Motion planning and numerical simulation of material deposition at corners in extrusion additive manufacturing

Comminal, Raphaël; Serdeczny, Marcin P.; Pedersen, David Bue; Spangenberg, Jon

doi:10.1016/j.addma.2019.06.005

Cited by 68 publications

(75 citation statements)

References 37 publications

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“…A three-step path planning strategy was developed by Jin et al [ 24 ] to achieve precision manufacturing in FDM. Communal et al [ 25 ] proposed a path planning strategy considering the shape accuracy of the corners in each layer in material extrusion AM. Figure 4 shows their successful fabrication of corners with good quality.…”

Section: Path Planning Strategiesmentioning

confidence: 99%

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Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Jiang

2020

Micromachines

207

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Additive manufacturing (AM) is the process of joining materials layer by layer to fabricate products based on 3D models. Due to the layer-by-layer nature of AM, parts with complex geometries, integrated assemblies, customized geometry or multifunctional designs can now be manufactured more easily than traditional subtractive manufacturing. Path planning in AM is an important step in the process of manufacturing products. The final fabricated qualities, properties, etc., will be different when using different path strategies, even using the same AM machine and process parameters. Currently, increasing research studies have been published on path planning strategies with different aims. Due to the rapid development of path planning in AM and various newly proposed strategies, there is a lack of comprehensive reviews on this topic. Therefore, this paper gives a comprehensive understanding of the current status and challenges of AM path planning. This paper reviews and discusses path planning strategies in three categories: improving printed qualities, saving materials/time and achieving objective printed properties. The main findings of this review include: new path planning strategies can be developed by combining some of the strategies in literature with better performance; a path planning platform can be developed to help select the most suitable path planning strategy with required properties; research on path planning considering energy consumption can be carried out in the future; a benchmark model for testing the performance of path planning strategies can be designed; the trade-off among different fabricated properties can be considered as a factor in future path planning design processes; and lastly, machine learning can be a powerful tool to further improve path planning strategies in the future.

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Section: Path Planning Strategiesmentioning

confidence: 99%

“… Successful fabrication of 90° and 30° corners reproduced with permission from [ 25 ]. Elsevier, 2019.…”

Section: Figurementioning

confidence: 99%

Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Jiang

2020

Micromachines

207

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“…It creates 3D object by ejecting material through a nozzle and depositing it layer after layer to produce the solid object desired from the 3D model of the part. The materials used in this class include polymers and metals [20] - [23]. The schematic diagram of material extrusion class of AM technologies is shown in figure 3.…”

Section: Materials Extrusionmentioning

confidence: 99%

Additive Manufacturing / 3D Printing Technology: A Review

et al. 2019

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Additive manufacturing (AM) also known as three dimensional (3D) printing is an important advanced manufacturing method that will change the way machines and consumer good are made. This technology is where the human creativity meets technology. AM allows product to be fabricated from the 3D computer aided design (CAD) model of the part, no matter the complexity, through addition of materials one layer at a time until the building is completed. In this article, the seven classes of AM, the advantages in the additively manufactured products as compared to the existing counterparts are highlighted and some of the research efforts in this technology are presented. Some of the problems and the future research need in this field are also presented.

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“…The reason for this attention is its relatively low cost, wide availability, comparatively minor safety concerns regarding the process, and ease of use [ 3 ]. In the ME-AM process, 3D parts are formed through the controlled deposition of successive layers of molten material extruded from a moving head along a predefined toolpath [ 4 , 5 ]. Nonetheless, because of the layer-by-layer nature of the deposited material and the existence of numerous voids, parts fabricated by ME-AM suffer from inferior mechanical properties, e.g., low elastic behaviour, possible delamination, and low mechanical integrity [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of a Core–Shell Polymer Strand in Material Extrusion Additive Manufacturing

et al. 2021

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Material extrusion additive manufacturing (ME-AM) techniques have been recently introduced for core–shell polymer manufacturing. Using ME-AM for core–shell manufacturing offers improved mechanical properties and dimensional accuracy over conventional 3D-printed polymer. Operating parameters play an important role in forming the overall quality of the 3D-printed manufactured products. Here we use numerical simulations within the framework of computation fluid dynamics (CFD) to identify the best combination of operating parameters for the 3D printing of a core–shell polymer strand. The objectives of these CFD simulations are to find strands with an ultimate volume fraction of core polymer. At the same time, complete encapsulations are obtained for the core polymer inside the shell one. In this model, the deposition flow is controlled by three dimensionless parameters: (i) the diameter ratio of core material to the nozzle, d/D; (ii) the normalised gap between the extruder and the build plate, t/D; (iii) the velocity ratio of the moving build plate to the average velocity inside the nozzle, V/U. Numerical results of the deposited strands’ cross-sections demonstrate the effects of controlling parameters on the encapsulation of the core material inside the shell and the shape and size of the strand. Overall we find that the best operating parameters are a diameter ratio of d/D=0.7, a normalised gap of t/D=1, and a velocity ratio of V/U=1.

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Motion planning and numerical simulation of material deposition at corners in extrusion additive manufacturing

Cited by 68 publications

References 37 publications

Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Additive Manufacturing / 3D Printing Technology: A Review

Numerical Simulation of a Core–Shell Polymer Strand in Material Extrusion Additive Manufacturing

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