Work

A review of AI application trends in industrial design

Year: 2025

Type: conference-paper

Abstract: This article presents a comprehensive literature review of recent trends in the application of Artificial Intelligence (AI) in the industrial design arena. The review primarily focuses on studies published since 2017, selected from high-quality Q1 and Q2 journals accessed through databases such as Science Direct, Scopus, and IEEE Explore. The review employed the ‘Targeted Literature Review’ methodology, ensuring a focused and relevant analysis of AI applications in industrial design. Key trends identified include the use of Machine Learning (ML) and Natural Language Processing (NLP) for extracting customer requirements, Deep Learning (DL) for generating design alternatives, and optimization algorithms for improving product prototypes. Notably, AI tools are not only automating routine design tasks but also emerging as creative collaborators, significantly enhancing human-technology interaction. The findings highlight AI’s ability to optimize design processes, streamline collaboration between human designers and AI systems, and redefine the boundaries of innovation in industrial design.

Source: Procedia Computer Science

DOI: 10.1016/j.procs.2025.07.008

Authors: María Villalba, Manuel Palomar

Institution: University of Alicante

Language: English

Topic: Design Education and Practice

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

Funders: Universidad de Alicante, Generalitat Valenciana

Award: G2872123551