2012
DOI: 10.1016/j.cirpj.2011.08.003
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An investigation on sliding wear of FDM built parts

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Cited by 131 publications
(71 citation statements)
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References 17 publications
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“…More specifically, surface roughness modelling is more extensive in ME, with the analytical approach of [124], the numerical of [125] and the empirical ones of [126][127][128]. Topology and dimensional accuracy issues have been modelled in [129,[132][133][134] using analytical methods, whereas in [125,135,136] numerical ones have been used and in [137][138][139][140][141] the empirical approach has been followed. Also, the dimensional deviations, caused by changes made in layer thickness and deposition angle, are analytically modelled in [129].…”
Section: Materials Extrusionmentioning
confidence: 99%
See 1 more Smart Citation
“…More specifically, surface roughness modelling is more extensive in ME, with the analytical approach of [124], the numerical of [125] and the empirical ones of [126][127][128]. Topology and dimensional accuracy issues have been modelled in [129,[132][133][134] using analytical methods, whereas in [125,135,136] numerical ones have been used and in [137][138][139][140][141] the empirical approach has been followed. Also, the dimensional deviations, caused by changes made in layer thickness and deposition angle, are analytically modelled in [129].…”
Section: Materials Extrusionmentioning
confidence: 99%
“…Reference number KPI Process/Part parameter (Variable) [137] Tensile strength Air gap, raster orientation, other parameters [124] Surface roughness Surface angle, layer thickness, cross-sectional shape of the filament, overlap interval [125] Build time, surface roughness Part deposition orientation, surface roughness [126] Surface roughness Layer thickness, build orientation [127] Surface roughness Layer thickness [128] Surface roughness Layer thickness, orientation, raster angle, raster width, air gap [129] Dimensional deviations Layer thickness, deposition angle [130] Residual stresses, part distortions Scan speed, layer thickness, tool path width [131] Dimensional accuracy Layer thickness, part orientation, raster angle, air gap and raster width [132] Mechanical properties Building direction, number of contours [133] Bonding quality among polymer filaments Heating/cooling rates [134] Mechanical properties Structural parameters [135] Mechanical and thermal phenomena Tool path patterns [136] Material flow through liquefier Temperature, velocity, drop of pressure [138] Compressive stress Layer thickness, part build orientation, raster angle, raster width and air gap [139] Tensile, flexural and Impact strength Layer thickness, orientation, raster angle, raster width, air gap [140] Sliding wear Layer thickness, part build orientation, raster angle, raster width and air gap [141] Elasticity, flexibility Air gap, raster angle, raster width, layer thickness [142] Build time Acceleration of scan head, part complexity, path planning…”
Section: Materials Jettingmentioning
confidence: 99%
“…From the scanning electron microscope (SEM) images, wear surfaces and internal structures of the specimens were evaluated. In separate studies, Equbal et al (2010) and Sood et al (2012) focused their investigation on understanding the effect of five important parameters such as layer thickness, part build orientation, raster angle, raster width, and air gap on the sliding wear of test specimen. Microphotographs were used to explain the mechanism of wear.…”
Section: Introductionmentioning
confidence: 99%
“…To develop models based on only the given data, several well-known computational intelligence (CI) methods such as artificial neural networks (ANNs), fuzzy logic, adaptivenetwork-based fuzzy inference system, genetic programming (GP) and support vector regression (SVR) have been applied to formulate the relationship between output and input process variables of the FDM process [12][13][14][15][16]. Among these methods, GP possesses the ability to evolve models structure and its coefficients automatically [12,[17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…The FDM process to be modelled is referred from an earlier study conducted on an investigation on sliding wear of FDM built parts [13]. The process input variables considered are layer thickness (x 1 ), orientation (x 2 ), raster angle (x 3 ), raster width (x 4 ) and air gap (x 5 ) and other factors such as part fill style, contour width and visible surface are fixed.…”
Section: Introductionmentioning
confidence: 99%