Response surface methodology-based optimization of laser cladding parameters for hardness of AlTiSiCrCo coated Ti6Al4V

Abstract This study investigates the optimization of laser cladding parameters to enhance the surface hardness of Ti6Al4V using an equiatomic AlTiSiCrCo high entropy alloy (HEA) coating. Although Ti6Al4V exhibits superior mechanical properties and corrosion resistance, its relatively low hardness limits its application in various industries such as aerospace, chemical, and biomedical. To address this limitation, response surface methodology (RSM) with a central composite design (CCD) was employed to investigate the effects of laser power (0.6–1.0 kW) and scan speed (0.3–1.2 m min −1 ) on the surface hardness. Laser cladding was performed using a 3-kW fiber laser system, and microhardness measurements were conducted on cross-sectioned samples to evaluate the response. The results showed that the highest hardness of 840.87 HV at 0.8 kW and 0.3 m min −1 occurred at extreme conditions but were filled with cracks and pores. In contrast, the parameter combination of 0.8 kW and 0.75 m min −1 achieved an optimum hardness of 533.23 HV with a defect-free microstructure. This study focused on hardness and macrostructural observations (cracks and pores), crystallographic analysis was outside of the scope of the study. This condition presented the best combination of hardness and coating integrity. ANOVA confirmed the model significance (R 2 = 0.9537, adjusted R 2 = 0.9207). Although the predicted R 2 (0.6709) was lower, the experiments validated the predictive capability of the model. This study showed that RSM is effective for identifying the processing window of laser cladding HEA, where optimum must be a balance between hardness properties and defect and crack free coat.

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Publication Details

Journal
Engineering Research Express
Published
2025-09-23
DOI
https://doi.org/10.1088/2631-8695/ae0ab6
Citations
1
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
0.71
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article

Response surface methodology-based optimization of laser cladding parameters for hardness of AlTiSiCrCo coated Ti6Al4V

Samuel Skhosane, Mamookho Elizabeth Makhatha, Nkutwane Washington Makoana, Kabelo Matome Raselabe
1 citations
Engineering Research Express
Additive Manufacturing Materials and Processes
0.71
article

Response surface methodology-based optimization of laser cladding parameters for hardness of AlTiSiCrCo coated Ti6Al4V

Samuel Skhosane, Mamookho Elizabeth Makhatha, Nkutwane Washington Makoana, Kabelo Matome Raselabe
article en
1 citations

Abstract

Abstract This study investigates the optimization of laser cladding parameters to enhance the surface hardness of Ti6Al4V using an equiatomic AlTiSiCrCo high entropy alloy (HEA) coating. Although Ti6Al4V exhibits superior mechanical properties and corrosion resistance, its relatively low hardness limits its application in various industries such as aerospace, chemical, and biomedical. To address this limitation, response surface methodology (RSM) with a central composite design (CCD) was employed to investigate the effects of laser power (0.6–1.0 kW) and scan speed (0.3–1.2 m min −1 ) on the surface hardness. Laser cladding was performed using a 3-kW fiber laser system, and microhardness measurements were conducted on cross-sectioned samples to evaluate the response. The results showed that the highest hardness of 840.87 HV at 0.8 kW and 0.3 m min −1 occurred at extreme conditions but were filled with cracks and pores. In contrast, the parameter combination of 0.8 kW and 0.75 m min −1 achieved an optimum hardness of 533.23 HV with a defect-free microstructure. This study focused on hardness and macrostructural observations (cracks and pores), crystallographic analysis was outside of the scope of the study. This condition presented the best combination of hardness and coating integrity. ANOVA confirmed the model significance (R 2 = 0.9537, adjusted R 2 = 0.9207). Although the predicted R 2 (0.6709) was lower, the experiments validated the predictive capability of the model. This study showed that RSM is effective for identifying the processing window of laser cladding HEA, where optimum must be a balance between hardness properties and defect and crack free coat.

Engineering Research ExpressVol. 7(4)
Council for Scientific and Industrial Research (ZA), University of Johannesburg (ZA)
Openalex Percentile: Top 27%
Additive Manufacturing Materials and Processes
0.71
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