Adaptive rapid prototyping/manufacturing for functionally graded material-based biomedical models

In this paper, research on developing adaptive rapid prototyping/manufacturing (RP/M) algorithms for functionally graded material (FGM)-based biomedical models is reported. Non-uniform rational B-spline and FGM-based features have been proposed to present the models. Innovative algorithms for tool p...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of advanced manufacturing technology Vol. 65; no. 1-4; pp. 97 - 113
Main Authors Jin, G. Q., Li, W. D.
Format Journal Article
LanguageEnglish
Published London Springer-Verlag 01.03.2013
Springer Nature B.V
Subjects
Adaptive algorithms
Adaptive control
Algorithms
Biomedical materials
CAE) and Design
Computer-Aided Engineering (CAD
Engineering
Functionally gradient materials
Industrial and Production Engineering
Mechanical Engineering
Media Management
Nozzles
Optimization
Original Article
Rapid prototyping
Tool path
Rapid prototyping/manufacturing
Functionally graded material
NURBS
Online AccessGet full text

Cover

More Information
Summary:In this paper, research on developing adaptive rapid prototyping/manufacturing (RP/M) algorithms for functionally graded material (FGM)-based biomedical models is reported. Non-uniform rational B-spline and FGM-based features have been proposed to present the models. Innovative algorithms for tool path optimization in RP/M have been developed, including: (1) a mixed tool path algorithm to generate contour/offset tool paths to represent varying material composition along the boundary of each sliced layer of a model and zigzag tool paths to present the internal area of a single material to simplify computing and processing and (2) adaptive algorithms to control the RP/M nozzle/print head to minimize the build time of each sliced layer according to the geometrical characteristics of the model. Case studies of FGM-based biomedical models have been used to verify and demonstrate the performance of the research in terms of algorithm effectiveness.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-012-4153-9