{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T21:31:09Z","timestamp":1766179869927},"reference-count":28,"publisher":"ASME International","issue":"4","content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2004,12,1]]},"abstract":"<jats:p>In variant design, the proliferation of bills of materials makes it difficult for designers to find previous designs that would aid in completing a new design task. This research presents a novel, data mining approach to forming generic bills of materials (GBOMs), entities that represent the different variants in a product family and facilitate the search for similar designs and configuration of new variants. The technical difficulties include: (i) developing families or categories for products, assemblies, and component parts; (ii) generalizing purchased parts and quantifying their similarity; (iii) performing tree union; and (iv) establishing design constraints. These challenges are met through data mining methods such as text and tree mining, a new tree union procedure, and embodying the GBOM and design constraints in constrained XML. The paper concludes with a case study, using data from a manufacturer of nurse call devices, and identifies a new research direction for data mining motivated by the domains of engineering design and information.<\/jats:p>","DOI":"10.1115\/1.1812556","type":"journal-article","created":{"date-parts":[[2005,1,4]],"date-time":"2005-01-04T23:00:41Z","timestamp":1104879641000},"page":"316-328","update-policy":"http:\/\/dx.doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":44,"title":["A Data Mining Approach to Forming Generic Bills of Materials in Support of Variant Design Activities"],"prefix":"10.1115","volume":"4","author":[{"given":"Carol J.","family":"Romanowski ,","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, 342 Bell Hall, University at Buffalo, SUNY Buffalo, New York 14260"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rakesh","family":"Nagi","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, 342 Bell Hall, University at Buffalo, SUNY Buffalo, New York 14260"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"33","published-online":{"date-parts":[[2005,1,4]]},"reference":[{"key":"2019100409120657900_r1","doi-asserted-by":"crossref","unstructured":"Prebil, I., Zupan, S., and Lu, P., 1995, \u201cAdaptive and Variant Design of Rotational Connections,\u201d Eng. Comput., 11, pp. 83\u201393.","DOI":"10.1007\/BF01312202"},{"key":"2019100409120657900_r2","unstructured":"Opitz, H., 1970, A Classification System to Describe Workpieces (translated by A. Taylor), Pergamon Press, New York."},{"key":"2019100409120657900_r3","doi-asserted-by":"crossref","unstructured":"Hegge, H. M. H., and Wortmann, J. C., 1991, \u201cGeneric Bill-Of-Material: A New Product Model,\u201d International Journal of Production Economics, 23, pp. 117\u2013128.","DOI":"10.1016\/0925-5273(91)90055-X"},{"key":"2019100409120657900_r4","doi-asserted-by":"crossref","unstructured":"Farrell, R., and Simpson, T., 2003, \u201cProduct Platform Design to Improve Commonality in Custom Products,\u201d Journal of Intelligent Manufacturing, 14(6), pp. 541\u2013556.","DOI":"10.1023\/A:1027306704980"},{"key":"2019100409120657900_r5","doi-asserted-by":"crossref","unstructured":"Simpson, T., Umapathy, K., Nanda, J., Halbe, S., and Hodge, B., 2003, \u201cDevelopment of a Framework for Web-Based Product Platform Customization,\u201d ASME J. Comput. Inf. Sci. Eng., 3, pp. 119\u2013129.","DOI":"10.1115\/1.1582881"},{"key":"2019100409120657900_r6","unstructured":"Koenig, D. T., 1994, Manufacturing Engineering: Principles for Optimization, Taylor & Francis, Washington, D.C."},{"key":"2019100409120657900_r7","unstructured":"McKernan, T. J., and Jayaraman, B., 2000, \u201cCobWeb: A Constraint-Based XML for the Web,\u201d Department of Computer Science, University at Buffalo."},{"key":"2019100409120657900_r8","unstructured":"Ham, I., Marion, D., and Rubinovich, J., 1986, \u201cDeveloping a Group Technology Coding and Classification Scheme,\u201d Industrial Engineering, 18(7), pp. 90\u201397."},{"key":"2019100409120657900_r9","doi-asserted-by":"crossref","unstructured":"Henderson, M., and Musti, S., 1988, \u201cAutomated Group Technology Part Coding From a Three-Dimensional CAD Database,\u201d ASME J. Eng. Ind., 110(3), pp. 278\u2013287.","DOI":"10.1115\/1.3187882"},{"key":"2019100409120657900_r10","unstructured":"Harhalakis, G., Kinsey, A., and Minis, I., 1992, \u201cAutomated Group Technology Code Generation Using PDES,\u201d in Proc. 3rd Int. Conf. Computer Integrated Manufacturing, Rensselaer Polytechnic Institute, Troy NY."},{"key":"2019100409120657900_r11","unstructured":"Ham, I., Hitomi, K., and Yoshida, T., 1985, Group Technology: Applications to Production Management (International Series in Management Science\/Operations Research, 9), Kluwer Academic Publishers, Dordrecht."},{"key":"2019100409120657900_r12","unstructured":"Shah, J., and Bhatnagar, A., 1989, \u201cGroup Technology Classification From Feature-Based Geometric Models,\u201d Manufacturing Review, 2(3), pp. 204\u2013213."