always be transferred to new products or components without problems. Accordingly, these technical risks must be taken into account when planning production systems. This paper presents an approach for the optimized allocation of development resources with regard to the technical risks of production technologies and processes. First, the production scenario is modeled and simulated using GRAMOSA. Then the simulation results are used for the optimized assignment of the development budget by means of mathematical optimization.

Technological progress offers opportunities for introducing new business models but also opens new paths for attackers. Security-by-design integrates factory security from the start and introduces a continuous security process built upon a variety of components. This article illustrates some of these components by highlighting secure processes with specific case studies: anomaly detection within value networks and secure production planning with simulation.

The Smart Factory concept describes the extensively networked production of industry 4.0, which affects the entire life cycle of a factory and, in particular, factory planning and factory operation. Both classic and more up-to-date factory planning approaches come to their limits through the new requirements. This paper identifies the requirements that are important for the future structural planning of factories and presents the need for a holistic virtual validation of the factory structure. Furthermore, a methodological approach is addressed for the solution of the challenges.