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

Authors: M. Hanief; Zahid Mushtaq; Umar Wani; Irfan M. Qureshi

Addresses: Mechanical Engineering Department, National Institute of Technology Srinagar, Jammu and Kashmir – 190006, India ' Mechanical Engineering Department, National Institute of Technology Srinagar, Jammu and Kashmir – 190006, India ' Mechanical Engineering Department, National Institute of Technology Srinagar, Jammu and Kashmir – 190006, India ' Mechanical Engineering Department, National Institute of Technology Srinagar, Jammu and Kashmir – 190006, India

Abstract: 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., R2, mean square error (MSE) and mean absolute percentage error (MAPE). It was found that R2, MAPE and MSE for the power law model were 0.998, 4.130 × 10-4, 14 × 10-4 and for were ANN 0.998, 6.416 × 10-4, 1.939 × 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.

Keywords: surface roughness; hardness; power law; regression; ANOVA; analysis of variance; ANN; artificial neural network.

DOI: 10.1504/IJNT.2021.119221

International Journal of Nanotechnology, 2021 Vol.18 No.11/12, pp.980 - 989

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 21 Nov 2021 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article