Publication Date:
2023
abstract:
Design For Assembly (DFA) aims at improving product design facilitating
assembly phases via the application of evaluation metrics and design
guidelines. However, DFA analyses are usually performed manually and the
adoption of supporting tool is poor. This paper investigates the application of
algorithms allowing to extract from CAD assembly models the required data to
perform automated DFA analyses, thus providing a tool to support designers'
everyday works. In particular, attributes from geometric feature recognition algorithms,
solids properties and assembly parts' semantics are leveraged and
mapped to the parameters required to accomplish DFA evaluations. The proposed
approach is illustrated on a 3D printer for home use. At first, a manual DFA analysis
has been performed on the product identifying product BOM, components
properties, assembly cycle and times according to models in the literature. Then,
the CAD model of the printer has been processed with some geometric algorithms
to verify the possibility to extract the required data to be used as input to the DFA
analysis. The test case has demonstrated the feasibility of the approach, even if
some design considerations and improvement directions still need the critical
evaluation of the designer.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Design For Assembly; Assembly Semantics; Part Recognition; Feature Recognition
List of contributors:
Bonino, Brigida; Monti, Marina; Giannini, Franca
Book title:
Advances on Mechanics, Design Engineering and Manufacturing IV. JCM 2022
Published in: