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Towards cognitive intelligence-enabled product design: The evolution, state-of-the-art, and future of AI-enabled product design

  • Zuoxu Wang
  • , Xinxin Liang
  • , Mingrui Li
  • , Shufei Li*
  • , Jihong Liu
  • , Lianyu Zheng
  • *Corresponding author for this work
  • MIIT Key Laboratory of Aeronautics Intelligent Manufacturing
  • Beijing Key Laboratory of Digital Media
  • Beihang University
  • Hong Kong Polytechnic University

Research output: Contribution to journalReview articlepeer-review

Abstract

Engineering design researchers have increasing interests in leveraging artificial intelligence (AI) techniques to a wide range of product design tasks, such as customer requirement analysis, product concept generation, design synthesis, and decision-making in product design. Indeed, AI techniques perform excellently on well-defined design tasks with clear problem definition, specialized solutions, and abundant training data. However, facing the ever-evolving AI techniques rapidly and radically changing the product design manner, there is still a lack of a systematic summary about the current stage of AI-enabled product design. Besides, although the current AI-enabled product design performs excellently on the well-defined tasks, the other advanced design tasks that need cognitive capability can still hardly be satisfyingly completed by the current product design system. This study systematically reviewed the literature on AI-enabled product design to understand its evolution and state-of-the-arts. To bridge the semantic gap between humans and systems, a novel cognitive intelligence-enabled product design (CIPD) framework is proposed, in which cognitive intelligence is the key enabler. The CIPD's key aspects, including its system architecture, human-like capabilities, enabling technologies, and potential applications, are also systematically discussed. It is hoped that this study could contribute to the future directions of the product design field and offer insightful guidance to the practitioners and researchers in their product design process.

Original languageEnglish
Article number100759
JournalJournal of Industrial Information Integration
Volume43
DOIs
StatePublished - Jan 2025

Keywords

  • Cognitive computing
  • Design knowledge support
  • Engineering product design
  • Industrial products and services design
  • Knowledge graph
  • Knowledge reasoning

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