151. Volumetric shrinkage prediction in fused deposition modelling process - ANFIS modelling approach
- Author
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Ahmed A. D. Sarhan, Yusuf S. Dambatta, Mehdi Hourmand, and Ibrahem Maher
- Subjects
Adaptive neuro fuzzy inference system ,Manufacturing technology ,Computer science ,Orientation (computer vision) ,020502 materials ,Mechanical Engineering ,Process (computing) ,Mechanical engineering ,02 engineering and technology ,Structural geometry ,021001 nanoscience & nanotechnology ,Industrial and Manufacturing Engineering ,0205 materials engineering ,Mechanics of Materials ,Deposition (phase transition) ,0210 nano-technology ,Safety, Risk, Reliability and Quality ,Shrinkage ,Volumetric shrinkage - Abstract
Fused deposition modelling (FDM) is a type of additive manufacturing technology which is being used to manufacture prototypes and functional parts. However, the volumetric shrinkage limits the functionality of the manufactured prototypes. Accurately predicting the volumetric shrinkage will diversify the applicability of this manufacturing technology because the volumetric error could be eliminated at the product specification/development stage. Also, the volumetric shrinkage prediction in the process will enable for an in-process adjustment and proper selection of the machine setting. This work involves using the layer thickness, orientation angle and structural geometry as parameters to predict the volumetric shrinkage. The prediction of the shrinkage in the FDM prototypes along both the XZ and YZ-axis was done using ANFIS. The experimental test result validates the effectiveness of the constructed ANFIS model, which has about 3.15% average prediction error. The comparison between the manufactured hollow shapes also gives the best input settings for manufacturing of the hollows in the components.
- Published
- 2019