Complexity Analysis and Structural Optimization for Architecture Models of Mechatronic Systems

Sammanfattning: The design and development of mechatronic system are becoming an increasingly complex task due to the numerous disciplines involved, rapidly increasing scales, and the integration issues of different domains and technologies. The structural complexity of the architecture model design decides the quality of system design in many aspects: the scalability of the system design; usage of allocated resources which influences the computational overhead, etc. It is a measurable characteristic of the mechatronic system. Therefore, finding efficient algorithm to measure and analyze the structural complexity of the architecture design model serves the purpose of optimizing and improving the design of the overall mechatronic system.  In this research project we abstract the Design Structure Matrix (DSM) from the system achitecture model and adopt a matrix-based approach to quantify the structural complexity of complex mechatronic system from three aspects: 1) the component complexity; 2) the interaction complexity due to the interaction behavior among components and the variety of interfaces; 3) the topology complexity based on the different system architecture patterns. We verify that thisapproach well matches the design regime. We then propose two different approaches: 1) a genetic algorithm-based approach; 2) a hierarchical clustering-based approach to solve the partitioning design problem. These two approaches aim to provide the partitioning strategy of the system architecture model to form a modularized design. This serves the purpose of lowering structural complexity and giving better design performance. We reproduce an existing DSM-based partitioning approach as a contrast to prove the validation of our proposed approaches.  A case study: an autonomous forest machine test platform is performed to verify our proposed complexity analysis and partitioning optimization design framework. We firstly build the corresponding architecture model and measure its structural complexity. The two proposed approaches give us two different partitioning strategies which focus on different aspects of system architecture but both approaches have a good performance. The reproduced approach is not applicable on the case study and needs further modification.