This work aims to apply data-driven approach [decision tree (DT) algorithm] to analyse the wear rate (WR) of ZnO-filled AA7075 composites. The results of model-based analysis was compared with Taguchi analysis. Stir casting was used to produce the composite samples. Characterization studies were conducted to analyse the composition and morphology. The scanning electron microscopy results indicated the even dispersion of ZnO in the AA7075. The energy-dispersive x-ray spectroscopy pattern ensures the presence of matrix elements and the inclusion of reinforcement particles into the proposed composites. To minimize the number of experimentation, L27 Orthogonal array is used for finding WR. The ‘DuCom’ Pin-on-Disc apparatus were used to prepare WR data for the set of the proposed composites. Taguchi technique reveals the optimum level factors for obtaining the minimum ‘WR’ is reinforcement content of 10 wt.%, applied load (P) at 10 N, sliding velocity (V) at 1 m s⁻¹ and sliding distance (D) of 1000 m. The experiments results from DT algorithm, and analysis of variance and signal-to-noise ratio analysis from Taguchi-based approach confirmed that reinforcement is the primary element for affecting wear of the composites. The reason for applying DT algorithm is that, the low-level knowledge could be converted into high-level knowledge (If-then-else rules), which can be effortlessly explicable by semiskilled personnel.

这项工作旨在应用数据驱动的方法 [决策树 (DT) 算法] 来分析 ZnO 填充的 AA7075 复合材料的磨损率 (WR)。将基于模型的分析结果与田口分析进行比较。搅拌铸造用于生产复合样品。进行表征研究以分析组成和形态。扫描电子显微镜结果表明 ZnO 在 AA7075 中均匀分散。能量色散 X 射线光谱图确保基体元素的存在和增强颗粒包含在所提出的复合材料中。为了尽量减少实验次数，L27 正交阵列用于寻找 WR。'DuCom' Pin-on-Disc 装置用于为一组建议的复合材料准备 WR 数据。⁻¹和 1000 m 的滑动距离 (D)。DT 算法的实验结果以及基于田口方法的方差分析和信噪比分析证实，加固是影响复合材料磨损的主要因素。应用DT算法的原因是，低级知识可以转换为高级知识（If-then-else规则），半熟练人员可以毫不费力地解释。