Composite materials are widely employed in various industries, such as aerospace, automobile, and sports equipment, owing to their lightweight and strong structure in comparison with conventional materials. Laser material processing is a rapid technique for performing the various processes on composite materials. In particular, laser forming is a flexible and reliable approach for shaping fiber-metal laminates (FMLs), which are widely used in the aerospace industry due to several advantages, such as high strength and light weight. In this study, a prediction model was developed for determining the optimal laser parameters (power and speed) when forming FML composites. Artificial neural networks (ANNs) were applied to estimate the process outputs (temperature and bending angle) as a result of the modeling process. For this purpose, several ANN models were developed using various strategies. Finally, the achieved results demonstrated the advantage of the models for predicting the optimal operational parameters.

中文翻译：

---

确定纤维增强复合材料激光成型最佳操作参数的预测模型

复合材料由于其与常规材料相比的轻质和结实的结构而广泛用于航空航天，汽车和运动器材等各种行业。激光材料加工是一种用于对复合材料执行各种工艺的快速技术。特别地，激光成型是一种用于成型纤维-金属层压板（FML）的灵活而可靠的方法，由于其具有诸如高强度和轻质等优点，因此广泛用于航空航天工业。在这项研究中，开发了一种预测模型，用于确定形成FML复合材料时的最佳激光参数（功率和速度）。作为建模过程的结果，人工神经网络（ANN）用于估计过程输出（温度和弯曲角度）。以此目的，使用各种策略开发了几种人工神经网络模型。最后，所获得的结果证明了模型在预测最佳运行参数方面的优势。