A bottom-up function-based synthesis approach for complex mechanisms based on clustering rules. Issue 5 (3rd September 2019)

• Record Type: Journal Article
• Authors: Li, Yu-Tong; Wang, Yu-Xin
• Is Part Of: Mechanics based design of structures and machines. Volume 47:Issue 5(2019)
• Page Start: 555
• Page End: 567
• Publication Date: 2019-09-03
• Subjects: Complex mechanisms -- type synthesis of mechanisms -- bottom-up synthesis -- grammar-based synthesis; Structural analysis (Engineering) -- Periodicals; Structural design -- Periodicals; 624.17
• DOI: 10.1080/15397734.2019.1578666
• Languages: English
• ISSNs: 1539-7734

Abstract

Abstract: The function-based synthesis is a major approach for the artificial intelligence (AI)-based type synthesis of complex mechanisms. Due to a lack of knowledge to support functional reasoning from the behaviors of constituent basic mechanisms to the whole functional behaviors of complex mechanisms, the AI-based type synthesis of compound mechanisms is still a hard challenge. In this article, a grammar-based synthesis approach is proposed for carrying out the type synthesis of complex mechanisms. The grammar-based synthesis rules, in which the functional requirements and the topological connections among functional members are included, are defined with the aid of nine kinds of common functional requirements that are primarily exhibited by complex mechanical systems. Through assigning a function as well as topological connections to each element in the graphic carrier according to the grammar-based synthesis rules, the type synthesis process for complex mechanisms is carried out automatically. Since the divergence creative design technique is applied, this system can efficiently expand the synthesis solution space of complex mechanisms, and more innovative design schemes including generalized mechanisms can be figured out. For extremely complex mechanisms, though dividing the design problem into several smaller parts, and carrying out grammar-based synthesis process to each smaller part, respectively, then combing the generated schemes from each smaller part together, the function-based synthesis for extremely complex mechanisms can also be solved. Communicated by Kristopher Wehage.