Optimization of tribo-performance of brake friction materials: Effect of nano filler

Singh, Tej; Patnaik, Amar; Gangil, Brijesh; Chauhan, Ranchan

doi:10.1016/j.wear.2014.11.020

Cited by 86 publications

(37 citation statements)

References 29 publications

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“…Unlike the most MCDM methods, the PSI method does not require determination of the relative importance of the criteria, and, therefore, it is not necessary to determine criteria weights. Thus, the method is particularly useful in the cases where a conflict in deciding the relative importance among criteria appears [9]. Actually, the PSI method determines criteria weights only by using information provided in the decision matrix, i.e.…”

Section: Preference Selection Index (Psi) Methodsmentioning

confidence: 99%

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Application of the Performance Selection Index Method for Solving Machining McDm Problems

et al. 2017

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Section: Preference Selection Index (Psi) Methodsmentioning

confidence: 99%

“…it uses an objective approach to determine criteria weights like standard deviation or entropy method. The main application procedure of the PSI method for solving MCDM problems includes several steps [8][9][10][11]:…”

Section: Preference Selection Index (Psi) Methodsmentioning

confidence: 99%

Application of the Performance Selection Index Method for Solving Machining McDm Problems

et al. 2017

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“…The weighted matrix is thus obtained by using Eq. (12). However, for the sake of brevity, the weighted matrix is not presented here.…”

Section: Ranking Based On Topsismentioning

confidence: 99%

PSI and TOPSIS Based Selection of Process Parameters in WEDM

Diyaley

Shilal²,

Shivakoti

et al. 2017

Period. Polytech. Mech. Eng.

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IntroductionWith the development of technology, more challenging problems are being faced by the technologists in the field of manufacturing. The difficulty in adopting the conventional manufacturing processes can be attributed mainly to the machining principle that requires a cutting tool which must be harder than the material of the work-piece. New materials which have a high strength-to-weight ratio, heat resistance and high hardness are tough to machine and also timeconsuming by conventional methods. Hence, advanced machining processes are being developed to overcome these difficulties. These newly developed techniques provide a very high accuracy and can machine complexly shaped surfaces. These processes, however, are not meant for replacing the conventional processes but are a supplement to them.Optimization and selection of proper process parameters play a vital role in any of the manufacturing or metal processing industries. Selection of proper cutting conditions is essential for efficient machining. Improper selection of machining parameters leads to several adverse effects during machining. Optimization technique provides a proper selection of cutting parameters. Many research attempts have been made to select the proper cutting parameters in WEDM. In past response surface methodology has been used to enumerate the relationship between input and output responses in the WEDM process and the effects of input process parameters on MRR and surface roughness were studied by Gowd et al. [1]. Tilekar et al. [2] investigated to analyze the effect of process parameters on surface roughness and kerf width of aluminium and mild steel. Taguchi method opted for the optimization. Spark on time, spark off time, input current and wire feed rate were used as input parameters and ANOVA results showed that spark on time and input current have statistically significant effect in the case of aluminium and mild steel respectively. Dabade and Karidkar [3] analyzed the machining conditions of material removal rate, surface roughness and kerf width and dimensional deviation during WEDM of Inconel 718 using Taguchi technique. It was observed that pulse on time was the most influencing factor. Patel et al. [4] applied AHP/TOPSIS

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“…The role of Kevlar fibre has been well reported to aid wear minimization and friction stabilization (Gopal et al, 1996;Kim et al, 2001;Kumar et al, 2011). Lapinus fibres inherently comprising metallic-silicates, when combined synergistically with other fibres that improved the tribo-performance and suppress the unwanted phenomenon like noise, vibration, judder over wide range of driving conditions Dadkar et al, 2010;Singh et al, 2015b). Wollastonite fibres having high thermal resilience and inherent hardness have been found to stabilize the coefficient of friction (l) and maximize recovery performance (Santoso and Anderson, 1985;Kogel et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Assessment of braking performance of lapinus–wollastonite fibre reinforced friction composite materials

Singh

Patnaik

Chauhan

et al. 2017

Journal of King Saud University - Engineering Sciences

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Brake friction materials comprising of varying proportions of lapinus and wollastonite fibres are designed, fabricated and characterized for their chemical, physical, mechanical and tribological properties. Tribological performance evaluation in terms of performance coefficient of friction, friction-fade, friction-recovery, disc temperature rise (DTR) and wear is carried out on a Krauss machine following regulations laid down by Economic Commission of Europe (ECE R-90). The increase in wollastonite fibre led to an increase in density and hardness whereas void content, heat swelling, water absorption and compressibility increased with the increased in lapinus fibre. The performance coefficient of friction, friction-fade behaviour and friction-stability have been observed to be highly dependent on the fibre combination ratio i.e. coefficient of friction, fade and friction-stability follow a consistent decrease with a decrease in the lapinus fibre content, whereas the frictional fluctuations in terms of l max À l min have been observed to increase with a decrease in lapinus fibre content. However, with an increase in wollastonite fibre content in formulation mix, a higher wear resistance and recovery response is registered. The worn surface morphology has revealed topographical variations and their underlying role in controlling the friction and wear performance of such brake friction composites. ª 2015 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Optimization of tribo-performance of brake friction materials: Effect of nano filler

Cited by 86 publications

References 29 publications

Application of the Performance Selection Index Method for Solving Machining McDm Problems

Application of the Performance Selection Index Method for Solving Machining McDm Problems

PSI and TOPSIS Based Selection of Process Parameters in WEDM

Assessment of braking performance of lapinus–wollastonite fibre reinforced friction composite materials

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