Tribological Properties Study on Polyamide with Incorporated Lubrication

Narendran, J.; Karthikeyan, T.

doi:10.5958/2249-7315.2016.01361.7

Cited by 1 publication

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“…It is evidence that the polymer filled with fibre/filler on non-lubrication conditions has influenced the tribological properties and also bio lubrication on polymer with fibre/filler improves the tribological properties such as COF and wear resistance. Bio lubrication using soybean oil, sunflower oil, and rice bran oil increases effectiveness of filling polyamide as compared with mineral oil (Chowdhury et al, 2014;Narendran and Karthikeyan, 2016;Ridzuan et al, 2011;Rodriguez et al, 2011;Hooke et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

Response surface methodology based on polyamide incorporated with biolubricant for optimisation of operating parameters in heavy vehicles

Narendran¹,

Karthikeyan²

2020

IJHVS

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In this paper, the coefficient of friction (COF) and wear of pure and filled polyamide incorporated with and without bio lubrication prediction models based on response surface methodology (RSM) are exhibited in heavy vehicles. A special purpose vehicle is a motor vehicle or trailer, other than an agricultural vehicle or a tow truck, built for a purpose other than carrying goods, or a concrete pump or fire truck (both of which carry water). Examples of a special purpose vehicle include a mobile crane, a concrete pump, drill rig or fire truck. The models were developed based on three-level design of experiments conducted on pure polyamide such as Polyamide6, Polyamide66 and filled polyamide like Polyamide66 filled with glass fibre 30 and Polyamide66 filled with molybdenum disulfide, considering with load, speed and sliding distance as process parameters. Numerical models of second order RSM clearly show that the prediction capabilities of response surface methodology models are more desirable. This implementation identifies the insignificant main factors and contact factors or insignificant quadratic expressions in the model and in this manner can diminish the complexity of the problem.

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Section: Introductionmentioning

confidence: 99%