Literature DB >> 33396782

Adaptive Neuro-Fuzzy Inference System for Modelling the Effect of Slurry Impacts on PLA Material Processed by FDM.

Bahaa Saleh1,2, Ibrahem Maher3, Yasser Abdelrhman2, Mahmoud Heshmat2, Osama Abdelaal2,4.   

Abstract

In this research, the effect of water-silica slurry impacts on polylactic acid (PLA) processed by fused deposition modeling (FDM) is examined under different conditions with the assistance of an adaptive neuro-fuzzy interference system (ANFIS). Building orientation, layer thickness, and slurry impact angle are considered as the controllable variables. Weight gain resulting from water, net weight gain, and total weight gain are the predicting variables. Results uncover the accomplishment of the ANFIS model to appropriately appraise slurry erosion in correlation with comparing real data. Both experimental and ANFIS results are almost identical with average percentage error less than 5.45 × 10-6. We observed during the slurry impacts tests that all specimens showed an increase in their weights. This weight gain was finally interpreted to the synergetic effect of water absorption and the solid particles fragmentations immersed within the specimens due to the successive slurry impacts.

Entities:  

Keywords:  3D printing; ANFIS; fused deposition modeling; polylactic acid; slurry impacts

Year:  2020        PMID: 33396782     DOI: 10.3390/polym13010118

Source DB:  PubMed          Journal:  Polymers (Basel)        ISSN: 2073-4360            Impact factor:   4.329


  1 in total

1.  Modeling of the Influence of Input AM Parameters on Dimensional Error and Form Errors in PLA Parts Printed with FFF Technology.

Authors:  Carmelo J Luis-Pérez; Irene Buj-Corral; Xavier Sánchez-Casas
Journal:  Polymers (Basel)       Date:  2021-11-27       Impact factor: 4.329

  1 in total

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