Optimization of manufacturing process effects on brake friction material wear

Manufacturing parameters of brake friction materials have a crucial impact on its friction and wear behavior. The effects of manufacturing parameters on wear have been modeled aiming at the optimization of facing behaviors. The influences of the five most important manufacturing parameters, such as molding pressure, molding time, molding temperature, heat-treatment temperature, and heat-treatment time, have been investigated. Their effects have been investigated on different formulations of the friction material and under different brake interface temperatures. The neuro-genetic optimization model was developed to be able to predict and optimize the effects of manufacturing parameters on the brake friction material wear.

[1]  Dragan Aleksendrić,et al.  Neural network prediction of disc brake performance , 2009 .

[2]  Adolfo Senatore,et al.  Experimental investigation and neural network prediction of brakes and clutch material frictional behaviour considering the sliding acceleration influence , 2011 .

[3]  Klaus Friedrich,et al.  Artificial neural networks for predicting sliding friction and wear properties of polyphenylene sulfide composites , 2011 .

[4]  Armando Blanco,et al.  A real-coded genetic algorithm for training recurrent neural networks , 2001, Neural Networks.

[5]  Bhabani K. Satapathy,et al.  Performance of friction materials based on variation in nature of organic fibres: Part I. Fade and recovery behaviour , 2004 .

[6]  A. Bahrami,et al.  Using GA–ANN algorithm to optimize soft magnetic properties of nanocrystalline mechanically alloyed Fe–Si powders , 2009 .

[7]  Vlastimil Matějka,et al.  Semimetallic Brake Friction Materials Containing ZrSiO4: Friction Performance and Friction Layers Evaluation , 2009 .

[8]  Driss Ouazar,et al.  Evolving neural network using real coded genetic algorithm for daily rainfall-runoff forecasting , 2009, Expert Syst. Appl..

[9]  Zhongya Zhang,et al.  Artificial neural networks applied to polymer composites: a review , 2003 .

[10]  S. Kim,et al.  Optimization of manufacturing parameters for a brake lining using Taguchi method , 2003 .

[11]  Dragan Aleksendrić,et al.  Prediction of automotive friction material characteristics using artificial neural networks-cold performance , 2006 .

[12]  Jayashree Bijwe,et al.  Friction and wear studies on brake-pad materials based on newly developed resin , 2007 .

[13]  K. Schiffner,et al.  Modeling of Compaction Processes of Friction Material Mixes , 2002 .

[14]  Dragan Aleksendrić,et al.  Neural network prediction of brake friction materials wear , 2010 .

[15]  Ling Han,et al.  Optimization of ceramic friction materials , 2006 .

[16]  Rongping Yun,et al.  Performance and evaluation of nonasbestos organic brake friction composites with SiC particles as an abrasive , 2011 .

[17]  Ali Selamat,et al.  An improvement on genetic-based learning method for fuzzy artificial neural networks , 2009, Appl. Soft Comput..

[18]  Hasan Ozturk,et al.  Artificial neural network-based prediction technique for wear loss quantities in Mo coatings , 2006 .

[19]  Zhenyu Jiang,et al.  Prediction on wear properties of polymer composites with artificial neural networks , 2007 .

[20]  Dragan Aleksendrić,et al.  Fade performance prediction of automotive friction materials by means of artificial neural networks , 2007 .

[21]  Klaus Friedrich,et al.  Prediction on tribological properties of short fibre composites using artificial neural networks , 2002 .

[22]  Nigel N. Clark,et al.  NEURAL NETWORK MODELLING OF THE EMISSIONS AND PERFORMANCE OF A HEAVY-DUTY DIESEL ENGINE , 2000 .

[23]  Yafei Lu,et al.  Optimization of a commercial brake pad formulation , 2002 .

[24]  A. Manan,et al.  Optimization of aeroelastic composite structures using evolutionary algorithms , 2010 .

[25]  Young-Don Ko,et al.  Modeling and optimization of the growth rate for ZnO thin films using neural networks and genetic algorithms , 2009, Expert Syst. Appl..

[26]  Andrew J. Day,et al.  Thermal Effects and Pressure Distributions in Brakes , 1991 .