Statistical Modeling and Optimization of Surface Roughness for PLA and PLA/Wood FDM Fabricated ItemsPages 38-44
Nikolaos Fountas Abstract:
During last decades fused deposition modeling (FDM) has emerged as a widely
applied additive manufacturing technology for numerous engineering
applications. The present work investigates the effects of two independent
variables during FDM fabrication of conventional polylactic acid (PLA) and
organic biocompatible composite material with coconut flour (PLA/w) on
mean surface roughness (Ra) of fabricated items. The parameter optimization
adopts a customized response surface (RSM) design, based on an L9
orthogonal array. The independent variables investigated, were nozzle
temperature, NT (oC) and layer thickness, LT (mm) whilst regression models
for Ra concerning both materials; PLA and PLA/W, were developed to
correlate the independent parameters. Proper analysis was preceded, based
on response surface analysis through contour plots. The regression models
were further utilized as objective functions to minimize Ra for both filament
materials with the use of grey-wolf optimization genetic algorithm (GWO) Keywords:Fused deposition modeling (FDM),
Polylactic acid (PLA),
Composite PLA/wood,
Mean surface roughness,
Response surface design,
Genetic algorithm
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