PySLM Python Library for Selective Laser Melting and Additive Manufacturing¶
PySLM is a Python library for supporting development of input files used in Additive Manufacturing or 3D Printing, in particular Selective Laser Melting (SLM), Direct Metal Laser Sintering (DMLS) platforms typically used in both academia and industry. The core capabilities aim to include slicing, hatching and support generation and providing an interface to the binary build file formats available for platforms. The library is built of core classes which may provide the basic functionality to generate the scan vectors used on systems and also be used as building blocks to prototype and develop new algorithms.
This library provides design tools for use in Additive Manufacturing including the slicing, hatching, support generation and related analysis tools (e.g. overhang analysis, build-time estimation).
PySLM is built-upon python libraries Trimesh and based on some custom modifications to the PyClipper libraries, which are leveraged to provide the slicing and manipulation of polygons, such as offsetting and clipping of lines.
The aims of this library is to provide a useful set of tools for prototyping novel pre-processing approaches to aid research and development of Additive Manufacturing processes, amongst an academic environment. The tools aim to compliment experimental and analytical studies that can enrich scientific understanding of the process. This includes data-fusion from expeirments and sensors within the process but also enahcning the capability of the process by providing greater control over the process. Furthermore, the open nature of the library intends to inform and educate those interested in the underlying algorithms of preparing toolpaths in Additive Manufacturing.
Current Features¶
PySLM is building up a core feature set aiming to provide the basic blocks for primarily generating the scan paths and additional design features used for AM and 3D printing systems typically (SLM/SLS/SLA) systems which consolidate material using a single/multi point exposure by generating a series of scan vectors in a region.
Slicing:
Slicing of triangular meshes supported via the Trimesh library.
Simplification of 2D layer boundaries
Bitmap slicing for SLA, DLP, Inkjet Systems
Hatching: The following operations are provided as a convenience to aid the development of novel scan strategies in Selective Laser Melting:
Offsetting of contours and boundaries
Trimming of lines and hatch vectors (sequentially ordered and sorted)
The following scan strategies have been implemented as reference for AM platforms:
Standard ‘alternating’ hatching
Stripe scan strategy
Island or checkerboard scan strategy
Support Structure Generation
PySLM provides underlying tools and a framework for identifying and generating support structures suitable for SLM. Tools are provided identifying overhang areas based on their mesh and connectivity information, but also usingprojection based method. The projection method takes advantage of GPU GLSL shaders for providing an efficient raytracing approach. Using the PyCork boolean CSG library, an algorithm for extracting precise defintion of volumetric support regions. These regions are segmented based on self-intersections with the mesh. From these volumes, porous grid-truss structure suitable for SLM based process can be generated.
Extracting overhang surfaces from meshes with optional connectivity information
- Projection based block and truss support structure generation
3D intersected support volumes are generated from overhang regions using OpenGL ray-tracing approach
Generate a truss grid using support volumes suitable for Metal AM processes
Exact support volume generation using the pycork library
Visualisation:
The laser scan vectors can be visualised using Matplotlib. The order of the scan vectors can be shown to aid
development of the scan strategies, but additional information such length, laser parameter information associated
with each scan vector can be shown.
Scan vector plots (including underlying BuildStyle information and properties)
Exposure point visualisation
Exposure (effective heat) map generation
Overhang visualisation
Analysis:
- Build time estimation tools
Based on scan strategy and geometry
Time estimation based on LayerGeometry
Iterators (Scan Vector and Exposure Points) useful for simulation studies
Export to Machine Files:
Currently the capability to enable translation to commercial machine build platforms is being providing through a supporting library called libSLM . This is a c++ library to enable efficient import and export across various commercial machine build files. With support from individuals the following machine build file formats have been developed.
Renishaw MTT (.mtt),
DMG Mori Realizer (.rea),
EOS SLI formats (.sli)
SLM Solutions (.slm).
If you would like to support implementing a custom format, please raise a request. For further information, see the latest release notes.
Installation¶
Installation is currently supported on Windows, Mac OS X and Linux environments. The pre-requisites for using PySLM can be installed via PyPi and/or Anaconda distribution.
conda install -c conda-forge shapely, Rtree, networkx, scikit-image, cython
conda install trimesh
Installation of PySLM can then be performed using pre-built python packages using the PyPi repository. Additionally to interface with commercial systems, the user can choose to install libSLM. Note, the user should contact the author to request machine build file translators, as this cannot be installed currently without having the machine build file translators available.
pip install PythonSLM
Alternatively, PySLM may be compiled directly from source. Currently the prerequisites are the cython package and a compliant c++ build environment.
git clone https://github.com/drlukeparry/pyslm.git && cd ./pyslm
python setup.py install
Usage¶
A basic example below, shows how relatively straightforward it is to generate a single layer from a STL mesh which generates a the hatch infill using a Stripe Scan Strategy typically employed on some commercial systems to limit the maximum scan vector length generated in a region.
import pyslm
import pyslm.visualise
from pyslm import hatching as hatching
# Imports the part and sets the geometry to an STL file (frameGuide.stl)
solidPart = pyslm.Part('myFrameGuide')
solidPart.setGeometry('../models/frameGuide.stl')
# Set te slice layer position
z = 23.
# Create a StripeHatcher object for performing any hatching operations
myHatcher = hatching.StripeHatcher()
myHatcher.stripeWidth = 5.0
# Set the base hatching parameters which are generated within Hatcher
myHatcher.hatchAngle = 10 # [°]
myHatcher.volumeOffsetHatch = 0.08 # [mm]
myHatcher.spotCompensation = 0.06 # [mm]
myHatcher.numInnerContours = 2
myHatcher.numOuterContours = 1
# Slice the object at Z and get the boundaries
geomSlice = solidPart.getVectorSlice(z)
# Perform the hatching operations
layer = myHatcher.hatch(geomSlice)
# Plot the layer geometries generated
pyslm.visualise.plot(layer, plot3D=False, plotOrderLine=True) # plotArrows=True)
The result of the script output is shown here
For further guidance please look at documented examples are provided in examples .
Links¶
Installation
Modules