Alternative Lubricants: Study on Palm Oil-Based Lubricants in Metal Forming Process

Nurul, M. A.; Syahrullail, S.; Teng, Haihao

doi:10.21894/jopr.2016.2801.11

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…The tested lubricants ensured better material flow/draw-inlength and uniform thickness profiles compared to mineral oil lubrication. Nurul et al [36] investigated palm oil-based lubricants in cold extrusion processes. The palm olein and palm kernel oil showed an enhanced extrusion load and no severe wear on the product surface.…”

Section: Introductionmentioning

confidence: 99%

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

Trzepieciński

2024

Materials

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Friction is one of the main phenomena accompanying sheet metal forming methods, affecting the surface quality of products and the formability of the sheet metal. The most basic and cheapest way to reduce friction is to use lubricants, which should ensure the highest lubrication efficiency and at the same time be environmentally friendly. Due to the trend towards sustainable production, vegetable oils have been used in research as an alternative to petroleum-based lubricants. The analysis of friction in sheet metal forming requires an appropriate tribotester simulating the friction conditions in a specific area of the sheet metal being formed. Research has used a special strip drawing tribometer, enabling the determination the value of the coefficient of friction in the blankholder zone in the deep drawing process. Quantitative analysis of the friction phenomenon is necessary at the stage of designing the technological process and selecting technological parameters, including blankholder pressure. This article presents the results of friction testing of 1.0338 (DC04) steel sheets using a strip drawing test. The experimental tests involved pulling a strip of sheet metal between two countersamples with a rounded surface. The tests were carried out on countersamples with different levels of roughness for the range of contact pressures occurring in the blankholder zone in the deep drawing process (1.7–5 MPa). The values of the coefficient of friction determined under dry friction conditions were compared with the results for edible (corn, sunflower and rapeseed) and non-edible (Moringa, Karanja) vegetable lubricants. The tested oils are the most commonly used vegetable-based biolubricants in metal forming operations. Multi-layer artificial neural networks were used to determine the relationship between the value of the contact pressure, the roughness of the countersamples, the oil viscosity and density, and the value of the coefficient of friction. Rapeseed oil provided the best lubrication efficiency during friction testing for all of the tested samples, with an average surface roughness of Sa 0.44–1.34 μm. At the same time, as the roughness of the countersamples increased, a decrease in lubrication efficiency was observed. The lowest root mean squared error value was observed for the MLP-4-8-1 network trained with the quasi-Newton algorithm. Most of the analysed networks with different architectures trained using the various algorithms showed that the kinematic viscosity of the oil was the most important aspect in assessing the friction of the sheets tested. The influence of kinematic viscosity on the value of the coefficient of friction is strongly dependent on the surface roughness of the countersamples.

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Section: Introductionmentioning

confidence: 99%

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

Trzepieciński

2024

Materials

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Lubrication of textured journal bearing by using vegetable oil: A review of approaches, challenges, and opportunities

Rasep

Yazid

Samion

2021

Renewable and Sustainable Energy Reviews

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A Friction–Wear Correlation for Four-Ball Extreme Pressure Lubrication

Chen

Lim

Yeong

et al. 2019

Journal of Tribology

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A first-ever friction–wear model for four-ball extreme pressure (EP) lubrication is developed in this work based on 12 oil samples comprising minerals, esters, and other formulated lubricants. The model considers the rate of entropy generation and dissipation within the lubricated tribosystem to describe the interaction between the friction and the wear behaviors at extreme pressure conditions. The model can be used to calculate the probability to pass or fail at a specific load to estimate the weld point of a lubricant. The calculated probability exhibited a similar trend as a load-wear index from the ASTM D2783 EP test method. Besides, the model is able to estimate the EP performance of an unknown lubricant based on the model parameter, namely the dissipative coefficient. This parameter describes the proportionality between the friction and the wear phenomena from the perspective of thermodynamic analysis. This work provides useful tools to better understand the fundamentals of EP lubrication and to characterize the lubricants without overly relying on tribotest machines.

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Alternative Lubricants: Study on Palm Oil-Based Lubricants in Metal Forming Process

Cited by 4 publications

References 6 publications

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

Lubrication of textured journal bearing by using vegetable oil: A review of approaches, challenges, and opportunities

A Friction–Wear Correlation for Four-Ball Extreme Pressure Lubrication

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