{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:47:35Z","timestamp":1777704455173,"version":"3.51.4"},"reference-count":18,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2018,8,6]],"date-time":"2018-08-06T00:00:00Z","timestamp":1533513600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2018,10,27]]},"abstract":"<jats:p>Typical process is a sample process which can reflect processes of a group of similar parts. As a kind of process knowledge it can be referred to for the process planning of new parts. In this paper a methodology of typical process discovery for body-in-white (BIW) parts, based on the distance (i.e. dissimilarity) between processes, is proposed. The process for BIW part is divided into assembly positioning, joining, and quality inspection operations, in accordance with the typical assembly; the assembly oriented typical process is extracted based on these three operations. The distances of assembly positioning, joining, and quality inspection are calculated respectively using different measuring methods. The distance between processes is calculated as the sum of the assembly positioning, joining, and quality inspection distances. Furthermore, the clustering algorithm is applied to form the process clusters according to the distances between processes. The mean variances of the distance between processes in the cluster are calculated. The process with the minimum mean variance in the cluster is selected as the typical process. Finally, a case study is used to show the procedure of the typical processes acquisition for BIW and validate the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3233\/jifs-18232","type":"journal-article","created":{"date-parts":[[2018,8,10]],"date-time":"2018-08-10T10:48:29Z","timestamp":1533898109000},"page":"4745-4755","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Typical process acquisition for body-in-white parts based on cluster algorithm"],"prefix":"10.1177","volume":"35","author":[{"given":"Yongsheng","family":"Chao","sequence":"first","affiliation":[{"name":"College of Mechanical Engineering, Xinjiang University, Urumqi, China"}]},{"given":"Wenlei","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Xinjiang University, Urumqi, China"}]}],"member":"179","published-online":{"date-parts":[[2018,8,6]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"257","article-title":"ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference","author":"Lee B.","year":"2003","unstructured":"LeeB., SaitouK., Assembly synthesis with subassembly partitioning for optimal in-process dimensional adjustability, ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2003, 257\u2013268.","journal-title":"Assembly synthesis with subassembly partitioning for optimal in-process dimensional adjustability"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1080\/07408170304376"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-010-2910-1"},{"issue":"4","key":"e_1_3_2_5_2","first-page":"491","article-title":"A knowledge-based diagnostic approach for the launch of the auto-body assembly process","volume":"116","author":"Ceglarek D.","year":"1994","unstructured":"CeglarekD., ShiJ. and WuS., A knowledge-based diagnostic approach for the launch of the auto-body assembly process, Journal of Manufacturing Science and Engineering 116(4) (1994), 491\u2013499.","journal-title":"Journal of Manufacturing Science and Engineering"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0007-8506(07)62776-0"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219686711001965"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-004-2105-8"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cad.2006.01.012"},{"key":"e_1_3_2_10_2","first-page":"325","volume-title":"Process Navigator for Automotive Body Assembly Process","author":"Shi J.","year":"1994","unstructured":"ShiJ., HuS.J., CeglarekD., Process Navigator for Automotive Body Assembly Process, Proceedings of the First S.M.Wu Symposium on Manufacturing Science, (1994), 325\u2013332."},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-007-5860-5_139"},{"issue":"5","key":"e_1_3_2_12_2","first-page":"1034","article-title":"Automatic Generation of Dimension Chains for Auto-Body Dimensional Quality Evaluation","volume":"17","author":"Zhou J.","year":"2005","unstructured":"ZhouJ., ChenG., LaiX. and LinZ., Automatic Generation of Dimension Chains for Auto-Body Dimensional Quality Evaluation, Journal of Computer Aided Design & Computer Graphics 17(5) (2005), 1034\u20131038.","journal-title":"Journal of Computer Aided Design & Computer Graphics"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-006-0554-y"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-007-0961-8"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.5121\/ijdkp.2011.1503"},{"key":"e_1_3_2_16_2","first-page":"165","article-title":"CIRP Conference on Assembly Technologies and Systems","author":"Papakostas N.","year":"2014","unstructured":"PapakostasN., PintzosG., MatsasM. and ChryssolourisG., CIRP Conference on Assembly Technologies and Systems, Knowledge-enabled Design of Cooperating Robots Assembly Cells (2014), 165\u2013170.","journal-title":"Knowledge-enabled Design of Cooperating Robots Assembly Cells"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0890-6955(95)00090-9"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1080\/17517570902741653"},{"key":"e_1_3_2_19_2","volume-title":"Data mining","author":"Ming Z.","year":"2002","unstructured":"MingZ., Data mining, Press of University of Science and Technology of China, 2002."}],"container-title":["Journal of Intelligent &amp; 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