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

Marco Livesu, Stefano Ellero, Jonás Martìnez, Sylvain Lefebvre, Marco Attene

arXiv:1705.03811v2cs.GR

TL;DR

The report addresses the need to organize a rapidly expanding body of Additive Manufacturing process-planning algorithms and relate them to fabrication objectives and technology capabilities. It surveys the pipeline, classifies its algorithms and technologies, and discusses tradeoffs and open challenges.

  • Problem

    Rapid advances in Additive Manufacturing process-planning algorithms have outpaced existing surveys, creating a need to organize methods and their fabrication objectives.

  • Method

    The report provides a comprehensive survey that classifies process-planning algorithms by problem, examines their data structures and representations, and relates them to Additive Manufacturing technologies and desirable part properties.

  • Results

    The report identifies technology-dependent tradeoffs, including support requirements, material mixing, enclosed voids, and whether printing time depends more on part height or solidified volume.

  • Takeaways & Limitations

    Process planning must balance multiple objectives against the capabilities and limitations of the selected Additive Manufacturing technology.

  • Takeaways & Limitations

    Within-layer solidification cannot generally mix different materials and requires non-solidified material to exit cavities, preventing fully closed empty voids.

Abstract

from arXiv · show

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.

1. Introduction

Digital 3D models connect product development to fabrication in modern manufacturing. Realizing a designed product requires selecting an appropriate manufacturing method.

  • Digital 3D models are central to modern product development as additive manufacturing gains industrial adoption.
  • An industrial product lifecycle proceeds through conception, design, realization, and service.
  • Moving from design to realization requires selecting a suitable manufacturing method.

1.1. Survey contents and objectives

This report surveys additive-manufacturing process planning because recent algorithmic advances have outpaced prior dedicated surveys. It classifies process-planning methods, explains their effects on final-part properties, and defines a scope centered on process planning rather than design or comprehensive technology reviews.

  • The report provides a comprehensive overview of algorithms, data structures, and shape representations that convert virtual models into machine instructions.
  • It categorizes algorithms by the process-planning problem they solve and discusses their effects on desirable final-part properties.
  • It excludes detailed part-design coverage and in-depth technical reviews of current printing technologies, discussing only properties and limitations relevant to process planning.
  • Motivation and timeliness: The survey is timely because the previous dedicated process-planning survey was published sixteen years earlier, despite many subsequent algorithmic advances.
  • Target reader: The report targets researchers across design, mechanical engineering, materials science, computer graphics, and applied mathematics.

1.2. General introduction to process planning

Process planning comprises operations between part design and manufacture. In additive manufacturing, layered fabrication simplifies path generation and changes the problem by making orientation and gravity significant.

  • Process Planning consists of operations performed after designing a part or assembly and before manufacturing its components.
  • Traditional subtractive process planning selects machining operations and machines according to part geometry and feature complexity.
  • CAM software uses stock and machine characteristics to simulate machining and generate machine instructions containing toolpaths and operating parameters.
  • Additive manufacturing usually performs fabrication in one machine without defined stock, while simplifying toolpath computation except for finishing.
  • Layered fabrication generates 2D toolpaths within slices, reducing process-planning dimensionality while making results orientation dependent and sensitive to gravity.

1.3. 3D printing technologies

Additive manufacturing technologies build objects layer by layer and are classified by how material is deposited or solidified, and by whether fabrication follows vector paths or raster patterns. These distinctions determine process-planning outputs, support needs, material capabilities, and printing-time tradeoffs.

  • All considered additive manufacturing technologies construct objects layer after layer.
  • Vector processes produce continuous paths, while raster processes use discrete devices and produce images as the processing-pipeline output.
  • Material deposition locally deposits material onto a previously printed layer, whereas layer solidification solidifies selected regions of a non-solid material such as powder or liquid.
  • Material deposition: Material deposition combines multiple materials, scales printing time mainly with part volume, and encloses voids, but strongly requires disposable supports for overhangs.
  • Layer solidification: Layer solidification reduces support needs for complex geometries, but supports may still be needed for stabilization or heat dissipation.
  • Layer solidification: Layer solidification cannot generally mix different materials and requires non-solidified material to exit cavities, preventing fully closed internal voids.
  • Layer solidification: 37?

