Combinatorial Design Optimization of Automotive Systems by Connecting System Architecture Models with Parts Catalog

Performing system-level trade studies during the design of complex systems has many benefits in terms of performance, reliability, and cost. However, current engineering practices often do not facilitate system-level trade studies because system specifications and requirements are not connected to analytical models that are used to predict performance and cost. To bridge the gap, authors have created a bridge between system architecture models and engineering analyses. This work extends the bridge between the system modeling language (SysML) and engineering analyses to support the use of parts catalogs from system architecture models. Complex systems such as automobiles are seldom created from scratch. Rather, there are many off-the-shelf parts and subsystems available. Combined with the bridge between SysML and engineering analyses, parts catalog data available from system models enables evaluating many different configurations of a system and identifying best designs. The technical approach is demonstrated using an automobile brake design example. The integrated approach allowed generating a large number of design configurations and evaluating those using engineering analyses. Multidimensional point cloud visualization techniques were applied to identify trade-offs between cost and system performance. It is discussed how the interactive point cloud visualization technique can be used to perform requirements change impact analysis