Simulation

Virtual prototypes become more and more relevant in product development since they permit the early testing of machines and include the customer in the product development process. Virtual prototyping can help to decrease costs in service, development and sales as well as marketing. Hence, the creation of virtual prototypes is still a resource insensitive project. This article presents the results of the research project “INPROVY”. The approach uses a model based method for systematic creation of simulation models. It includes the product management perspective of simulation models and uses reference models for higher reuse. Based on a mobile construction vehicle, the creation of various simulation models and the management of product variants are discussed.

Changeability is the capability of an organization to establish changes with a lasting effect. The possibility to correctly plan and create changeability of an organization already in the phase of plan-ning is an essential factor to be taken into account when considering changeable logistics systems. For this reason there is a need for conceptual change of established planning methods. In the context of discrete-event simulation, as an established planning method, the modular design of simulation models may be a first step to include changeability into model-based analysis. Against this background, This article discusses possibilities to build modular simulation models and shows how this modular design can be used in practice.

In the research project LUPO a hybrid simulation laboratory is build up. This combines the advantages of the computer simulation with those of a model factory. For the systematic recording, mapping and analysis of various production processes a procedure model has been created that responds to the special requirements (quick, flexible, effortless determination of informative results) of the project. A library of production objects facilitates the reutilisa tion of existing machines and hereby a reduction of simulation effort.

Due to the increasing energy demand in Brazil renewable energy sources become more and more important. In addition to hydropower which is already used in Brazil there is a high potential for wind energy. In particular the coastal regions in Northern Brazil have great potential for using wind turbines. Modern wind turbines show a clear tendency for larger more powerful and economic usage. But the limits of the physical feasibility are reached. A weight reduction while increasing the maintenance-free operation time is the problem to be solved by a Brazilian-German research team. The Institute of Metal Forming, RWTH Aachen develops a solution with regard to the lightweight construction of generator shafts for large wind turbines within the “Brazilian German Collaborative Research Initiative in Manufacturing Technology” (BRAGECRIM) together with the “Universidade Federal do Rio Grande do Sul (Porto Alegre, Brazil).

This study deals with the problem of collaborative maritime transportation between manufactured export industries and maritime carriers as well as its relationships polices applied to the Brazilian case. The general maritime exportation mechanism is very comprehensive and complex with several variables (volumes, capacity of the ships, prices, maritime fees) and agents such as industries and carriers. To understand the patterns of transition from the system and its long-term behaviour, the System Dynamics’ approach is presented in order to start modelling the problem. This method allows improving the analysis of the global behaviour of the export network. For further implementation, some recommendations are given.

In an increasingly turbulent environment, today enterprises are confronted with the challenge of aligning available capacities with the capacities required using targeted measures. An approach is presented to support the selection of measures quantitatively.

In a world of steady change, manufacturing companies face major challenges. They have to react quickly to an increasing competition and more and more individual customer requests. New technologies and organisational structures like RFID or decentralised and real-time based production control can deal with this issue successfully. The specific realization of selection and analysis of each production process of the company often approves to be difficult and cost intensive. Previous simulation approaches are frequently combined with high efforts in order to state credible propositions regarding suitability and economic efficiency. The present paper shows a new opportunity towards managing these disadvantages. Additionally, the advantages are combined with computer-based simulations of the model factory. A fast and flexible illustration of the analysed production processes is achieved.

The investigation of dynamical properties considering job shop systems often employs discrete-event simulation. How-ever, to apply advanced analysis methods like Fourier and correlation analysis to the temporal evolution of important variables, time series are required, which comprise data taken in equally measured timesteps. Therefore sampling is applied. This paper investigates the definition of an optimal sampling rate, which ensures high quality data at a minimum of sampling efforts. Furthermore, errors occurring due to deviating sampling rates are investigated and summed up in qualitative error curves.

The Autonomous Logistic Engineering Methodology (ALEM), which is developed within the Collaborative Research Center 637, provides several tools for creating models of autonomously controlled logistic systems. To evaluate such models, the ALEM framework is extended to include a simulation component. As the ALEM Models cannot run directly within simulation software, they are transformed using principles of the Model Driven Architecture. To enable the transformation several open source tools can be applied. This article evaluates a selection of such tools with the aim of integrating them into ALEM.

Dynamics and complexity of today`s production systems bring established approaches for production planning and control to their limits. Accordingly, developing new concepts and methods is a key point for research in this area. The combination of a decentralized control structure and innovative methods from the field of artificial intelligence seems promising here. Open source tools have proven their applicability to implement those methods. They are disposable and can be flexibly adapted to many problems. This contribution introduces an approach for the decentralized control of a shop floor. Here, artificial neuronal networks are used as adaptive control instruments. The simulation of these networks is performed with the open source tool Stuttgart Neural Network Simulator (SNNS) and its successor Java Neural Network Simulator (JNNS).