Influence of materials' hardness and operating parameters on the surface roughness during reciprocating sliding

被引:1
作者
Hanief, M. [1 ]
Mushtaq, Zahid [1 ,2 ]
Wani, Umar [1 ,3 ]
Qureshi, Irfan M. [1 ,4 ]
机构
[1] Natl Inst Technol Srinagar, Dept Mech Engn, Jammu 190006, Jammu & Kashmir, India
[2] Univ Kashmir, Mech Engn, Srinagar, Jammu & Kashmir, India
[3] J&K Govt, Publ Works Dept, Srinagar, Jammu & Kashmir, India
[4] NIT Srinagar, BTech & MTech, Srinagar, India
关键词
surface roughness; hardness; power law; regression; ANOVA; analysis of variance; ANN; artificial neural network; TAGUCHI METHOD; RUNNING-IN; PREDICTION; WEAR; OPTIMIZATION; REGRESSION; MODELS;
D O I
10.1504/IJNT.2021.119221
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
This paper investigates the influence of the hardness, sliding distance and time on the surface roughness during the sliding process. Three materials with different hardness were chosen for the study. The tests were performed on the reciprocating friction monitor (RFM) with ball-on-disc configuration. The steel balls of AISI 52100 were used to reciprocate over the discs of different materials. A total of 24 experiments were conducted with eight tests on each material. The surface roughness was recorded corresponding to each test. A power law and ANN model were developed for the surface roughness prediction. The competence of the models was evaluated by the statistical parameters, i.e., R-2, mean square error (MSE) and mean absolute percentage error (MAPE). It was found that R-2, MAPE and MSE for the power law model were 0.998, 4.130 x 10(-4), 14 x 10(-4) and for were ANN 0.998, 6.416 x 10(-4), 1.939 x 10(-4), respectively. Analysis of variance (ANOVA) was used to estimate the influence of each factor. From the ANOVA, sliding distance was found to have the significant influence on the surface roughness followed by the material hardness and time.
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页码:980 / 989
页数:10
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