TY - JOUR
T1 - Artificial intelligence in industrial design: A semi-automated literature survey
AU - Tsang, Y. P.
AU - Lee, C. K.M.
N1 - Funding Information:
The authors would like to thank the Department of Industrial and Systems Engineering, Hong Kong , The Hong Kong Polytechnic University for supporting the research. This research is funded by the Laboratory for Artificial Intelligence in Design, Hong Kong (Project Code: RP2-2), Hong Kong Special Administrative Region, Hong Kong . Special thanks go to Miss W.W. Chong and Miss Y.S. Au for their assistance provided in this research.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/6
Y1 - 2022/6
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Industrial design
KW - Industry 4.0
KW - Review
KW - Text analytics
UR - http://www.scopus.com/inward/record.url?scp=85129247369&partnerID=8YFLogxK
U2 - 10.1016/j.engappai.2022.104884
DO - 10.1016/j.engappai.2022.104884
M3 - Short survey
AN - SCOPUS:85129247369
SN - 0952-1976
VL - 112
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
M1 - 104884
ER -
