Simulation-Based Early Warning Systems As A Practical Approach For The Automotive Industry

ABSTRACT Simulation-based Early Warning Systems (SEWS) support proactive control of real material flow systems. In consequence of real or potential state changes, proactive control (unlike reactive control) makes foresighted and targetoriented acting possible. Starting from the definition of SEWS their architecture and the requirements for design of SEWS are discussed. The compliance with simulatorindependency is one important facet. Basically, this is achieved by the use of Web Services, XML and XSD (XML Schema Definition). One key component of SEWS are online simulation models which are initialized with the current system state of a real system. The utilization of RFID technology to generate information about current system states improves the quality of simulation-based forecasting. Example applications from the automotive industry show the benefits of SEWS. INTRODUCTION Decision support with long time horizon is one classic application of simulation models. Different parameters of planned systems have to be evaluated based on simulation results and planners endeavour to optimize them. In this standard application simulation models are offline, i.e. the models are not directly linked with the real system. Usually, the developed simulation models are not used upon completion of the decision-making process. By contrast, short time decisions have to be made constantly during controlling and managing processes of existing systems. Nowadays, the complexity of such systems is increasing as well as the need of their efficient control and management. There are two main classes of control strategies: simulation-based strategies and strategies based on heuristic rules and mathematical equations. Comparing both the simulation is based on the current state of the real system and provides decision makers higher quality support. Simulation-based Early Warning Systems (SEWS) support proactive control of real material flow systems. In consequence of real or potential state changes, proactive control (unlike reactive control) makes foresighted and target-oriented acting possible (Banks 1998). The usage of early warning systems to control complex systems like material handling systems makes grand demands on simulation models and system environment. One requirement is that potential users of SEWS do not have to parameterize, start or analyze simulation runs. That means the simulation model has to be embedded invisibly into a SEWS and special programming constructs are required that allow simulation models to be integrated in a production control or operating system (Banks 2000). The main objective of this paper is to describe the design and architecture of SEWS with regard to the independency of integrated simulators. The following section gives a description of Simulation-based Early Warning Systems including a suggested architecture. After that, requirements for the design are pointed out. Communication principles between SEWS-components and possibilities to guarantee simulator independency are discussed in the next section. Also, methodologies for collecting state data about the real system and their influence on the initialization process is pointed out. Finally, the paper presents applications from the automotive industry and gives a conclusion. ARCHITECTURE OF SIMULATION-BASED EARLY WARNING SYSTEMS Generally, early-warning systems are mechanisms deployed to inform persons about risk of imminent danger at an early stage. So the purpose is to enable the user or the deployer of the early-warning system to prepare for the danger and act accordingly to mitigate the effects or to even avoid the

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