Measurement of environmental aspect of 3-D printing process using soft computing methods
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- @Article{Garg:2015:Measurement,
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author = "Akhil1 Garg and Jasmine Siu Lee Lam",
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title = "Measurement of environmental aspect of {3-D} printing
process using soft computing methods",
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journal = "Measurement",
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volume = "75",
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pages = "210--217",
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year = "2015",
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ISSN = "0263-2241",
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DOI = "doi:10.1016/j.measurement.2015.04.016",
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URL = "http://www.sciencedirect.com/science/article/pii/S0263224115002195",
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abstract = "For improving the environmental performance of the
manufacturing industry across the globe, 3-D printing
technology should be increasingly adopted as a
manufacturing procedure. It is because this technology
uses the polymer PLA (Polyactic acid) as a material,
which is biodegradable, and saves fuel and reduces
waste when fabricating prototypes. In addition, the
technology can be located near to industries and
fabricates raw material itself, resulting in reduction
of transport costs and carbon emission. However, due to
its high production cost, 3-D printing technology is
not yet being adopted globally. One way of reducing the
production cost and improving environmental performance
is to formulate models that can be used to operate 3-D
printing technology in an efficient way. Therefore,
this paper aims to deploy the soft computing methods
such as genetic programming (GP), support vector
regression and artificial neural network in formulating
the laser power-based-open porosity models. These
methods are applied on the selective laser sintering (a
3-D printing process) process data. It is found that GP
evolves the best model that is able to predict open
porosity satisfactorily based on given values of laser
power. The laser power-based-open porosity model
formulated can assist decision makers in operating the
SLS process in an effective and efficient way, thus
increasing its viability for being adopted as a
manufacturing procedure and paving the way for a
sustainable environment across the globe.",
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keywords = "genetic algorithms, genetic programming, Selective
laser sintering, Soft computing methods, Open porosity
prediction, 3-D printing, Environmental aspect",
- }
Genetic Programming entries for
Akhil Garg
Jasmine Siu Lee Lam
Citations