Application of the Mechatronic Design Quotient (MDQ) for Intelligent Design and Evolutionary Design of Mechatronic Systems

Abstract

Mechatronic systems are integrated electro-mechanical systems. Intelligent mechatronic systems possess computational intelligence with capabilities such as perception, learning, reasoning, and making inferences from incomplete information. A mechatronic system will consist of many different types of interconnected components and elements. The dynamic coupling between components means an accurate design of the system should consider the entire system as a whole rather than using single-criterion and sequential design methodologies, which are traditional. However, in view of the system complexity, it is difficult to adopt a wholistic approach in practice. The presentation will explore a multi-criteria and concurrent approach to mechatronic design and evaluation. A design formulation and criteria based on the concepts of mechatronic design quotient (MDQ) will be introduced for this purpose. Human experience on mixed systems and interactions between criteria will be taken into account by applying techniques of soft computing for the aggregation of criteria. The use of artificial intelligence and evolutionary computing in the design of mechatronic systems may be viewed as an attempt to mimic natural intelligent design and natural evolution of a biological system (e.g., human), albeit in a greatly simplified form. The talk will address these concepts as well. In particular, intelligent design is applicable when human intelligence is used in the design process. On the other hand, evolutionary design is applied when evolutionary computing is used in the design process. Several industrial applications of intelligent mechatronics have been designed and developed in the Industrial Automation Laboratory under the direction of the speaker.