The present study aims to multi factor optimization for preparation of aluminum matrix composites (AMC) by reinforcement of SiC/ Al₂O₃/ Al₂O₃+ SiC particles having dual particle size (DPS) and triplicate particle size (TPS) based upon signal to noise (S/N) ratio analysis. In this work the amalgamation of fused deposition modelling (FDM) and vacuum moulding (V-process) assisted stir casting (SC) has been employed for the development of AMC. The process parameters under investigation are: particle size (DPS/ TPS); reinforcement type (Al₂O₃/ SiC/ Al₂O₃+ SiC); vacuum pressure (VP) (300-400 mm of Hg); moulding sand grit size (American foundry society (AFS) No. 50-70); vibration time (VT) (4-6 sec) and reinforcement proportion/composition (5/7.5/10 by wt.%). The S/N ratio based upon the wear performance (pin-on disc tester), micro hardness (HV) and dimensional accuracy/deviation (Δt) has been evaluated by using Minitab-17 software which further acts as input for multifactor optimization. The best parametric setting proposed for multi objective/factor optimization is: DPS of Al₂O₃+ SiC reinforcement at 350 mm of Hg VP with 50 AFS No. sand grain size, 4sec VT and 10% composition/proportion. The results of analysis of variance (ANOVA) highlight that particle size (with 18.49% contribution) and reinforcement type (with 42.13% contribution) have significant influence on multi factor optimization for the development of AMC. Confirmatory experiments have been performed which shows that the proposed amalgamation of FDM and V-process assisted SC can be successfully applied for enhancing the performance of AMC. Finally the X-chart and R-chart have been plotted at the proposed settings, which highlights that amalgamation process is controlled and useful for mass/ batch production.

中文翻译：

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混合铝基复合材料开发的多因素优化

本研究旨在通过增强SiC / Al ₂ O ₃ / Al ₂ O ₃ +具有双重粒径（DPS）和三重粒径（TPS）的SiC颗粒来制备铝基复合材料（AMC）的多因素优化。信噪比（S / N）分析。在这项工作中，融合沉积模型（FDM）和真空成型（V-process）辅助搅拌铸造（SC）的合并已用于AMC的开发。研究中的工艺参数为：粒径（DPS / TPS）；增强型（Al ₂ O ₃ / SiC / Al ₂ O ₃+ SiC）; 真空压力（VP）（300-400毫米汞柱）; 型砂粒度（美国铸造学会（AFS）第50-70号）; 振动时间（VT）（4-6秒）和增强比例/组成（5 / 7.5 / 10 wt。％）。通过使用Minitab-17软件评估了基于磨损性能（针式圆盘测试仪），显微硬度（HV）和尺寸精度/偏差（Δt）的信噪比，该软件进一步用作多因素优化的输入。为多目标/因素优化建议的最佳参数设置是：Al ₂ O _3的DPS+ SiC增强剂在350 mm Hg VP下具有50 AFS号砂粒尺寸，4sec VT和10％的组成/比例。方差分析（ANOVA）的结果表明，粒径（占18.49％）和增强类型（占42.13％）对AMC发展的多因素优化具有重要影响。已经进行了验证性实验，表明所提出的FDM与V-过程辅助SC的合并可以成功地用于增强AMC的性能。最后，在建议的设置下绘制了X图表和R图表，这突出说明了合并过程是可控的，可用于批量生产。