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This paper presents a focused literature review of AI-based methods mapped to the different stages of the engineering design process and describes how these methods assist the design process. We surveyed 108 AI-based engineering design papers from peer-reviewed journals and conference proceedings and mapped their contribution to five stages of the engineering design process. We categorized seven AI-based methods in our dataset. Our literature study indicated that most AI-based design research works are targeted at the conceptual and preliminary design stages. Given the open-ended, ambiguous nature of these early stages, these results are unexpected. We conjecture that this is likely a result of several factors, including the iterative nature of design tasks in these stages, the availability of open design data repositories, and the inclination to use AI for processing computationally intensive tasks, like those in these stages. Our study also indicated that these methods support designers by synthesizing and\/or analyzing design data, concepts, and models in the design stages. This literature review aims to provide readers with an informative mapping of different AI tools to engineering design stages and to potentially motivate engineers, design researchers, and students to understand the current state-of-the-art and identify opportunities for applying AI applications in engineering design.<\/jats:p>","DOI":"10.1017\/s0890060423000203","type":"journal-article","created":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T07:41:48Z","timestamp":1702366908000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":17,"title":["Mapping artificial intelligence-based methods to engineering design stages: a focused literature review"],"prefix":"10.1017","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9798-0348","authenticated-orcid":false,"given":"Pranav Milind","family":"Khanolkar","sequence":"first","affiliation":[]},{"given":"Ademir","family":"Vrolijk","sequence":"additional","affiliation":[]},{"given":"Alison","family":"Olechowski","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2023,12,12]]},"reference":[{"key":"S0890060423000203_ref58","doi-asserted-by":"crossref","first-page":"121101","DOI":"10.1115\/1.4044399","article-title":"Mining and representing the concept space of existing ideas for directed ideation","volume":"141","author":"He","year":"2019","journal-title":"Journal of Mechanical Design, Transactions of the ASME"},{"key":"S0890060423000203_ref53","doi-asserted-by":"publisher","DOI":"10.1115\/1.4036780"},{"key":"S0890060423000203_ref14","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jprocont.2020.03.014","article-title":"Modular design optimization using machine learning-based flexibility analysis","volume":"90","author":"Bhosekar","year":"2020","journal-title":"Journal of Process Control"},{"key":"S0890060423000203_ref50","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/S0954-1810(01)00017-6","article-title":"Conceptual modeling from natural language functional specifications","volume":"15","author":"Gangopadhyay","year":"2001","journal-title":"Artificial Intelligence in Engineering"},{"key":"S0890060423000203_ref18","doi-asserted-by":"publisher","DOI":"10.1115\/1.4045126"},{"key":"S0890060423000203_ref89","doi-asserted-by":"crossref","unstructured":"Lin, K and Kim, HM (2021) Investigate the influence of online ratings and reviews in purchase behavior using customer choice sets. 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