Prediction of dimensional accuracy in fused deposition modelling: a fuzzy logic approach

Equbal, Asif; Sood, Anil K.; Mahapatra, S.S.

doi:10.1504/ijpqm.2011.037730

Cited by 44 publications

(27 citation statements)

References 22 publications

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“…Part orientation plays an important role in the surface finish [2][3][4][5], dimensional accuracy [6][7][8][9][10], cost [11,12] and mechanical behaviour. It has been reported a dependence of the mechanical behaviour of AM parts on its orientation in the building chamber.…”

Section: Introductionmentioning

confidence: 99%

Mechanical property characterization and simulation of fused deposition modeling Polycarbonate parts

et al. 2015

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Section: Introductionmentioning

confidence: 99%

Mechanical property characterization and simulation of fused deposition modeling Polycarbonate parts

et al. 2015

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“…Equabal et al [21] present a Fuzzy classifier and neural-net implementations for the prediction of the accuracy within the Fused Deposition Modeling (FDM) process under varying process parameters. They achieve a mean absolute relative error of 5.5% for the predictor based on Fuzzy logic.…”

Section: Accuracymentioning

confidence: 99%

Scanned Image Data from 3D-Printed Specimens Using Fused Deposition Modeling

Baumann

Eichhoff

Roller

2017

Data

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Abstract:This dataset provides high-resolution 2D scans of 3D printed test objects (dog-bone), derived from EN ISO 527-2:2012. The specimens are scanned in resolutions from 600 dpi to 4800 dpi utilising a Konica-Minolta bizHub 42 and Canon LiDE 210 scanner. The specimens are created to research the influence of the infill-pattern orientation; The print orientation on the geometrical fidelity and the structural strength. The specimens are printed on a MakerBot Replicator 2X 3D-printer using yellow (ABS 1.75 mm Yellow, REC, Moscow, Russia) and purple ABS plastic (ABS 1.75 mm Pink Lion&Fox, Hamburg, Germany). The dataset consists of at least one scan per specimen with the measured dimensional characteristics. For this, software is created and described within this work. Specimens from this dataset are either scanned on blank white paper or on white paper with blue millimetre marking. The printing experiment contains a number of failed prints. Specimens that did not fulfil the expected geometry are scanned separately and are of lower quality due to the inability to scan objects with a non-flat surface. For a number of specimens printed sensor data is acquired during the printing process. This dataset consists of 193 specimen scans in PNG format of 127 objects with unadjusted raw graphical data and a corresponding, annotated post-processed image. Annotated data includes the detected object, its geometrical characteristics and file information. Computer extracted geometrical information is supplied for the images where automated geometrical feature extraction is possible.

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“…Orientation refers to the building direction regarding the part in which the slices are built [3,19,38]. Determination of the optimal part orientation is a fundamental problem in layered manufacturing [2,19,38], since the building direction has a significant effect on many key characteristics which determine the final part's cost [15,27], dimensional accuracy [16,[41][42][43]50], surface roughness [6,34,48,49] and even the part's mechanical properties [1,4,11,20,26,28,32,36,44]. Selection of an optimum part's building orientation is a very important factor as it improves dimensional accuracy and surface finish and reduces building time and support structures, optimizing the final cost of the physical part [2,12,19,35,38].…”

Section: Additive Manufacturingmentioning

confidence: 99%

“…Some of these parameters are: the distance between extruded filaments, width of the filaments, layer thickness, the lay-down pattern of each layer, the thickness of the outer shell when producing low or high density parts, etc. [4,5,16,19,26,43,44]. This implies that the correct building strategy has a significant effect on both the properties and performance of the produced part.…”

Section: Fused Deposition Modellingmentioning

confidence: 99%

Sustainability in extrusion-based additive manufacturing technologies

et al. 2016

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Growing environmental and social concerns about human society's impact on the natural environment have been pushing sustainable development issues into the front line of public policies. The degradation of natural resources has been aggravated by several other factors: the actual lifestyle of consumer societies, the rapid growth of emerging countries, rising inequalities among regions, and the reduction of the life cycle time for each product requiring a high consumption of limited resources. Sustainable industrial practices can contribute to the development of more sustainable products and processes. It is critical to apply eco-design principles and develop greener products and production processes, reducing impacts associated with its production and consumption. An environmental impact assessment should be taken into account from the early design and production phases, through all the stages of a product's life until disposal. As public interest in additive manufacturing grows, its increasing usage for the production of final parts can support a drive towards more sustainable manufacturing processes. To introduce sustainability awareness during extrusion-based additive manufacturing productions, a study of the production of a part in terms its building orientation and internal filling, regarding the production time, energy consumption and end-of-life scenarios is considered. By combining the additive processes with eco-design, a higher awareness is possible, which results in added value to the produced parts while maintaining the part's objective performance.

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Prediction of dimensional accuracy in fused deposition modelling: a fuzzy logic approach

Cited by 44 publications

References 22 publications

Mechanical property characterization and simulation of fused deposition modeling Polycarbonate parts

Mechanical property characterization and simulation of fused deposition modeling Polycarbonate parts

Scanned Image Data from 3D-Printed Specimens Using Fused Deposition Modeling

Sustainability in extrusion-based additive manufacturing technologies

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