Simulation

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).

Considering new challenges in logistics planning and supply processes, companies are forced to plan their supply chains relating to more flexibility, effectiveness and cost reduction. Today, supply processes are planned once and never changed due to new demand or capacity situations. This article will introduce a new approach of integrated logistics planning combining demand and capacity planning (DCP) with supply planning concepts. The result is an Logistic Assistance System (LAS) as a new generation of Digital-Logistics-Software, which allows dynamic supply chain planning by providing DCP-functionalities with a simulation based approach. The developed simulation component is able to handle the complexity of high-value-added branches with efficient algorithms, to forecast the supply chain behaviour (future stock range, dynamic processes and resulting costs) taking different scenarios into account. It has been demonstrated to produce convincing results in different projects.

Virtual Engineering is an important tool to verify and optimise products in early design phases. For the development of innovative complex technical systems the applied models should comprehend the most important product properties. Up to now there are deficits in modelling and evaluating the acoustic behaviour of technical products although this is important in areas with rigid ergonomic and comfort requirements, e.g. in the consumer goods and automobile industries. In order to overcome these deficits, at the Ilmenau University of Technology a flexible audiovisual stereoscopic projection system (FASP) has been constructed. Consequently, investigations of the sound effects of machine components, machines, cars and other products as well as psycho-acoustic assessments of designed products in a virtual environment can be realized.

This article describes an opportunity to model actors and systems in various business processes into an overall model by using the technique of networking. To achieve this goal, an algorithm is introduced. Next, different metrics based on social network analysis, are described. These metrics are able to expose parts of the network which have a huge utilization and therefore the underlying process itself. With this technique it is possible for project leaders, managers and decision makers to analyze the processes for flaws, finding out capacities and to build new project teams together (staffing).

Shorter product life cycles and rising demands for product variants increasingly lead to capacity demand fluctuations and result in unsatisfactory degrees of assembly system capacity utilization. By offering additional assembly capacities to their customers, manufacturers of assembly systems can establish a promising new business model. If the assembly system manufacturer takes over the responsibility for operating assembly systems, it has to be decided which HR option, recruiting own employees or leasing personnel from a temporary employment agency is best suited for this new business model. In this article a System Dynamics model is introduced that can be used for the assessment of such alternative HR concepts.

Additional to the consideration of technological and organisational aspects as well personnel adjustments have to be considered in time during the introduction of new manufacturing technologies. Reasons for a systematic personnel development are technological changes, e.g. the introduction of new products and manufacturing processes or a modified manufacturing programme. Especially the number and the qualification of the employees who are affected by these changes have to be adjusted to the new requirements. The method of the personnel-oriented technology calendar which is presented in this article provides a systematic and targeted personnel development planning. The approach is demonstrated by means of an application example.