Design and evaluation of abrasion pot experiments using statistical methods

Statistical Analysis of Abrasive Wear Data of Aramid Fabric-reinforced Polyethersulfone Composites

“…In this case, the selected parameters were the weight of fabric (Z 1 ), the abrasive particle size (Z 2 ), and the load (Z 3 ); and their test levels are given in Table 1, where a i is the lower level and b i is the higher level of Z i . The standardized value X i , whose value generally falls within the range [À1, 1] [20] corresponding to the levels of a i and b i respectively, can be calculated as follows:…”

“…In order to have a better understanding of the wear behavior of the polymer, it is very important to know the effect of these parameters and their interactions. Despite the thorough investigations on the abrasive wear behavior of the polymers and the metals, less is reported on the influence of the various operating parameters and their interactions on the abrasive wear behavior of the polymers and the metals [15][16][17][18][19][20][21].…”

“…While investigating the wear behavior of the PA6/UHMWPE blend using a statistical method, Liu et al [19] reported that the wear rate of the blend was more sensitive to the pressure and surface roughness, while the sliding distance and sliding speed had less significant influence on the wear behavior of the blend. The statistical analysis of the slurry erosion behavior of the metals using an electrochemical technique by Wandke and Rasemann [20] revealed that the liquid to solid ratio of the slurry and the type of acid used were found to be the important factors, which caused erosion of the materials. While investigating the extent of influence of the operating parameters on the abrasive wear behavior of the Ni-based alloys using the factorial design method, Fernandez et al [21] observed that the abrasive particle size and the reinforcement were more dominating parameters in controlling the abrasive wear behavior of the Ni-based alloy than that of the load and the hardness.…”