ABSTRACT

Metal Matrix Composite (MMC) materials are having enhanced characteristics and considered as an alternate material for various engineering applications. Due to reinforcement added, the materials become harder which results in poor machining performance by conventional machining techniques. Wire Electrical Discharge Machining (WEDM) is an effective method for making complex shapes in harder material that are electrically conductive. In this present exploration, an analysis has been performed on machinability of WEDM of Hybrid MMC (AA2024+Al₂O₃+BN) which is prepared by stir cast process and development of artificial intelligent decision-making tool for WEDM process. The ascendancy of variables namely duration of pulse on, pulse off and applied current in contrast to preferred performance parameters such as material removal rate, surface roughness, dimensional deviation, and orientation tolerance error were investigated. Grey theory has been engaged for attaining gray relational coefficient values and considered as an input information to develop the Grey-ANFIS model for predicting the desired performance measures. An analysis has been performed by comparing the experimentation outcomes and predicted values. Also the performance of developed Grey-ANFIS model is analyzed to disclose the competency and it is proved that the model is capable of predicting the desired performance measures in an effective manner.

摘要

金属基复合材料（MMC）材料具有增强的特性，被认为是各种工程应用的替代材料。由于添加了增强材料，材料变得更硬，这导致常规加工技术的加工性能差。线材放电加工（WEDM）是一种在较硬的导电材料中制成复杂形状的有效方法。在本次探索中，对混合MMC（AA2024 + Al ₂ O ₃+ BN）是通过搅拌铸造工艺和WEDM工艺的人工智能决策工具的开发而制备的。与首选的性能参数（例如材料去除率，表面粗糙度，尺寸偏差和方向公差）相比，研究了变量上升的时间，即脉冲接通，脉冲断开和施加电流的持续时间。灰色理论已被用于获得灰色关联系数值，并被视为开发Grey-ANFIS模型以预测所需性能指标的输入信息。通过比较实验结果和预测值进行了分析。