A study of melt flow analysis of an ABS-Iron composite in fused deposition modelling process

Nikzad, Mostafa; Syed, Hasan Masood; Sbarski, Igor; Andrew, Groth

doi:10.1016/s1007-0214(09)70063-x

Cited by 146 publications

(82 citation statements)

References 6 publications

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“…An experimental investigation into the same phenomenon was conducted by Venkataraman [79]. Heat transfer to the built material inside the liquefier was theoretically studied by [68,70,72], while a number of authors dealt numerically with the same issue [68,72,75,76].…”

Section: Extrusion Processesmentioning

confidence: 99%

Additive manufacturing methods and modelling approaches: a critical review

Bikas

Stavropoulos

Chryssolouris

2015

Int J Adv Manuf Technol

1,129

443

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Additive manufacturing is a technology rapidly expanding on a number of industrial sectors. It provides design freedom and environmental/ecological advantages. It transforms essentially design files to fully functional products. However, it is still hampered by low productivity, poor quality and uncertainty of final part mechanical properties. The root cause of undesired effects lies in the control aspects of the process. Optimization is difficult due to limited modelling approaches. Physical phenomena associated with additive manufacturing processes are complex, including melting/ solidification and vaporization, heat and mass transfer etc. The goal of the current study is to map available additive manufacturing methods based on their process mechanisms, review modelling approaches based on modelling methods and identify research gaps. Later sections of the study review implications for closed-loop control of the process.

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Section: Extrusion Processesmentioning

confidence: 99%

Additive manufacturing methods and modelling approaches: a critical review

Bikas

Stavropoulos

Chryssolouris

2015

Int J Adv Manuf Technol

1,129

443

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“…In this research, the FDM in AM processes is mainly studied. FDM is a process of layer to layer deposition of extruded material through a nozzle using feedstock filaments from a spool [47], which is an alternative to the conventional manufacturing techniques that enables the direct fabrication of products with complex shapes. FDM process involves heat and mass transfer, thermos-mechanical field and phase changes, which will often has deviations from the design specifications.…”

Section: Additive Manufacturingmentioning

confidence: 99%

“…For example, in [61,118] the initial temperature of the newly deposited filament is assumed to be the same as the nozzle temperature. In [47,119], the filament temperature is assumed to rise to a certain value after entering the melt flow channel. In [120], the input of material accompanied with a heat reservoir is simulated but without a specific expression.…”

Section: Constitutive Modelingmentioning

confidence: 99%

Integration of physically-based and data-driven approaches for thermal field prediction in additive manufacturing

Jin

2018

Materials & Design

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A quantitative understanding of thermal field evolution is vital for quality control in additive manufacturing (AM). Because of the unknown material parameters, high computational costs, and imperfect understanding of the underlying science, physically-based approaches alone are insufficient for component-scale thermal field prediction. Here, I present a new framework that integrates physically-based and data-driven approaches with quasi in situ thermal imaging to address this problem. The framework consists of (i) thermal modeling using 3D finite element analysis (FEA), (ii) surrogate modeling using functional Gaussian process, and (iii) Bayesian calibration using the thermal imaging data. Based on heat transfer laws, I first investigate the transient thermal behavior during AM using 3D FEA. A functional Gaussian process-based surrogate model is then constructed to reduce the computational costs from the high-fidelity, physically-based model. I finally employ a Bayesian calibration method, which incorporates the surrogate model and thermal measurements, to enable layer-to-layer thermal field prediction across the whole component. A case study on fused deposition modeling is conducted for components with 7 to 16 layers. The cross-validation results show that the proposed framework allows for accurate and fast thermal field prediction for components with different process settings and geometric designs. Integration of Physically-based and Data-driven Approaches for Thermal Field Prediction in Additive ManufacturingJingran Li GENERAL AUDIENCE ABSTRACT This paper aims to achieve the layer to layer temperature monitoring and consequently predict the temperature distribution for any new freeform geometry. An engineering statistical synergistic model is proposed to integrate the pure statistical methods and finite element modeling (FEM), which is physically meaningful as well as accurate for temperature prediction. Besides, this proposed synergistic model contains geometry information, which can be applied to any freeform geometry. This paper serves to enable a holistic cyber physical systems-based approach for the additive manufacturing (AM) not only restricted in fused deposition modeling (FDM) process but also can be extended to powder-based process like laser engineered net shaping (LENS) and selective laser sintering (SLS). This paper as well as the scheduled future works will make it affordable for customized AM including customized geometries and materials, which will greatly accelerate the transition from rapid prototyping to rapid manufacturing. This article demonstrates a first evaluation of engineering statistical synergistic model in AM technology, which gives a perspective on future researches about online quality monitoring and control of AM based data fusion principles. iv ACKNOWLEDGEMENTS

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“…Therefore, FDM mechanism on an additive principle by a laying down material in layers and then a plastic filament wire or metal that are used is the wind down from a coil and supplies material to fabricate a model. It is the only 3D printing machinery that uses in several productionsgrade of thermoplastic, so the parts are incomparable in mechanical, thermal and chemical strength [1]. In FDM, one of the most important parts is the filament.…”

Section: Introductionmentioning

confidence: 99%

Characterization and Mechanical Analysis of PCL/PLA composites for FDM feedstock filament

Haq

Rahman

Ariffin

et al. 2017

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract. In this research, characterization, and the mechanical properties of Polycaprolactone (PCL) and Polylactic Acid (PLA) composites with the objective of determining their suitability as biomaterials for an alternative composites material for Fused Deposition Modelling (FDM) was investigated. The percentage of PLA is varies from 10% to 50% by weight. The PCL/PLA composites were prepared by melting and mixing using Brabender Plastograph machine. The characterization of PCL/PLA composites was characterized using Fourier Transform Infrared (FTIR). Meanwhile, the mechanical properties were evaluated are the Tensile, Flexural and Impact. It demonstrate that by the addition of PLA it improve the mechanical properties of PCL and leads to a better processability of PCL/PLA composites. With the decrement of PLA content in PCL/PLA composites the Tensile Strength the Young's Modulus and also the Impact Strength of the composites increased. The highest tensile strength was recorded at 10.00 Mpa and the Young's Modulus was recorded at 118.26 Mpa. The highest Impact Strength was recorded at 1.33 J. However, the Flexural Strength and Flexural Modulus increased when the content of PLA decrease and it slightly drop when the content of PLA is at the 40%. The highest Flexural Strength and Flexural Modulus were recorded at 7.59 Mpa and 35.33 Mpa respectively. Overall it can be concluded that the PCL70PLA30 composites are the best formulation and it gives a better mechanical properties result.

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A study of melt flow analysis of an ABS-Iron composite in fused deposition modelling process

Cited by 146 publications

References 6 publications

Additive manufacturing methods and modelling approaches: a critical review

Additive manufacturing methods and modelling approaches: a critical review

Integration of physically-based and data-driven approaches for thermal field prediction in additive manufacturing

Characterization and Mechanical Analysis of PCL/PLA composites for FDM feedstock filament

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