Automatic generation of disassembly sequences and exploded views from solidworks symbolic geometric relationships

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

Costa, CM (Autor) Outra; Germano Veiga (Autor) FEUP; Armando Jorge Sousa (Autor) FEUP; Rocha, LF (Autor) FEUP; Eugénio Oliveira (Autor) FEUP; Henrique Lopes Cardoso (Autor) FEUP; Thomas, U (Autor) Outra

Ata de Conferência Internacional

Título: 2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Páginas: 211-218

Indexação

ISI Web of Science

Scopus - 8 Citações

Outras Informações

ID Authenticus: P-00N-ZQJ

DOI: 10.1109/icarsc.2018.8374185

Abstract (EN): Planning the optimal assembly and disassembly sequence plays a critical role when optimizing the production, maintenance and recycling of products. For tackling this problem, a recursive branch-and-bound algorithm was developed for finding the optimal disassembly plan. It takes into consideration the traveling distance of a robotic end effector along with a cost penalty when it needs to be changed. The precedences and part decoupling directions are automatically computed in the proposed geometric reasoning engine by analyzing the spatial relationships present in SolidWorks assemblies. For accelerating the optimization process, a best-first search algorithm was implemented for quickly finding an initial disassembly sequence solution that is used as an upper bound for pruning most of the non-optimal tree branches. For speeding up the search further, a caching technique was developed for reusing feasible disassembly operations computed on previous search steps, reducing the computational time by more than 18%. As a final stage, our SolidWorks add-in generates an exploded view animation for allowing intuitive analysis of the best solution found. For testing our approach, the disassembly of two starter motors and a single cylinder engine was performed for assessing the capabilities and time requirements of our algorithms. © 2018 IEEE.

Idioma: Inglês

Tipo (Avaliação Docente): Científica