OptMeSys — Cross-domain optimization for the automated redesign of mechatronic actuation systems

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Mechatronic actuation systems are the basis for the automation of a wide variety of tasks. In their development, it is possible to make use of existing products, since the changes and thus the redesign of predecessor products, such as due to customer-specific requirements, are comparatively small. Reusing existing, implicit knowledge from previous product development cycles and optimization iterations could significantly reduce the effort in redesign, but is strongly impeded by the lack of methods for its structured acquisition, linking and provision. Instead, it is necessary to regather the information from the individual domains of mechanics, electronics, and informatics, the cross-domain function and behavior models must be recreated or manually adapted, and the optimization problems have to be set up and solved once more. Thus, the goal of this research project is to automate the individual steps of the product development process, which are necessary for the cross-domain optimization of mechatronic actuation systems. A consistent, knowledge-based engineering method intends to avoid time-consuming redesign iterations. This requires the development of suitable automation processes for the identification of domain-specific product characteristics, for the model-based mapping of cross-domain relationships, and for the linking of diverse information and models, such as requirements, solution principles, and product characteristics with system and behavior models, among others. The use of text mining, ontologies, graph databases and system modeling as well as their harmonization should enable an automated definition of optimization problems for the model-based design of time-variant mechatronic systems. In order to be able to solve the resulting complex optimization problems efficiently, this research project focuses on novel optimization strategies using knowledge from previous product development steps and optimizations. Besides the selection of suitable metaheuristic algorithms and their settings in combination with methods to increase their efficiency, such as metamodel-based optimization strategies, the reuse of knowledge from intermediate solutions obtained from previous optimization aims at significantly reducing the optimization problem complexity. In addition to representative use cases accompanying the development of the method during the different project phases, such as electric window regulators and actuation systems to align extruders and platforms in 3D printers, final studies on further mechatronic products will demonstrate its transferability, potential and limitations with regard to the type and degree of changes confronted in redesign.