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Optimization of wear loss in silicon nitride (Si3N4)–hexagonal boron nitride (hBN) composite using DoE–Taguchi method

Overview of attention for article published in SpringerPlus, September 2016
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Title
Optimization of wear loss in silicon nitride (Si3N4)–hexagonal boron nitride (hBN) composite using DoE–Taguchi method
Published in
SpringerPlus, September 2016
DOI 10.1186/s40064-016-3379-7
Pubmed ID
Authors

Sachin Ghalme, Ankush Mankar, Y. J. Bhalerao

Abstract

The contacting surfaces subjected to progressive loss of material known as 'wear,' which is unavoidable between contacting surfaces. Similar kind of phenomenon observed in the human body in various joints where sliding/rolling contact takes place in contacting parts, leading to loss of material. This is a serious issue related to replaced joint or artificial joint. Out of the various material combinations proposed for artificial joint or joint replacement Si3N4 against Al2O3 is one of in ceramic on ceramic category. Minimizing the wear loss of Si3N4 is a prime requirement to avoid aseptic loosening of artificial joint and extending life of joint. In this paper, an attempt has been made to investigate the wear loss behavior of Si3N4-hBN composite and evaluate the effect of hBN addition in Si3N4 to minimize the wear loss. DoE-Taguchi technique is used to plan and analyze experiments. Analysis of experimental results proposes 15 N load and 8 % of hBN addition in Si3N4 is optimum to minimize wear loss against alumina.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 15%
Student > Ph. D. Student 4 15%
Professor > Associate Professor 4 15%
Professor 3 11%
Student > Doctoral Student 3 11%
Other 3 11%
Unknown 6 22%
Readers by discipline Count As %
Engineering 10 37%
Materials Science 3 11%
Medicine and Dentistry 2 7%
Physics and Astronomy 2 7%
Social Sciences 1 4%
Other 0 0%
Unknown 9 33%