Introduction of Simulation Learning and Optimization to Support Engineering Design

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The objective of this research is to integrate simulation, learning, and optimization to form an Adaptive and Interactive Modeling System (AIMS) to support multiple perspectives at different stages for design and concurrent engineering. Given a database of examples collected from simulations or experiments, and a set of modeling objectives and design objectives, AIMS performs multi-objective optimization at both model formation and utilization phases. By varying modeling objectives, such as speed, accuracy, and comprehensibility, AIMS can produce layered models to meet the changing needs at different stages of design. By treating different life-cycle concerns as competing design objectives, AIMS can support systematic incorporation of multiple perspectives for concurrent engineering. This research represents a significant and meaningful integration between artificial intelligence based techniques and conventional engineering methods to further advance the basic research in design automation.