A new adaptive slicing approach for the fully dense freeform fabrication (FDFF) process

Hayasi, Mohammad; Asiabanpour, Bahram

doi:10.1007/s10845-011-0615-4

Cited by 44 publications

(27 citation statements)

References 21 publications

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“…Yang et al 26 adopted the Boolean operations between two polygons to obtain the volume difference between two adjacent layers to describe the staircase effect. Hayasi and Asiabanpour 27 proposed the triangle area of the projected contours on the side views as the error parameter rather than the area of adjacent layers. Firstly, the model was sliced with the minimum thickness to avoid losing the significant features.…”

Section: Background and Related Workmentioning

confidence: 99%

A polygons Boolean operations-based adaptive slicing with sliced data for additive manufacturing

Lin

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part C:

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In order to increase the efficiency of additive manufacturing, this paper proposes a novel adaptive slicing approach of sliced data with minimum thickness based on Boolean operations of polygons. It can greatly handle the balance between the build time and the surface precision of additive manufacturing. The proposed adaptive slicing is available for the single solid model, the support of additive manufacturing, and simultaneously manufactured multiple models. At first, the Boolean operations of polygons are used to gain the relationship of the adjacent layers to serve as the topological information. Second, two parameters are proposed to evaluate the precision of sliced surface: the ameliorative area ratio and variation of the cusp height. Ameliorative area ratio overcomes the drawbacks of original area deviation ration criteria and can work on the large and complex models. Variation of the cusp height makes the calculation of cusp height suitable for sliced data of model, and it is independent of the normal vector of surfaces. Third, the adaptive slicing is realized by removing unnecessary layers based on two parameters and the maximum allowable thickness. The thicknesses are times of the minimum thickness. Moreover, the adaptive slicing for support of additive manufacturing is developed through dividing the support into two parts according to its height and location. Slicing of multiple models is also proposed by choosing the maximum ameliorative area ratio and variation of the cusp height among all models in the same z level as the two parameters. Finally, the adaptive slicing for the three types is tested with some special models, and corresponding models are printed with FDM technology based on slicing results of the proposed approach. Results show that the proposed adaptive slicing approach is effective.

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Section: Background and Related Workmentioning

confidence: 99%

A polygons Boolean operations-based adaptive slicing with sliced data for additive manufacturing

Lin

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…CEO: Geometric metric together with l 0 optimization. HA13: Heuristic merging with geometric error defined by the triangle area of the projected slicers in [HA13].…”

Section: Convergencementioning

confidence: 99%

“…Comparison of visual quality between our method (a) and[HA13] (c). Images(b) and (d)show the close-ups of the red marked regions.…”

mentioning

confidence: 99%

Saliency‐Preserving Slicing Optimization for Effective 3D Printing

Wang

Chao

Tong

et al. 2015

Computer Graphics Forum

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We present an adaptive slicing scheme for reducing the manufacturing time for 3D printing systems. Based on a new saliencybased metric, our method optimizes the thicknesses of slicing layers to save printing time and preserve the visual quality of the printing results. We formulate the problem as a constrained 0 optimization and compute the slicing result via a two-step optimization scheme. To further reduce printing time, we develop a saliency-based segmentation scheme to partition an object into subparts and then optimize the slicing of each subpart separately. We validate our method with a large set of 3D shapes ranging from CAD models to scanned objects. Results show that our method saves printing time by 30-40% and generates 3D objects that are visually similar to the ones printed with the finest resolution possible.

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“…Apart from GT technology, parametric process plan templates were widely used to store and represent the machining process of features. Process plans were generated by engineers who retrieve and modify the template library and solve related constraints according to the parameters of machining features [58][59]. Then, the tool paths can be generated according to the machining feature parameters and the process information.…”

Section: Computer Aided Machiningmentioning

confidence: 99%

From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

Lee

Gao

2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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The aim of this paper is to provide an introduction and overview of recent advances in the key technologies and the supporting computerized systems, and to indicate the trend of research and development in the area of computational numerical control machining. Three main themes of recent research in CNC machining are simulation, optimization and automation, which form the key aspects of *Corresponding author, Email: welcome.li@nuaa.edu.cn 2 intelligent manufacturing in the digital and knowledge based manufacturing era. As the information and knowledge carrier, feature is the efficacious way to achieve intelligent manufacturing. From the regular shaped feature to freeform surface feature, the feature technology has been used in manufacturing of complex parts, such as aircraft structural parts. The authors' latest research in intelligent machining is presented through a new concept of multi-perspective dynamic feature (MpDF), for future discussion and communication with readers of this special issue. The MpDF concept has been implemented and tested in real examples from the aerospace industry, and has the potential to make promising impact on the future research in the new paradigm of intelligent machining. The authors of this paper are the guest editors of this special issue on computational numerical control machining. The guest editors have extensive and complementary experiences in both academia and industry, gained in China, USA and UK.

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A new adaptive slicing approach for the fully dense freeform fabrication (FDFF) process

Cited by 44 publications

References 21 publications

A polygons Boolean operations-based adaptive slicing with sliced data for additive manufacturing

A polygons Boolean operations-based adaptive slicing with sliced data for additive manufacturing

Saliency‐Preserving Slicing Optimization for Effective 3D Printing

From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

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