A comprehensive study of the tribological performance of the Al-Zn-Mg-Cu/Al₂O₃ composite and its matrix alloy is presented in this paper, with a specific emphasis to identify and model the applicable wear conditions where the composite provides a minimum of 50% reduction in wear rate and 25% lowering of the friction coefficient. Two-body abrasion experiments following Taguchi L₂₇ orthogonal design have been performed separately on alloy and composite materials, both prepared by the stir casting method. The influence of crucial control factors including silicon carbide (SiC) abrasive size, load, sliding distance, and velocity on the percentage variations of wear rates and friction coefficients between alloy and composite have been studied using the analysis of variance technique and full quadratic regression method. The dominant control factors are identified as abrasive size, load, and the interaction between abrasive size and load. This has been verified by establishing the influence of abrasive size and load on variations of wear mechanisms like microcutting, microploughing, and delamination, identified by means of in-depth characterization of worn surfaces and generated debris for both alloy and composite. The selection of applicable tribological condition for the composite has been accomplished by adopting the multi-response optimization technique based on combined desirability approach to obtain concurrent optimization of the percentage variations of wear rates and friction coefficients. Predictive models correlating the superiority of tribological performance of composite with abrasion conditions have been developed, and these are found to be accurate (errors <10%), as determined by confirmatory experiment.

中文翻译：

---

铝铸复合材料适用磨损条件的识别和建模

本文对Al-Zn-Mg-Cu / Al ₂ O ₃复合材料及其基体合金的摩擦学性能进行了全面研究，并特别着重于识别和建模复合材料提供最小磨损的适用磨损条件。磨损率降低50％，摩擦系数降低25％。Taguchi L ₂₇之后的两体磨损实验通过搅拌铸造法分别对合金和复合材料分别进行正交设计。使用方差分析和全二次回归方法研究了碳化硅（SiC）磨料尺寸，载荷，滑动距离和速度等关键控制因素对合金与复合材料之间磨损率和摩擦系数的百分比变化的影响。 。确定的主要控制因素为磨料尺寸，负载以及磨料尺寸与负载之间的相互作用。通过确定磨料尺寸和载荷对磨损机理（如微切削，微犁和分层）变化的影响已得到验证，这通过对磨损表面的深入表征以及合金和复合材料产生的碎屑来确定。通过采用基于组合期望方法的多响应优化技术来获得复合材料适用的摩擦学条件的选择，从而获得磨损率和摩擦系数的百分比变化的同时优化。已经建立了将复合材料的摩擦学性能与磨损条件的优越性相关联的预测模型，并且通过验证性实验确定，这些模型是准确的（误差<10％）。