Design optimization of machines and manufacturing plants on the basis of component-oriented behavior models

• Applicant: Dr.-Ing. Werner Herfs
• Subject Area: Production Systems, Operations Management, Quality Management and Factory Planning
• Term: from 2014 to 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 254897330

Machines and manufacturing plants are mechatronic systems. Their design requires the close cooperation of several disciplines. The aim of mechatronic system design is to create, evaluate and optimize different conceptual solutions at an early stage considering the beforehand specified requirements. The conceptual mechatronic solution is then the basis for the work in subsequent disciplines. Expressive design models allow to reduce realization-time and to increase product quality.The aim of the project is to develop a new methodology for optimizing the mechatronic behavior of machines and manufacturing plants with regards to technical and managerial requirements. On the basis of mathematical optimization methods those mechatronic components and dimensioning parameters are searched that optimally fulfill the requirements. The subsequent step is then to compare the competing designs with optimal parameterization.Models of behavior, requirements and component data are the basis optimization. For behavioral modeling a library with electromechanical, electrical, mechanical, hydraulic and pneumatic components is developed. In this context the question is addressed, how models should be designed that can be parameterized in the early phase, but at the same time deliver expressive results for optimization. In addition, methods are developed to model requirements, e.g. in terms of cost, cycle time and energy consumption, and to relate these to the behavior models.The potential design space of all parameter and component combinations is usually very large. Therefore, the search for components and dimensioning parameters requires a robust and efficient optimization strategy. On the one hand, this optimization strategy consists of an adequate combination of global and local solver algorithms. On the other hand, the strategy comprises engineering know-how to reduce the search space significantly.The developed models are used to build-up a reusable library and the methods are implemented in a prototype. The models and the implementation will be tested subsequently in several test cases.

• DFG Programme: Research Grants
• Participating Person: Professor Dr.-Ing. Christian Brecher