1.4. Pipeline

The Process Planning pipeline converts design specifications and geometry into fabrication-ready CAM representations and machine instructions. It typically includes geometry adaptation, orientation, support creation, slicing, and toolpath generation, with iteration back to design when fabrication constraints are unmet.

  • CAD models or technical drawings are converted into CAM representations before fabrication.Integrated CAD/CAM systems can make this transition more transparent.
  • Process planning is iterative because incompatible design specifications may require returning to the design phase for updates.
  • Tessellated CAM models are commonly represented in STL, while newer indexed formats reduce redundancy and encode attributes such as colours and materials.STL represents an unstructured collection of triangles and describes surface geometry without colour, texture, or other common CAD attributes.
  • The pipeline adapts input geometry, selects a building direction, creates supports, slices the model, and converts slices into toolpaths.Toolpaths include movements for boundaries, interiors, and possible support structures.

2. Metrics / Desiderata

Process Planning balances competing objectives rather than optimizing a single universal criterion. The report discusses cost, fidelity, surface texture, and functionality, including distinct proxies and tradeoffs for evaluating printed parts.

  • Process Planning seeks a tradeoff among objectives whose relative importance depends on the application scenario.
  • Cost: Production cost combines pre-build, build, and post-processing components.These components include preparation, machine and material use, and labour, material, and time for finishing and support removal.
  • Form fidelity: Form fidelity measures deviation between the design and layered printed shape, while cusp-height error and volumetric difference are widely used proxies.Cusp height depends on layer thickness and local surface orientation relative to the build direction.
  • Form fidelity: Volumetric difference and cusp height are not equivalent proxies; for steep slopes, volumetric error may better reflect substantial shape variation.
  • Texture: Texture measures local surface variations affecting visual, haptic, and mechanical properties, but it cannot generally be estimated before printing.Surface roughness depends largely on printer resolution and printing material; Ra and Rz are commonly used metrics.
  • Functionality: Additive manufacturing also supports functionality-oriented shape requirements, including optimization for physical properties such as weight, heat dissipation, and stiffness.

3.1. Meeting fabrication requirements

Meeting fabrication requirements requires separating printer-specific shape compatibility from representation validity. Geometry checks, thickening, splitting, repairing, and robust implicit processing help make models printable, but repairs can trade robustness or printability against geometric fidelity.

  • Shape requirements ensure compatibility with printing hardware, whereas representation requirements ensure that tessellated geometry unambiguously encloses a solid.
  • Checks identify features that fall below printing resolution, including thin walls and other tiny regions.Related methods estimate the thickness of triangulated models.
  • Geometry adaptation can thicken sheet-like structures or split oversized models into printable parts that are later reassembled.
  • Mesh-repair methods may use volumetric or implicit representations to create robust printable geometry, but these approaches can introduce distortion.Robustness and precision are major issues, especially when removing self-intersections.
  • Because 3D printing produces solid objects, repaired meshes must enclose a solid; filling open boundaries can perform poorly when boundaries represent zero-thickness sheet-like features.Global remeshing can successfully fix open-boundary STL inputs at the cost of overall approximation.

3.2. Orientation

Build orientation strongly affects printing time, support requirements, surface quality, structural performance, and cost or fidelity objectives. Orientation methods therefore optimize single or multiple criteria using sampling, specialized metrics, decision systems, or weighted objectives.

  • Build direction directly influences print time, support volume, and surface quality.
  • Direct optimization over all orientations is difficult because the relevant metrics are non-smooth.Many recent methods sample orientations regularly and shortlist promising candidates.
  • Orientation methods optimize criteria including support volume, surface roughness, volumetric error, decomposition loss, and post-processing effort.
  • Layered fabrication can introduce structural anisotropy, motivating orientation optimization for safety factors and structural equilibrium.
  • Multi-criteria orientation algorithms combine cost and fidelity objectives through user-adjustable weights or prioritized decision criteria.Some decision-support systems consider overhang area, support volume, build time, and cost but do not scale well to free-form shapes.

