A Taguchi Approach for Investigation of Erosion of Glass Fiber — Polyester Composites

Abstract

Polyester composites reinforced with three different weight fractions of woven E-glass fiber reinforcement are developed. To study the effect of various operational and material parameters on erosive wear behavior of these composites in an interacting environment, erosion test are carried out. For this purpose, an air jet type erosion test rig and the design of experiments approach utilizing Taguchi's orthogonal arrays are used. The findings of the experiments indicate that erodent size, fiber loading, impingement angle and impact velocity are the significant factors in a declining sequence affecting the wear rate. Significance of erosion efficiency in identifying the wear mechanism is highlighted. It is confirmed that the glass-reinforced-polyester composites exhibit mostly semi-ductile erosion response. An optimal parameter combination is determined, which leads to minimization of erosion rate. Analysis of variance (ANOVA) is performed on the measured data and signal to noise (S/N) ratios. A correlation derived from the results of Taguchi experimental design is proposed as a predictive equation for estimation of erosion wear rate of these composites. It is demonstrated that the predicted results obtained using this equation are consistent with experimental observations. Finally, optimal factor settings for minimum wear rate are determined using genetic algorithm.KEY WORDS: glass fiber reinforced polyester, taguchi method, design of experiment.

Erosion Behavior of Glass-epoxy Composites Filled with SiC from Bamboo Leaf

“…Exhaustive literature review on erosion behavior of polymer composites reveal that parameters namely; impact velocity, impingement angle, fiber loading, filler content, erodent size etc. largely influence the erosion rate of polymer composites (Patnaik et al 2008a(Patnaik et al , 2008b(Patnaik et al , 2008c(Patnaik et al , 2008dMahapatra, 2008;Patnaik et al, 2007;Aglan and Chenock, 1993;Harsha et al, 2003;Tamer and Taskiran, 2007;Tewari et al, 2002;Zhou et al, 2005;Rattan and Bijwe, 2007). In the present work, the impact of four such parameters are studied using L9 (3 4 ) orthogonal design.…”

High-temperature slurry erosion of vinylester matrix composites – The effect of test parameters

“…Thus, the erosion behaviour of a wide range of fibre-reinforced polymer composites with different matrix materials has recently been evaluated. These include glass and carbon fibre reinforced epoxy [3][4][5], polyester [6][7][8][9], polyetheretherketone (PEEK) [10], polyetherimine (PEI) [11,12] and polyphenylenesulphide (PPS) [13], to name a few. Typically, the effect of the reinforcement material, concentration, type and orientation as well as its adhesion to the matrix has been studied in these investigations.…”

Optimization of tribological behavior of nano clay particle with sisal/jute/glass/epoxy polymer hybrid composites using RSM

“…The Taguchi techniques used to design the experiment on weight loss and friction coefficient prediction models for polyamide‐6 composites filler with 0, 5, and 10 wt% wollastonite (W) particles with different parameters of sliding speed, applied load, and filler ratio . In addition, the analysis of variance (ANOVA) analysis and S/N ratio are used to obtain wear rate on Glass Fiber Polyester Composites . The L 8 orthogonal array used to design the experiment and influence the process parameters found by ANOVA and Linear regression equation, it is concluded that the addition of load and sliding speed is the most significant factors among the selected parameters …”

“…[16] In addition, the analysis of variance (ANOVA) analysis and S/N ratio are used to obtain wear rate on Glass Fiber Polyester Composites. [17] The L 8 orthogonal array used to design the experiment and influence the process parameters found by ANOVA and Linear regression equation, it is concluded that the addition of load and sliding speed is the most significant factors among the selected parameters. [18] Design of experiment techniques used for researchers is to minimize the number of experiments and determine significant factor in the selected design levels.…”