ABSTRACT

This research addresses the influence of the Abrasive Water Jet Machining (AWJM) process parameters on the Chicken Feather Fiber (CFF) composite. The CFF composite was prepared using the waste chicken feather by a compression molding process. The AWJM experiments were conducted with different process parameters of water pressure (p), standoff distance (d), and nozzle transfer speed (s) and investigated their impact on surface roughness. The process parameter optimization has also been carried out, for better surface quality. The better surface quality was obtained for the combination of 350 MPa of water pressure, 80 mm/min of nozzle transfer speed, and 3 mm standoff distance. The surface quality has been improved using the optimized process parameters during the AWJM of the CFF composite in the confirmation experiments. Prediction of surface roughness has also been carried out by Artificial Neural Networks (ANN) and Response Surface Methodology (RSM) techniques. The comparison of the predicted surface roughness results with the experimental results has also been carried out, and the predicted results were very close to the experimental valves it shows the efficiency of the results.

摘要

本研究探讨了磨料水射流加工 (AWJM) 工艺参数对鸡毛纤维 (CFF) 复合材料的影响。CFF复合材料是使用废鸡羽毛通过压缩成型工艺制备的。AWJM 实验是在水压 (p)、间隔距离 (d) 和喷嘴转移速度 (s) 等不同工艺参数下进行的，并研究了它们对表面粗糙度的影响。还进行了工艺参数优化，以获得更好的表面质量。350 MPa 的水压、80 mm/min 的喷嘴传输速度和 3 mm 的间隔距离的组合获得了更好的表面质量。在确认实验中，在 CFF 复合材料的 AWJM 期间，使用优化的工艺参数提高了表面质量。表面粗糙度的预测也已通过人工神经网络 (ANN) 和响应曲面方法 (RSM) 技术进行。还进行了预测的表面粗糙度结果与实验结果的比较，预测结果与实验阀门非常接近，说明了结果的有效性。