Comparing Slicing Technologies for Digital Light Processing Printing

In additive manufacturing (AM), slicing is a crucial step in process planning to convert a computer-aided design (CAD) model to a machine-specific format. Digital light processing (DLP) printing is an important AM process that has a good surface finish, high accuracy, and fabrication speed and is widely applied in many dental and engineering industries. However, as DLP uses images for fabrication different from other toolpath-based processes, its process planning is understudied. Therefore, the main goal of this paper is to study and compare the slicing technologies for DLP printing. Three slicing technologies are compared: contour, voxelization, and ray-tracing

Single Path Generation for Closed Contours via Graph Theory and Topological Hierarchy

Slicing converts a 3D object into a set of 2D polygons that are filled with multiple path types. These paths involve travels where the extruder of the machine must stop building, lift, travel to the next path, lower, and resume construction. Travels are considered wasted time as construction of the object is not occurring. Further, the start/stop point, called a seam, causes both reduced aesthetic and weaker material properties. To address these issues, an algorithmic approach was developed to compute a continuous single path from closed contours. The algorithm utilizes graph theory and a topological hierarchy to produce a single path for an individual layer. This approach can be combined with spiralization techniques to compute a single path for entire objects. The resulting objects can be constructed quicker and have improved material properties as verified via tensile testing.Mechanical Engineerin

An Efficient Triangle Mesh Slicing Algorithm for All Topologies in Additive Manufacturing

To date, slicing algorithms for additive manufacturing are 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 case 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 1025s. Maximum improvement was measured as 9,400% 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

Anti-aliasing for fused filament deposition

14 pages, 22 figuresInternational audienceLayered manufacturing inherently suffers from staircase defects along surfaces that are gently slopped with respect to the build direction. Reducing the slice thickness improves the situation but never resolves it completely as flat layers remain a poor approximation of the true surface in these regions. In addition, reducing the slice thickness largely increases the print time. In this work we focus on a simple yet effective technique to improve the print accuracy for layered manufacturing by filament deposition. Our method works with standard three-axis 3D filament printers (e.g. the typical, widely available 3D printers), using standard extrusion nozzles. It better reproduces the geometry of sloped surfaces without increasing the print time. Our key idea is to perform a local anti-aliasing, working at a sub-layer accuracy to produce slightly curved depo-sition paths and reduce approximation errors. This is inspired by Computer Graphics anti-aliasing techniques which consider sub-pixel precision to treat aliasing effects. We show that the necessary deviation in height compared to standard slicing is bounded by half the layer thickness. Therefore, the height changes remain small and plastic deposition remains reliable. We further split and order paths to minimize defects due to the extruder nozzle shape, avoiding any change to the existing hardware. We apply and analyze our approach on 3D printed examples, showing that our technique greatly improves surface accuracy and silhouette quality while keeping the print time nearly identical

CurviSlicer: Slightly curved slicing for 3-axis printers

International audienceMost additive manufacturing processes fabricate objects by stacking planar layers of solidified material. As a result, produced parts exhibit a so-called staircase effect, which results from sampling slanted surfaces with parallel planes. Using thinner slices reduces this effect, but it always remains visible where layers almost align with the input surfaces. In this research we exploit the ability of some additive manufacturing processes to deposit material slightly out of plane to dramatically reduce these artifacts. We focus in particular on the widespread Fused Filament Fabrication (FFF) technology, since most printers in this category can deposit along slightly curved paths, under deposition slope and thickness constraints. Our algorithm curves the layers, making them either follow the natural slope of the input surface or on the contrary, make them intersect the surfaces at a steeper angle thereby improving the sampling quality. Rather than directly computing curved layers, our algorithm optimizes for a deformation of the model which is then sliced with a standard planar approach. We demonstrate that this approach enables us to encode all fabrication constraints , including the guarantee of generating collision-free toolpaths, in a convex optimization that can be solved using a QP solver. We produce a variety of models and compare print quality between curved deposition and planar slicing

Adaptive slicing based on efficient profile analysis

Adaptive slicing is an important computational task required in the layer-based manufacturing process. Its purpose is to find an optimal trade-off between the fabrication time (number of layers) and the surface quality (geometric deviation error). Most of the traditional adaptive slicing algorithms are computationally expensive or only based on local evaluation of errors. To tackle these problems, we introduce a method to efficiently generate slicing plans by a new metric profile that can characterize the distribution of deviation errors along the building direction. By generalizing the conventional error metrics, the proposed metric profile is a density function of deviation errors, which measures the global deviation errors rather than the in-plane local geometry errors used in most prior methods. Slicing can be efficiently evaluated based on metric profiles in contrast to the expensive computation on models in boundary-representation. An efficient algorithm based on dynamic programming is proposed to find the best slicing plan. Our adaptive slicing method can also be applied to models with weighted features and can serve as the inner loop to search the best building direction. The performance of our approach is demonstrated by experimental tests on different examples

From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044