Methodology of a statistical and DOE approach to the prediction of performance in tribology – A DLC boundary-lubrication case study

Simonovic, K.; Kalin, Mitjan

doi:10.1016/j.triboint.2016.04.007

Cited by 7 publications

(4 citation statements)

References 36 publications

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“…The distribution of measurement points in the considered experimental space was determined by using a structured design of experiments (DoE) approach. Standard DoE methods such as (full) factorial design, split-plot design, linear regression, Monte Carlo, Taguchi or Box-Behnken [18,19] are, however, poorly suited to obtain a detailed insight into the studied multidimensional stochastic phenomenon. In fact, these approaches are commonly aimed at conventional industrial practices where results are generally limited to the values of the control variables inducing local extrema of the dependent variable [19].…”

Section: Experimental Methodologymentioning

confidence: 99%

An experimental methodology for the concurrent characterization of multiple parameters influencing nanoscale friction

et al. 2019

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A structured transdisciplinary method for the experimental determination of friction in the nanometric domain is proposed in this paper. The dependence of nanoscale friction on multiple process parameters on these scales, which comprise normal forces, sliding velocities, and temperature, was studied via the lateral force microscopy approach. The procedure used to characterize the stiffness of the probes used, and especially the influence of adhesion on the obtained results, is thoroughly described. The analyzed thin films were obtained by using either atomic layer or pulsed laser deposition. The developed methodology, based on elaborated design of experiments algorithms, was successfully implemented to concurrently characterize the dependence of nanoscale friction in the multidimensional space defined by the considered process parameters. This enables the establishment of a novel methodology that extends the current state-of-the-art of nanotribological studies, as it allows not only the gathering of experimental data, but also the ability to do so systematically and concurrently for several influencing variables at once. This, in turn, creates the basis for determining generalizing correlations of the value of nanoscale friction in any multidimensional experimental space. These developments create the preconditions to eventually extend the available macro-and mesoscale friction models to a true multiscale model that will considerably improve the design, modelling and production of MEMS devices, as well as all precision positioning systems aimed at micro-and nanometric accuracy and precision.

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Section: Experimental Methodologymentioning

confidence: 99%

An experimental methodology for the concurrent characterization of multiple parameters influencing nanoscale friction

et al. 2019

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“…In the available literature, an increasing trend towards the development of friction models through a combination of experimental and numerical analyses can be observed. This can be seen in the application of statistical methods (Simonovic and Kalin, 2016) as well as other advanced mathematical modelling such as artificial neural networks, machine learning and artificial intelligence (Argatov, 2019; Ciulli, 2019). In previous work of the present authors, a model for prediction of friction in a cold forming process was developed by combining experimental data, statistical and numerical analyses (Lüchinger et al , 2018).…”

Section: Introductionmentioning

confidence: 99%

Optimisation of a chuck for cardboard can seaming – part 2: numerical modelling and statistical analyses

Velkavrh¹,

Ausserer²,

Klien³

et al. 2020

ILT

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Purpose In the cardboard package production process, the cardboard roll and the cardboard bottom are joined in the seaming process. During the process, the cardboard is plastically deformed and damage to the cardboard surface can occur. The purpose of this study was to optimise the macro-geometrical parameters of the seaming chuck in order to minimise the cardboard damage during the seaming process. Design/methodology/approach The influences of geometrical properties of the seaming chuck on the seaming force were investigated using numerical investigations and statistical analysis. Findings A force-displacement model was established, which enabled the optimisation of the seaming chuck geometry for a reduction of the seaming force. Research limitations/implications Results from the present study imply that for tribological optimisation, not only the surface properties such as roughness and frictional response but also the macro-geometrical features of the actual mechanical components should be considered, as these can considerably affect the contacting forces and consequently the friction within the tribosystem. Practical implications Based on the performed analyses, a new seaming chuck was manufactured, which is currently undergoing testing in the real production process and is providing improved performance in terms of seam quality as compared to the benchmark. Originality/value In the present work, a systematic approach towards the use of statistical methods in tribological optimisation projects is provided for a use case applying a combination of numerically calculated and experimentally measured values. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2020-0065/

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“…asperity contact model to address the roughness effect in lubricated contact [8], finite element method to solve the lubricated contact problem involving complex domain of surface contacts [9,13], and molecular dynamics simulation to investigate tribological phenomena in multiscale modelling [14,15]. Other than Reynolds Equation and its variants, other lubrication models in the literature revolve around regression analysis based on statistical approaches [16][17][18][19], empirical model driven by experimental observations [20,21], and models derived from first principles [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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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Methodology of a statistical and DOE approach to the prediction of performance in tribology – A DLC boundary-lubrication case study

Cited by 7 publications

References 36 publications

An experimental methodology for the concurrent characterization of multiple parameters influencing nanoscale friction

An experimental methodology for the concurrent characterization of multiple parameters influencing nanoscale friction

Optimisation of a chuck for cardboard can seaming – part 2: numerical modelling and statistical analyses

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

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