Performance evaluation of warping characteristic of fused deposition modelling process

Abstract

In recent years, fused deposition modelling (FDM) is gaining more popularity due to its distinct advantages in terms of cost-effectiveness, lower build times, and flexibility. Compared to other 3-D printing processes such as SLS, this process does not use any kind of high-intensity laser power to build functional parts out of CAD models and, hence, makes the process much simpler, cheaper, and adaptable. Past studies reveal that productivity of the FDM process can be further increased by effectively controlling its process parameters such as layer thickness, part orientation, extrusion temperature, and so on. In this regard, many authors have investigated the optimal parameter settings for improving part strength, surface finish, wear, and fatigue properties of FDM made prototypes. However, warping performance behavior has got very recent attention due to complex heat transfer mechanism involved during this process. Experimental investigations are necessary to understand the deformation behavior of prototypes. In addition, the quantification and optimization of warp deformation along with dimensional error poses a challenging multi-objective optimization problem. Therefore, this work proposes an evolutionary system identification (SI) approach to explicitly quantify the warp deformation and dimensional error based on the four inputs such as line width compensation, extrusion velocity, filling velocity, and layer thickness of FDM prototypes. The two models' performance analysis comprising of error metrics evaluation, cross-validation, and hypothesis tests is performed to validate its robustness. The analysis concluded that the layer thickness and extrusion velocity influence the warp deformation and, while filling velocity and line width compensation, influences the dimensional error the most.

Material extrusion‐based additive manufacturing of polypropylene: A review on how to improve dimensional inaccuracy and warpage

“…Irreversible thermal strain that is formed during the solidification of a strand and causes residual stresses was determined to be critically dependent on the printing orientation and the layer thickness . Low layer thicknesses result in elevated thermal strains and therefore high residual stresses and warpage, which is in agreement with simulation results …”

Assessment of Crystallinity Development during Fused Filament Fabrication through Fast Scanning Chip Calorimetry

“…Crystallization of the extruded polymer melt upon deposition from the print nozzle will lead to anisotropic shrinkage and part warpage due to a build-up of internal stresses. This can severely disturb the dimensional stability of the printed part [15][16][17]. To provide the final printed part with adequate mechanical strength, polymer chains should diffuse and re-entangle across the interface between successively deposited layers to successfully weld them together [18].…”

Design of robust battery capacity model for electric vehicle by incorporation of uncertainties

“…Sophisticated modelling methods based on hybrid frameworks [40,41], advanced neural computing models [42][43][44][45][46] and genetic programming frameworks [47][48][49] are required to quantify the multi-physics mechanisms for an improved battery design. There could be another factor such as the sudden mechanical impact (buckling, shearing and compression tests) which can also influence the battery capacity estimation.…”

“…The interactions between these mechanisms are hardly studied as it is complicated. Sophisticated modelling methods based on hybrid frameworks [40,41], advanced neural computing models [42][43][44][45][46] and genetic programming frameworks [47][48][49] are required to quantify the multi-physics mechanisms for an improved battery design. .00000000000000e-001, 0.00000000000000e+000, 3.00000000000000e-001, 5.00000000000000e-001, 1.00000000000000e+000, 1.00000000000000e+000, 4.00000000000000e-001, 1.00000000000000e+000, 3.00000000000000e-001, 4.00000000000000e-001, 2.00000000000000e-001, 0.00000000000000e+000, 3.00000000000000e-001, 6.00000000000000e-001, 2.00000000000000e-001, 5.00000000000000e-001, 4.00000000000000e-001, 8.00000000000000e-001, 5.00000000000000e-001, 8.00000000000000e-001, 3.00000000000000e-001, 6.00000000000000e-001, 5.00000000000000e-001, 1.00000000000000e+000, 3.00000000000000e-001, 1.00000000000000e+000, 4.00000000000000e-001, 6.00000000000000e-001, 2.00000000000000e-001, 6.00000000000000e-001, 4.00000000000000e-001, 8.00000000000000e-001, 2.00000000000000e-001, 1.00000000000000e+000, 4.00000000000000e-001, 6.00000000000000e-001, 4.00000000000000e-001, 1.00000000000000e+000, 2.00000000000000e-001, 8.00000000000000e-001, 0.00000000000000e+000, 1.00000000000000e+000, 4.00000000000000e-001, 4.00000000000000e-001, 5.00000000000000e-001, 6.00000000000000e-001, 3.00000000000000e-001, 8.00000000000000e-001, 3.00000000000000e-001, 1.00000000000000e-001, 5.00000000000000e-001, 9.99999999999999e-002, 1.00000000000000e-001, 3.00000000000000e-001, 1.00000000000000e-001, 1.00000000000000e-001, 9.99999999999999e-002, 9.99999999999999e-002, 1.00000000000000e-001, 9.99999999999999e-002, 1.00000000000000e-001, 9.99999999999999e-002, 1.00000000000000e-001, 9.99999999999999e-002, 1.00000000000000e-001, 9.99999999999999e-002,…”