Simulation

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.

Simulation is an accepted method within modern engineering processes across different industrial domains. Especially automation engineers use modelling and simulation methods within various project phases to guarantee high quality products that are produced on high quality plants. The necessity of modern simulation technology rises due to the latest trends regarding the virtualization of production plants. This article describes the need for standards within the field of modelling and simulation of mechatronic factories and machines using a digital twin.

Wind energy has become an established technology for the generation of electricity from renewable energies. However, suitable sites for the installation of onshore wind turbines are limited or often already developed. Consequently, offshore wind energy will play a key role in the future of renewable energy production. Especially in implementing the turnaround of energy policy. The installation of offshore wind farms is comparatively complex and expensive due to the harsh weather conditions and the limited availability of resources. Therefore, new concepts for the construction of offshore wind parks have to be developed and evaluated. However, classical planning tools reach their limits due to such complex problems. This gap can be closed by means of a process simulation.

Industrial work 4.0 challenges workers due to ambiguity, self-organization, and interconnec-tedness. To qualify workers to successfully cope with these challenges, this article introduces the software-based situational learning factory that is completed like a flight simulator. By playing these so called serious games that simulate situations on the shop floor of varying complexity, employees gain experiential knowledge and improve their IT-skills.

The global community is currently experiencing many disasters requiring humanitarian aid not only for ethical reasons. This concerns natural disasters, but also man-made disasters such as war, terrorist attacks and nuclear disasters. Humanitarian aid is generally understood as a response to humanitarian emergencies, which goes beyond an initial support. Key elements of humanitarian aid are disaster management and humanitarian logistics, which operate as organizational principles in order to coordinate the supply of food, goods and emergency rescue workers. Due to the high dynamics and limited information transparency it is very difficult for the responsible persons to mitigate the plight as effectively as possible. A good method to develop effective disaster risk management strategies and decision-making mechanisms is the use of model-based planning and control approaches. This article discusses the current modeling challenges of humanitarian aid scenarios as well as the potential of ...

When selecting logistics strategies for their production networks, companies increasingly need to consider not only economic but as well environmental aspects. Those environmental aspects are, however, not easy to evaluate. This holds especially for SME with their limited resources. To assist companies in selecting a logistics strategy that meets their needs, a KPI framework to evaluate the economic and environmental sustainability of logistics strategies was developed within the Green-Net research project. Using the system dynamics approach, a simulation model was developed, which helps to anticipate and evaluate the impact of a certain logistics strategy on the company’s network.