Optimization of Multi-Track Laser Cladding Process Parameters for Fe-Cr-Ni Wear-Resistant Coatings via RSM-MOPSO

The surface of nodular cast iron is susceptible to wear failure under high-load conditions. In this study, Fe-Cr-Ni wear-resistant coatings were developed on the surface of nodular cast iron using laser cladding technology. The influence of laser power (P), powder feeding rate (F), scanning speed (V), and overlapping rate (φ) on the microhardness and dilution rate of the coatings was analyzed by response surface methodology, while the model’s accuracy was evaluated through analysis of variance. Subsequently, the multi-objective particle swarm optimization algorithm was utilized to identify the optimal process parameters (P = 1350 W, V = 12.5 mm/s, F = 9 g/min, and φ = 45%) based on non-destructive testing results. The predictive model values closely matched the experimental results. The average microhardness of the Fe-Cr-Ni cladding layer was 620.3 HV, which was 2.8 times that of the nodular cast iron substrate. Importantly, the laser cladding layer demonstrated a significant improvement in wear resistance compared to the substrate. The wear mechanisms for the coating predominantly involved mild abrasive wear and adhesive wear, while the substrate primarily experienced severe adhesive wear. This study offers valuable insights for optimizing laser cladding process parameters for nodular cast iron.

Authors

Institutions

Publication Details

Journal
Coatings
Published
2026-08-20
DOI
https://doi.org/10.3390/coatings16080991
Primary Topic
High Entropy Alloys Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of Multi-Track Laser Cladding Process Parameters for Fe-Cr-Ni Wear-Resistant Coatings via RSM-MOPSO

Bing Du, Yong Wang, Jixiang Xie, 正 孙 et al.
Coatings
High Entropy Alloys Studies
article

Optimization of Multi-Track Laser Cladding Process Parameters for Fe-Cr-Ni Wear-Resistant Coatings via RSM-MOPSO

Bing Du, Yong Wang, Jixiang Xie, 正 孙, Jie Chen, Yong Ye, Jin Yue
article en

Abstract

The surface of nodular cast iron is susceptible to wear failure under high-load conditions. In this study, Fe-Cr-Ni wear-resistant coatings were developed on the surface of nodular cast iron using laser cladding technology. The influence of laser power (P), powder feeding rate (F), scanning speed (V), and overlapping rate (φ) on the microhardness and dilution rate of the coatings was analyzed by response surface methodology, while the model’s accuracy was evaluated through analysis of variance. Subsequently, the multi-objective particle swarm optimization algorithm was utilized to identify the optimal process parameters (P = 1350 W, V = 12.5 mm/s, F = 9 g/min, and φ = 45%) based on non-destructive testing results. The predictive model values closely matched the experimental results. The average microhardness of the Fe-Cr-Ni cladding layer was 620.3 HV, which was 2.8 times that of the nodular cast iron substrate. Importantly, the laser cladding layer demonstrated a significant improvement in wear resistance compared to the substrate. The wear mechanisms for the coating predominantly involved mild abrasive wear and adhesive wear, while the substrate primarily experienced severe adhesive wear. This study offers valuable insights for optimizing laser cladding process parameters for nodular cast iron.

CoatingsVol. 16(8)
Chongqing University (CN), Chongqing University of Science and Technology (CN), Chongqing University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Chongqing, Chongqing Municipal Education Commission
Openalex Percentile: Top 18%
High Entropy Alloys Studies
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.