Citation :

Jawahar Thangavelu, 2024. "Artificial Intelligence in Engineering Design: Enhancing Creativity and Efficiency" ESP International Journal of Advancements in Science & Technology (ESP-IJAST) Volume 2, Issue 3: 29-39.

Abstract :

Today, engineering design has been enhanced significantly by the integration of Artificial Intelligence (AI). By simplifying routine work related to parametric design and performance optimization, AI enables engineers to work on more advanced tasks. The fast processing of large amounts of data makes it possible for designers to consider a great number of design solutions within a considerably shorter time than it would take with traditional approaches. This has mainly resulted in shorter design cycle times as well as reductions in the amounts of material used and total costs of a project. Techniques such as generative design and machine learning have yielded highly satisfying results in terms of structure, pattern recognition and results prediction, offering solutions that were impossible by normal means.

This paper presents a detailed review of the modern AI methods and tools that expedite engineering design in several sectors, including aerospace and automotive, as well as the civil engineering industry. We discuss the state of the art of AI for design, based on the application of AI in structural optimization, CFD, and FEA. This paper shows virtually and practically how artificial intelligence is improving design applications, precision, and creativity in engineering designs through a review of literature and experimental case studies. Furthermore, the paper outlines some potentially serious issues related to AI implementation, such as the inadequate integration of data sources, the understanding of multilayer structures of most modern AI models, and human supervision of the AI results. Last, we discuss future research implications for overcoming these challenges in an effort to enhance the practicality and utility of AI for design practice.

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Keywords :

Artificial Intelligence (AI), Engineering Design, Creativity, Efficiency, Machine Learning, Generative Design, Optimization Algorithms, Collaborative Design, Automation, Predictive Analytics, Design Thinking, Innovation.