Investigation of the effect of Fiber Laser Parameter on Arithmetic Mean Height (Sa) and Friction coefficient of ST52 Steel Surface

In this study, the surfaces of ST52 steel plates were textured using a fiber laser. The topographies of the resulting surfaces were examined, and the relationship between the coefficient of friction and the Arithmetic Mean Height (Sa) of the surface was investigated, focusing on the Arithmetic Mean Height (Sa) of the surface roughness parameters. Different laser parameters were used to obtain different Sa values. To minimize the Sa value and thus reduce the coefficient of friction, three independent laser parameters were examined: laser power, scan area ratio, and the type of pattern created on the surface. The three parameters were examined at four levels using the Taguchi Optimization Method. As a result of the Taguchi optimization method, it was predicted that the Sa value would be 4.24 when using the necessary laser parameter levels for obtaining the lowest coefficient of friction, with a square pattern type, 20% scan area, and 40W laser power. The ANOVA analysis revealed that the parameters most influential in obtaining optimum values were, in order, azer power (48.61% contribution), followed by scanning area ratio (32.67%) and pattern type (18.72%). The results of the study show that the friction coefficients of surfaces can be altered by precisely controlling the Arithmetic Mean Height (Sa), a parameter of surface roughness.

Authors

Institutions

Publication Details

Journal
Natural and Applied Sciences Journal
Published
2026-06-30
DOI
https://doi.org/10.38061/idunas.1951856
Primary Topic
Tribology and Lubrication Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigation of the effect of Fiber Laser Parameter on Arithmetic Mean Height (Sa) and Friction coefficient of ST52 Steel Surface

Timur Canel, Çağla PİLAVCI
Natural and Applied Sciences Journal
Tribology and Lubrication Engineering
article

Investigation of the effect of Fiber Laser Parameter on Arithmetic Mean Height (Sa) and Friction coefficient of ST52 Steel Surface

Timur Canel, Çağla PİLAVCI
article en

Abstract

In this study, the surfaces of ST52 steel plates were textured using a fiber laser. The topographies of the resulting surfaces were examined, and the relationship between the coefficient of friction and the Arithmetic Mean Height (Sa) of the surface was investigated, focusing on the Arithmetic Mean Height (Sa) of the surface roughness parameters. Different laser parameters were used to obtain different Sa values. To minimize the Sa value and thus reduce the coefficient of friction, three independent laser parameters were examined: laser power, scan area ratio, and the type of pattern created on the surface. The three parameters were examined at four levels using the Taguchi Optimization Method. As a result of the Taguchi optimization method, it was predicted that the Sa value would be 4.24 when using the necessary laser parameter levels for obtaining the lowest coefficient of friction, with a square pattern type, 20% scan area, and 40W laser power. The ANOVA analysis revealed that the parameters most influential in obtaining optimum values were, in order, azer power (48.61% contribution), followed by scanning area ratio (32.67%) and pattern type (18.72%). The results of the study show that the friction coefficients of surfaces can be altered by precisely controlling the Arithmetic Mean Height (Sa), a parameter of surface roughness.

Natural and Applied Sciences JournalVol. 9(1)
Kocaeli Üniversitesi (TR)
Sustainable cities and communities
Openalex Percentile: Top 14%
Tribology and Lubrication Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.