AI-DRIVEN COMPUTER-AIDED DESIGN (CAD) SYSTEMS: LEVERAGING NEURAL NETWORKS FOR OPTIMIZED ENGINEERING PRODUCT DEVELOPMENT

Abstract

Computer-Aided Design (CAD) systems are foundational to modern engineering, enabling the creation of precise digital models. However, traditional CAD often relies heavily on manual input and iterative testing, leading to prolonged development cycles. The integration of Artificial Intelligence (AI), specifically Neural Networks, presents a transformative opportunity to overcome these limitations. This paradigm shift towards AI-driven CAD leverages machine learning to automate and enhance the design process. By learning from vast datasets of existing designs and performance metrics, these systems can predict optimal geometries, suggest design improvements, and perform real-time simulation and optimization. The key benefits include significantly reduced design time, lower costs, and the generation of superior, high-performance products that may surpass conventional human-centric design paradigms.