Study of effect of nanofluid concentration on response characteristics of machining process for cleaner production
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gp-bibliography.bib Revision:1.7964
- @Article{Garg:2016:JCPb,
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author = "Akhil Garg and Shrutidhara Sarma and B. N. Panda and
Jian Zhang2 and L. Gao",
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title = "Study of effect of nanofluid concentration on response
characteristics of machining process for cleaner
production",
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journal = "Journal of Cleaner Production",
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year = "2016",
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volume = "135",
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pages = "476--489",
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month = "1 " # nov,
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ISSN = "0959-6526",
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DOI = "doi:10.1016/j.jclepro.2016.06.122",
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URL = "http://www.sciencedirect.com/science/article/pii/S0959652616307995",
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abstract = "With the ever-increasing concern for reducing
environmental pollution and waste minimization,
{"}green manufacturing{"} has been successful to draw
sufficient amount of attention towards it. Minimum
Quantity Lubrication (MQL) is one such technique that
has revolutionized the manufacturing industry by not
only reducing the amount of working fluid dramatically
but also enhancing cutting tool life and reducing
material costs. Past studies have reported the use of
experiments in MQL based manufacturing but limited
computational modeling for optimizing the process
parameters Based on the past experimental procedure of
machining process (micro-drilling), a computational
framework such as Adaptive Neuro Fuzzy Inference System
(ANFIS) and Genetic Programming (GP) in quantification
of three response characteristics (torque, thrust
forces and material removal rate (MRR) is proposed. The
performance analysis based on the cross-validation,
error metrics, curve fitting and hypothesis tests
reveals that among the two models, the GP models have
performed better. 2-D and 3-D surface analysis were
performed to validate the robustness of the models.
Among the three response characteristics, It was found
that the nanofluid concentration influences torque the
most, which is an important aspect for power
consumption. At nanofluid concentration values of 1.4
and 4, the minimum values of torque and thrust forces
is achieved respectively. When drill diameter is
minimum and the spindle speed is maximum, the values of
torque, thrust forces and MRR is the lowest. Thus, the
feed rate, nanofluid concentration and drill diameter
are most critical for obtaining higher MRR and lower
values of torque and thrust force, thus enabling
cleaner production and environment.",
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keywords = "genetic algorithms, genetic programming, Minimum
quality lubrication, Green manufacturing,
Micro-drilling process, Torque, Drill diameter",
- }
Genetic Programming entries for
Akhil Garg
Shrutidhara Sarma
Biranchi Narayan Panda
Jian Zhang2
Liang Gao
Citations