The present research deals with laser surface texturing (LST) on titanium super alloy considering four important LST parameters viz. average power, pulse frequency, scan speed and gas pressure. The material removal rate (MRR) and average texture width (ATW) are evaluated at various parametric combinations. Experiments are conducted on a multi-diode Nd: YAG laser as per a L16 orthogonal array design. The main effects and the interaction effect of the four LST variables on the two responses i.e., MRR and ATW are studied. To simultaneously optimize all the LST parameters such that the desired performance of the responses is achieved multi-criteria decision-making (MCDM) method is used. Hybrid-MCDM formulations are introduced in this paper by using Preference Selection Index (PSI) in conjunction with Technique for order preference by similarity to the ideal solution (TOPSIS) and Evaluation based on Distance from Average Solution (EDAS). The hybrid PSI-TOPSIS and PSI-EDAS are evaluated by comparing with three popular objective methods (viz. mean-weight method, standard deviation method and entropy method) of weight allocation to criteria. It is observed that except for Entropy-TOPSIS and PSI-TOPSIS all other methods predict A3B4C3D3 as the optimal process parameter combination.

本研究涉及钛超级合金的激光表面纹理化 (LST)，考虑四个重要的 LST 参数，即。平均功率、脉冲频率、扫描速度和气体压力。在各种参数组合下评估材料去除率 (MRR) 和平均纹理宽度 (ATW)。根据 L16 正交阵列设计，在多二极管 Nd:YAG 激光器上进行实验。研究了四个 LST 变量对两个响应即 MRR 和 ATW 的主要影响和交互作用。为了同时优化所有 LST 参数，从而实现所需的响应性能，使用了多标准决策 (MCDM) 方法。本文通过使用偏好选择指数 (PSI) 结合通过与理想解决方案的相似性 (TOPSIS) 和基于与平均解决方案的距离 (EDAS) 进行评估的顺序偏好技术，介绍了混合 MCDM 公式。混合 PSI-TOPSIS 和 PSI-EDAS 通过与三种流行的目标方法（即平均权重法、标准差法和熵法）进行权重分配来评估。据观察，除了 Entropy-TOPSIS 和 PSI-TOPSIS 之外，所有其他方法都将 A3B4C3D3 预测为最佳工艺参数组合。标准差法和熵法）的权重分配。据观察，除了 Entropy-TOPSIS 和 PSI-TOPSIS 之外，所有其他方法都将 A3B4C3D3 预测为最佳工艺参数组合。标准差法和熵法）的权重分配。据观察，除了 Entropy-TOPSIS 和 PSI-TOPSIS 之外，所有其他方法都将 A3B4C3D3 预测为最佳工艺参数组合。