Nonplanar slicing and path generation methods for robotic additive manufacturing

Zhao, Gang; Ma, Guocai; Feng, Jiangwei; Xiao, Wenlei

doi:10.1007/s00170-018-1772-9

Cited by 96 publications

(34 citation statements)

References 31 publications

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“…Figure 5 shows the example 5DOF machine and the product fabricated using their path planning method. Zhao et al [ 45 ] introduced a nonplanar path planning strategy that can reduce the usage of support material in robot-based material extrusion AM. Tarabanis [ 46 ] developed a path planning strategy, based on shelving and bridging features, that allows parts to be able to be printed “in the air” in FDM, thus reducing support structure usage.…”

Section: Path Planning Strategiesmentioning

confidence: 99%

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

Jiang

2020

Micromachines

198

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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%

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

Jiang

2020

Micromachines

198

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“…Combining the slicing algorithm with tool path generation [25] can improve the efficiency of the overall process by removing the need to write to an intermediary slice file but limits the possibilities of the output of the algorithm to the specific application, due to the varying nature of the toolpath input format. There have been a number of efforts to compensate for low-quality models, containing errors or incorrect geometric features using the slicing process; Zhao et al [26] aimed to reduce the error caused by discretising the CAD model into the triangular mesh file using contour approximation, and Luo and Wang [27] similarly aimed to minimise the impact of defects such as cracks and overlapping edges in the model during the slicing process. Zhang's [10] ECC algorithm presents a comprehensive universal slicing algorithm that is both time-and memoryefficient; their method exploits the clockwise nature of a triangular mesh, allowing for only one intersection per slice plane per triangle to be computed, reducing the memory requirement of the slicing algorithm by half.…”

Section: Review Of Related Workmentioning

confidence: 99%

An efficient triangle mesh slicing algorithm for all topologies in additive manufacturing

King

Rennie

Bennett³

2020

Int J Adv Manuf Technol

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To date, slicing algorithms for additive manufacturing is the most effective for favourable triangular mesh topologies; worst-case models, where a large percentage of triangles intersect each slice plane, take significantly longer to slice than a like-for-like file. In larger files, this results in a significant slicing duration, when models are both worst cases and contain more than 100,000 triangles. The research presented here introduces a slicing algorithm which can slice worst-case large models effectively. A new algorithm is implemented utilising an efficient contour construction method, with further adaptations, which make the algorithm suitable for all model topologies. Edge matching, which is an advanced sorting method, decreases the number of sorts per edge from n total number of intersections to two, alongside additional micro-optimisations that deliver the enhanced efficient contour construction algorithm. The algorithm was able to slice a worst-case model of 2.5 million triangles in the 1025s. Maximum improvement was measured as 9400% over the standard efficient contour construction method. Improvements were also observed in all parts in excess of 1000 triangles. The slicing algorithm presented offers novel methods that address the failings of other algorithms described in literature to slice worst-case models effectively.

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“…DED is often the AM process of choice for applications where the substrate is an existing part, as it can more easily build off non-horizontal or complex surfaces [4]. PBF processes are currently more generally available in industry and often have better accuracy and surface finish, but any substrate surface being printed on must be planar and secured horizontally in the powder bed [5].…”

Section: Introductionmentioning

confidence: 99%

Interface Joint Strength Between SS316L Wrought Substrate and Powder Bed Fusion Built Parts

Weaver

Linn

Miles

2021

Preprint

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Metal powder bed fusion (PBF) additive manufacturing (AM) builds metal parts layer by layer upon a substrate material. The strength of this interface between substrate and printed material is important to characterize, especially in applications where the substrate is retained and included in the finished part. This paper studied the tensile and torsional strengths of wrought and additively manufactured (through PBF) SS316L and compared them to specimens composed of half wrought material and half PBF material. The PBF specimens consistently exhibited higher strength and lower ductility than the wrought specimens. The hybrid PBF/wrought specimens performed similarly to the wrought material. In no specimens did any failure appear to occur at or near the interface between wrought substrate and PBF material. In addition, most of the deformation in the PBF/wrought specimens appeared to be limited to the wrought portion of the specimens. These results are consistent with microscopy showing smaller grain size in the PBF material, which often leads to increased strength in SS316L due to the Hall-Petch relationship.

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Nonplanar slicing and path generation methods for robotic additive manufacturing

Cited by 96 publications

References 31 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

An efficient triangle mesh slicing algorithm for all topologies in additive manufacturing

Interface Joint Strength Between SS316L Wrought Substrate and Powder Bed Fusion Built Parts

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