},{"key":"2019100409120657900_r13","doi-asserted-by":"crossref","unstructured":"Kao, Y., and Moon, Y. B., 1991, \u201cUnified Group Technology Implementation Using the Backpropagation Learning Rule of Neural Networks,\u201d Computers & Industrial Engineering, 20(4), pp. 425\u2013437.","DOI":"10.1016\/0360-8352(91)90015-X"},{"key":"2019100409120657900_r14","doi-asserted-by":"crossref","unstructured":"Iyer, S., and Nagi, R., 1997, \u201cAutomated Retrieval and Ranking of Similar Parts in Agile Manufacturing,\u201d IIE Transactions, Design and Manufacturing, special issue on Agile Manufacturing, 29(10), pp. 859\u2013876.","DOI":"10.1080\/07408179708966407"},{"key":"2019100409120657900_r15","doi-asserted-by":"crossref","unstructured":"Lee-Post, A.\n          , 2000, \u201cPart Family Identification Using a Simple Genetic Algorithm,\u201d Int. J. Prod. Res., 38(4), pp. 793\u2013810.","DOI":"10.1080\/002075400189158"},{"key":"2019100409120657900_r16","unstructured":"Jiao, J., and Tseng, M. M., 1999, \u201cMethodology of Developing Product Family Architecture for Mass Customization,\u201d Journal of Intelligent Manufacturing, 10(1), pp. 3\u201320."},{"key":"2019100409120657900_r17","doi-asserted-by":"crossref","unstructured":"Jiao, J., Tseng, M. M., Ma, Q., and Zou, Y., 2000, \u201cGeneric Bill-Of-Materials-and-Operations for High-Variety Production Management,\u201d Concurrent Engineering-Research & Applications, 8(4), pp. 297\u2013321.","DOI":"10.1106\/95P6-GB09-YHG6-H5QG"},{"key":"2019100409120657900_r18","unstructured":"Ramabhatta, V., Lin, L., and Nagi, R., 1997, \u201cObject Hierarchies to aid Representation and Variant Design of Complex Assemblies in an Agile Environment,\u201d International Journal of Agile Manufacturing, 1(1), pp. 77\u201390."},{"key":"2019100409120657900_r19","doi-asserted-by":"crossref","unstructured":"Cook, D. J., and Holder, L. B., 2000, \u201cGraph-Based Data Mining,\u201d IEEE Intell. Syst., 15(2), pp. 32\u201341.","DOI":"10.1109\/5254.850825"},{"key":"2019100409120657900_r20","doi-asserted-by":"crossref","unstructured":"Romanowski, C. J., and Nagi, R., 2004, \u201cOn Comparing Bills Of Materials: A Similarity\/Distance Measure for Unordered Trees,\u201d accepted by IEEE Trans. Sys. Man Cybern., Part A (to appear May 2005).","DOI":"10.1109\/TSMCA.2005.843395"},{"key":"2019100409120657900_r21","unstructured":"Ng, R., and Han, J., 1994, \u201cEfficient and Effective Clustering Methods for Spatial Data Mining,\u201d Proc. of 20th International Conference on Very Large DataBases, pp. 144\u2013155, Santiago de Chile, Chile."},{"key":"2019100409120657900_r22","unstructured":"Romanowski, C. J., and Nagi, R., 2004, \u201cAdaptive Data Mining in a Variant Design Support System,\u201d in Proc. of the 13th Industrial Engineering Research Conference, Houston TX."},{"key":"2019100409120657900_r23","unstructured":"Orlicky, J., 1975, Material Requirements Planning, McGraw-Hill Book Company, New York."},{"key":"2019100409120657900_r24","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Imielinski, T., and Swam\u0131\u00b4, A., 1993, \u201cMining Association Rules Between Sets of Items in Large Databases,\u201d SIGMOD Record (ACM Special Interest Group on Management of Data), 22(2), pp. 207\u2013216.","DOI":"10.1145\/170036.170072"},{"key":"2019100409120657900_r25","unstructured":"Liu, B., Hsu, W., and Ma, Y., 1998, \u201cIntegrating Classification and Association Rule Mining,\u201d Proc. of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98, Plenary Presentation), New York, USA."},{"key":"2019100409120657900_r26","doi-asserted-by":"crossref","unstructured":"Zaki, M. J.\n          , 2000, \u201cScalable Algorithms for Association Mining,\u201d IEEE Transactions on Knowledge & Data Engineering, 12(3), pp. 372\u2013390.","DOI":"10.1109\/69.846291"},{"key":"2019100409120657900_r27","doi-asserted-by":"crossref","unstructured":"Romanowski, C. J., and Nagi, R., 2001, \u201cA Data Mining-Based Engineering Design Support System: A Research Agenda,\u201d in Data Mining for Design and Manufacturing: Methods and Applications, D. Braha, ed., Kluwer Academic Publishers, The Netherlands, pp. 235\u2013254.","DOI":"10.1007\/978-1-4757-4911-3_7"},{"key":"2019100409120657900_r28","unstructured":"Romanowski, C. J., Nagi, R., and Sudit, M., 2003, \u201cData Mining in an Engineering Design Environment: OR Applications From Graph Matching,\u201d submitted to Computers and Operations Research, special issue on Data Mining."}],"container-title":["Journal of Computing and Information Science in Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/asmedigitalcollection.asme.org\/computingengineering\/article-pdf\/4\/4\/316\/5773590\/316_1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/asmedigitalcollection.asme.org\/computingengineering\/article-pdf\/4\/4\/316\/5773590\/316_1.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,4]],"date-time":"2019-10-04T13:12:25Z","timestamp":1570194745000},"score":1,"resource":{"primary":{"URL":"https:\/\/asmedigitalcollection.asme.org\/computingengineering\/article\/4\/4\/316\/462855\/A-Data-Mining-Approach-to-Forming-Generic-Bills-of"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004,12,1]]},"references-count":28,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2004,12,1]]}},"URL":"https:\/\/doi.org\/10.1115\/1.1812556","relation":{},"ISSN":["1530-9827","1944-7078"],"issn-type":[{"value":"1530-9827","type":"print"},{"value":"1944-7078","type":"electronic"}],"subject":[],"published":{"date-parts":[[2004,12,1]]}}}