A Design Optimization Framework for Multidisciplinary Mechatronic Systems
Sprache des Titels:
Proceedings of TMCE 2016 - Tools and Methods for Competitive Engineering
Designing complex mechatronic systems is a challenging task; engineers from different disciplines have to work concurrently to find an optimal solution. In this paper a design optimization framework is presented to support the optimum design of mechatronic systems. It combines system modeling with a genetic multi criteria optimization algorithm and a GUI to manage the automated simulation and validation processes as well as the finding of the optimal solutions. The developed system models are computationally inexpensive, but answer the system questions with satisfying accuracy. In this way, design engineers can compare various solution concepts by their Pareto optimal representations in the design objectives domain. These developed system models should be reused and refined in later design phases for various purposes: To provide basic system behavior information for non-experts, to investigate design parameter changes, and to check the validity of these system models by comparing their optimal designs with those obtained in the detail design phases. These system models can be augmented to answer further system questions as a basis for the implementation of automated simulation processes. An intuitive graphical user interface was developed, which guides users through the simulation processes, allows design parameter changes, investigates the impact on the systems behavior, and initiates and manages all the required model- and parameter exchanges between several simulation tools. The approach was developed and successfully tested on a pick and place robot system.