Effect of tribological parameters and their optimization for wear responses of TiAlN coating

IF 1.3 4区 材料科学 Q4 MATERIALS SCIENCE, MULTIDISCIPLINARY Emerging Materials Research Pub Date : 2023-03-01 DOI:10.1680/jemmr.22.00015
Sunil Kumar, S. Maity, Lokeswar Patnaik
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引用次数: 1

Abstract

This study investigates the relative effect of tribological process parameters and their optimization for wear responses of TiAlN thin film deposited on heat-treated and plasma nitrided novel MDC-K hot work tool steel. The effect of tribological process parameters was studied by conducting the tribological test on TiAlN thin film against Tungsten Carbide (WC) counterbody. There were three tribological process parameters considered namely: sliding velocity, applied load, and sliding distance to conduct the tribological test and study their effect on five different wear responses, namely friction coefficient (COF), surface roughness (Ra), wear depth (WD), wear mass loss (WML), and hardness (Hv). The relative effect of the process parameters was studied using counter plots and the individual effect and contribution were analyzed using the ANOVA test. Further, t overall evaluation criteria (OEC) method was employed to select the optimal setting of tribological process parameters based on the experimental results. Finally, the surface morphology of the worn TiAlN surface against the best and worst parametric settings was evaluated using EDS-integrated SEM to investigate the underlying wear mechanisms.
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摩擦学参数及其优化对TiAlN涂层磨损响应的影响
研究了热处理和等离子体氮化新型热加工工具钢表面沉积TiAlN薄膜的摩擦学工艺参数及其优化对其磨损响应的相对影响。通过对TiAlN薄膜与碳化钨(WC)摩擦体的摩擦学试验,研究了工艺参数对TiAlN薄膜摩擦学性能的影响。考虑滑动速度、施加载荷和滑动距离三个摩擦学过程参数,进行摩擦学试验,研究其对摩擦系数(COF)、表面粗糙度(Ra)、磨损深度(WD)、磨损质量损失(WML)和硬度(Hv)五种不同磨损响应的影响。用对照图研究了各工艺参数的相对影响,用方差分析检验分析了个体效应和贡献。基于实验结果,采用综合评价准则(OEC)法选择摩擦学工艺参数的最优设置。最后,利用集成eds的扫描电镜对最佳和最差参数设置下磨损的TiAlN表面形貌进行了评估,以研究潜在的磨损机制。
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来源期刊
Emerging Materials Research
Emerging Materials Research MATERIALS SCIENCE, MULTIDISCIPLINARY-
CiteScore
4.50
自引率
9.10%
发文量
62
期刊介绍: Materials Research is constantly evolving and correlations between process, structure, properties and performance which are application specific require expert understanding at the macro-, micro- and nano-scale. The ability to intelligently manipulate material properties and tailor them for desired applications is of constant interest and challenge within universities, national labs and industry.
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