Artificial intelligence in industrial design: A semi-automated literature survey

Abstract

In the era of industry 4.0, artificial intelligence (AI) may potentially be used to provide reasoning and decision support on engineering and technical challenges. The role of AI in industrial design, which is the practice of improving the function, value and aesthetics of products to optimise customer satisfaction, has not yet been extensively explored. To effectively synthesise the existing literature, an unsupervised learning-enabled review methodology is proposed in this study. Important journals and articles are identified by using k-means clustering, and the relevant articles are analysed by using co-citation, bibliographic coupling, and co-occurrence analyses. Six clusters of the body of knowledge are then extracted, and naming of the clusters is assisted by using document summarisation and evaluation. Consequently, six intellectual cores related to AI in industrial design are formulated: (i) supply chain perspectives on product design and innovation, (ii) manufacturability and performance of new product development, (iii) intelligent tools and systems for industrial design and engineering, (iv) applied intelligence for product and service innovation, (v) industry 4.0 technologies for design and manufacturing, and (vi) blockchain-enabled artificial intelligence in industry 4.0. Future research trends on sustainable design, trust in AI, and emerging technology integration towards the next-generation AI in industrial design are discussed.