3.3. Support Structures

Support structures compensate for fabrication limits such as unsupported overhangs, islands, instability, and costly inner-volume printing. Process planning balances support reliability against material, time, removal effort, surface quality, and part properties.

  • Why supports are required: Support structures address maximum overhang angles, unsupported deposition, part movement or deformation, and the time cost of printing inner volumes.Islands can trigger cascading failure in subsequent layers, while excessive overhangs may cause deposited material to fall.
  • External supports: External supports are sacrificial geometries removed after fabrication, but removal is often time-consuming, expensive, and damaging to surface finish.Chemical or mechanical removal may require human intervention, and residual material can remain attached to the part.
  • Reducing supports: Part orientation, design deformation, and support-free model design can reduce supports, although process planners usually must retain some supports for the input geometry.Orientation is a major factor in external support requirements.
  • Detection and generation: Support generation first detects unsupported surfaces using facet angles, successive-slice differences, or image-space morphology, then selects and constructs support geometry.Some methods down-sample the detected support points before generating the structure.
  • Detection and generation: Support design trades off print time, material use, and reliability: large weakly infilled supports are reliable but consume substantial resources.Large contact areas with the part and print bed improve stability in filament printing.
  • Internal supports and hollowing: Internal hollowing and infill reduce material and time, but must preserve fabricability, rigidity, and desired mechanical behavior.Changing the interior can make regions flexible or rigid and alter object balance.

3.4. Slicing

Slicing converts a solid 3D model into planar contours for layer fabrication, requiring choices about slice positions and efficient contour extraction. Adaptive strategies address geometry-dependent quality and time, while representations determine slicing algorithms and information loss.

  • Slicing problem: Slicing divides a solid into planar contours that are manufactured layer by layer, with each slice formed by intersecting the shape at a build height.The build direction is assumed to align with the z axis.
  • Slicing problem: The two central slicing problems are selecting slice positions and efficiently computing each contour from the input geometry.These problems are treated separately in the slicing pipeline.
  • Slice placement: Uniform slicing uses a constant layer thickness, which can over-sample some regions while producing staircase defects and increased manufacturing time on slanted surfaces.Thin layers required by slanted regions are then applied throughout the part.
  • Slice placement: Adaptive slicing varies layer thickness to meet geometric-error constraints and reduce print time, while locally adaptive slicing independently handles regions with different in-layer complexity.Interior regions may use thicker slices than visible exterior shells.
  • Direct slicing: Direct slicing avoids resampling CAD geometry into meshes or ray representations, but output formats may be vendor-dependent despite independent formats such as CLI.NURBS models are among the geometries targeted by direct-slicing approaches.
  • Contour extraction: Triangle-mesh contouring extracts plane-triangle intersections and forms loops, with mesh validity determining whether repair or hole-closing is needed.Connectivity-aware methods can sweep the slicing plane efficiently because contour topology remains unchanged between mesh vertices.
  • Contour extraction: Ray representations store solid intervals along rays and can be directly contoured, while also supporting operations such as CSG, self-intersection regulation, and hollowing offsets.Multiple ray directions can improve geometric reproduction.

3.5. Machine instructions

Machine instructions convert slices into vector toolpaths or raster images according to printer operation. Their design addresses deposition regularity, continuity, path geometry, infill efficiency, domain decomposition, motion overhead, and binder control.

