{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T10:33:36Z","timestamp":1753180416456},"reference-count":25,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2007,1,22]],"date-time":"2007-01-22T00:00:00Z","timestamp":1169424000000},"content-version":"unspecified","delay-in-days":21,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIEDAM"],"published-print":{"date-parts":[[2007,1]]},"abstract":"<jats:p>Achieving the dimensional integrity for a complex structural assembly \nis a demanding task due to the manufacturing variations of parts and the \ntolerance relationship between them. Although assigning tight tolerances \nto all parts would solve the problem, an economical solution is taking \nadvantage of small motions that joints allow, such that critical \ndimensions are adjusted <jats:italic>during<\/jats:italic> assembly processes. This paper \npresents a systematic method that decomposes product geometry at an early \nstage of design, selects joint types, and generates subassembly \npartitioning to achieve the adjustment of the critical dimensions during \nassembly processes. A genetic algorithm generates candidate assemblies \nbased on a joint library specific for an application domain. Each \ncandidate assembly is evaluated by an internal optimization routine that \ncomputes the subassembly partitioning for optimal in-process \nadjustability, by finding a series of minimum cuts on weighted graphs. A \ncase study on a three-dimensional automotive space frame with the \naccompanying joint library is presented.<\/jats:p>","DOI":"10.1017\/s0890060407070126","type":"journal-article","created":{"date-parts":[[2007,1,22]],"date-time":"2007-01-22T23:24:27Z","timestamp":1169508267000},"page":"31-43","source":"Crossref","is-referenced-by-count":7,"title":["Assembly synthesis with subassembly partitioning for optimal \nin-process dimensional adjustability"],"prefix":"10.1017","volume":"21","author":[{"given":"BYUNGWOO","family":"LEE","sequence":"first","affiliation":[]},{"given":"KAZUHIRO","family":"SAITOU","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2007,1,22]]},"reference":[{"key":"S0890060407070126_ref014","doi-asserted-by":"crossref","unstructured":"Liu, S.C. , & Hu, S.J. 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