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Furthermore, when considering AM for an inventory of existing components traditionally fabricated through traditional means, such a guarantee could result in significant technical and economic advantages. To realize such advantages, this paper presents a platform that allows for a successful and efficient transition of part-inventories to AM. This is accomplished using a novel design recommender system supported by machine learning, capable of making suggestions towards effective design modifications. This system uses an automatic AM feasibility analysis of existing parts and a clustering of the parts based on similarities in their AM-feasibilities to develop a set of recommendations for those part clusters whose current designs are deemed as infeasible and\/or inefficient for AM. The design modifications leverage a redesign algorithm to address not only problematic geometric issues but also potential infeasibilities associated with resource consumption. The utility of the presented modification algorithm is demonstrated using a number of case studies.<\/jats:p>","DOI":"10.1115\/1.4051342","type":"journal-article","created":{"date-parts":[[2021,6,2]],"date-time":"2021-06-02T08:36:01Z","timestamp":1622622961000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":5,"title":["A Recommender System for the Additive Manufacturing of Component Inventories Using Machine Learning"],"prefix":"10.1115","volume":"22","author":[{"given":"Seyedeh","family":"Elaheh Ghiasian","sequence":"first","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, University at Buffalo, Buffalo, NY 14260"}]},{"given":"Kemper","family":"Lewis","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, University at Buffalo, Buffalo, NY 14260"}]}],"member":"33","published-online":{"date-parts":[[2021,7,13]]},"reference":[{"key":"2021071309445366000_CIT0001","doi-asserted-by":"crossref","DOI":"10.1115\/DETC2019-97840","article-title":"A Design Modification System for Additive Manufacturing: Towards Feasible Geometry Development","author":"Ghiasian","year":"2019"},{"key":"2021071309445366000_CIT0002","doi-asserted-by":"crossref","DOI":"10.1115\/DETC2018-85996","article-title":"Self-Improving Additive Manufacturing Knowledge Management","author":"Lu","year":"2018"},{"issue":"1","key":"2021071309445366000_CIT0003","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.cirpj.2013.10.001","article-title":"Design for Additive Manufacturing\u2014Element Transitions and Aggregated Structures","volume":"7","author":"Adam","year":"2014","journal-title":"CIRP J. 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