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Python Package for Additive Manufacturing Development

Project description

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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. Additional functionality will be added to provide basic capabilities.

The aims is this library provides especially for an academic environment, a useful set of tools for prototyping and used in-conjunction with simulation and analytic studies.

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.

Support Structure Generation

  • [TODO] A prototype for support structure generation

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 developing the scan strategies:

  • Offsetting of contours and boundaries

  • Trimming of lines and hatch vectors (sequentially ordered)

The following scan strategies have been implemented as reference on platforms:

  • Standard ‘Alternating’ hatching

  • Stripe Scan Strategy

  • Island or Checkerboard Scan Strategy

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)

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. Work is underway to support the following file formats. If you would like to support implementing a custom format, please raise a request.

  • Renishaw MTT (.mtt),

  • DMG Mori Realizer (.rea),

  • EOS SLI formats (.sli) - WIP,

  • SLM Solutions (.slm).

For further information, see the latest release notes.

Installation

Installation is currently supported on Windows 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 libSLM
pip install PythonSLM

Alternatively, PySLM may be compiled 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
geomSlice = solidPart.getVectorSlice(z)

#Perform the hatching operations
layer = myHatcher.hatch(geomSlice)

# Plot the layer geometries
pyslm.visualise.plot(layer, plot3D=False, plotOrderLine=True) # plotArrows=True)

For further guidance please look at documented examples are provided in examples .

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