  • Machine instructions: Plotter-like machines require vector slices, whereas inkjet-like machines interpret each slice as a raster image.The distinction follows whether instructions connect points with paths or encode a discrete 2D image.
  • Vector case: Vector toolpaths are piecewise-linear paths prepared for each slice’s outer contour and interior, with boundary representations requiring inside–outside classification.Some machines also support arcs.
  • Vector case: FDM path planning controls deposition regularity and overlap, while powder-bed processes additionally require careful heat control.Uniform coverage depends on controlling overlap between adjacent paths.
  • Continuity: Reducing disconnected paths helps maintain constant deposition because starting and ending paths make material control difficult.The objective is to minimize discontinuities in the deposition process.
  • Continuity: Long, low-curvature paths are preferred because sharp turns slow the nozzle and can cause under- or overfilling.Path geometry therefore affects both deposition quantity and completion time.
  • Patterns: Infill patterns reduce the time and material consumed by internal volumes, but they must accommodate FDM continuity, geometry, and overhang constraints.These patterns are especially associated with FDM processes.
  • Domain split: Divide-and-conquer toolpath methods partition complex slices into pockets, using decompositions such as monotone polygons, convex regions, iso-contours, Voronoi structures, or medial axes.The partitioning avoids covering an arbitrarily complex slice with one connected curve.
  • Performances: Machine airtime is reduced by optimizing the order and arrangement of disconnected curves, while raster systems instead manage pixel exposure and binder saturation.Binder saturation affects both strength and accuracy in Z-Corp.-type systems.

3.6. Multiple components / Batch printing

Printing multiple components separately can avoid chamber-size, fusion, inaccessible-support, and surface-quality problems associated with pre-assembled models. Splitting methods therefore seek printable, reassemblable parts while trading off packing, material use, structural stress, distortion, and part count.

  • Multiple components: Pre-assembled models may exceed the chamber, fuse at tangencies, require inaccessible supports, or suffer rough surfaces after support removal.These issues motivate manufacturing multi-part components separately and reassembling them afterward.
  • Part decomposition: Splitting an oversized object produces independently printable, reassemblable parts constrained by the available printing volume.One approach also avoids overly small parts and seams in areas of high mechanical stress.
  • Packing and optimization: Packing-oriented decomposition trades packing efficiency against the number of parts, with other methods also optimizing material use or structural stresses.Some approaches combine hollowing and orientation optimization, while others convert shapes into nearly cubical foldable parts.
  • Printability and quality: Support-free decomposition can reduce surface defects, while limited distortion or small-part counts may be accepted to improve printability and surface quality.Methods split models into approximate pyramidal pieces or parts that can be consistently sliced with small geometries.

4. Relations between quality metrics and basic steps

Process-planning stages affect different quality metrics, whose relative importance depends on the application. The report summarizes these relationships to support process tuning, while recognizing that multiple metrics may require tradeoffs.

  • Each process-planning stage affects some of the final part’s quality metrics.The report relates specific process-planning steps to their quality effects through a summary table and detailed sections.
  • The relative importance of quality metrics depends on the application, so process planning must be tuned accordingly.
  • Multiple quality metrics often need simultaneous optimization, motivating decision systems and genetic algorithms to help find tradeoffs.

5. Open challenges

Open challenges include integrating and customizing process-planning tools, balancing user-selected objectives, improving simulation, and overcoming current precision and hardware limitations. The report also identifies supports, embedded devices, geometry representations, and discretization as continuing research challenges.

  • Industrial integration and control: Industrial users seek integrated process-planning tools covering model repair, orientation, supports, slicing, and toolpath calculation, with customization and continued updating.A common software framework is suggested as a way to support this integration.
  • Industrial integration and control: Process-planning systems should let users select optimization parameters because priorities differ between part performance and process efficiency.Examples include structural resistance and surface finish versus production time and material waste.
  • Simulation: More accurate process simulation is needed to improve desiderata and reduce uncertainty, although some final-result characteristics can already be forecast and optimized.
  • Complementarity with subtractive technologies: AM currently lacks the precision, stability, and roughness required for many mechanically demanding features, so production commonly combines AM with subtractive finishing.Extra material is left on high-precision features and later milled to the desired shape.
  • Complementarity with subtractive technologies: Improved AM precision could simplify production, reduce manufacturing cost, and remove finishing constraints that limit exploitation of AM’s geometric freedom.
  • Design and support challenges: Supports remain a difficult and penalizing issue affecting material use, removal effort, and surface artifacts, requiring research across modeling, planning, materials, and machines.
  • Multidisciplinary fabrication: Embedding sensors and electronics creates challenges spanning material science, geometry, 3D modeling, circuit routing, and process planning.
  • Representations and hardware: Current printers impose hardware limits because they execute finite command sets, typically straight segments or, in advanced systems, circular arcs.
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