For manufacturers of high-tech multi-disciplinary systems such as semiconductor equipment, the effort required for integration and system testing is ever increasing, while customers demand a shorter time-to-market. This book describes how executable models can replace unavailable component realizations, enabling early integration and system testing. Using a range of model-based techniques, system level problems can be detected earlier, resulting in lower costs, less rework, and a shorter time-to-market. By coupling the models to the available component realizations in a real-time environment, the system level behavior can be tested months before the complete system is realized. An industrial application clearly shows the practical applicability and the potential benefits of using such models. To determine whether these benefits outweigh the necessary investments in modeling, a quantitative decision making process is proposed. The practical illustration of how model-based techniques from academic theory can be applied in industrial practice will interest both engineers and managers looking for new ways to speed up and reduce the costly rework in their system development process.
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For manufacturers of high-tech multi-disciplinary systems such as semiconductor equipment, the effort required for integration and system testing is ever increasing, while customers demand a shorter time-to-market. This book describes how executable models can replace unavailable component realizations, enabling early integration and system testing. Using a range of model-based techniques, system level problems can be detected earlier, resulting in lower costs, less rework, and a shorter time-to-market. By coupling the models to the available component realizations in a real-time environment, the system level behavior can be tested months before the complete system is realized. An industrial application clearly shows the practical applicability and the potential benefits of using such models. To determine whether these benefits outweigh the necessary investments in modeling, a quantitative decision making process is proposed. The practical illustration of how model-based techniques from academic theory can be applied in industrial practice will interest both engineers and managers looking for new ways to speed up and reduce the costly rework in their system development process.
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