{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T15:57:10Z","timestamp":1726847830242},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2010,12,28]],"date-time":"2010-12-28T00:00:00Z","timestamp":1293494400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Intell Manuf"],"published-print":{"date-parts":[[2012,10]]},"DOI":"10.1007\/s10845-010-0498-9","type":"journal-article","created":{"date-parts":[[2010,12,27]],"date-time":"2010-12-27T07:05:46Z","timestamp":1293433546000},"page":"1833-1847","source":"Crossref","is-referenced-by-count":26,"title":["A robust approach for root causes identification in machining processes using hybrid learning algorithm and engineering knowledge"],"prefix":"10.1007","volume":"23","author":[{"given":"Shichang","family":"Du","sequence":"first","affiliation":[]},{"given":"Jun","family":"Lv","sequence":"additional","affiliation":[]},{"given":"Lifeng","family":"Xi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2010,12,28]]},"reference":[{"key":"498_CR1","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1023\/B:JIMS.0000037713.74607.00","volume":"15","author":"M. Bargash","year":"2004","unstructured":"Bargash M., Santarisi N. (2004) Pattern recognition of control charts using artificial neural networks-analyzing the effect of the training parameters. Journal of Intelligent Manufacturing 15: 635\u2013644","journal-title":"Journal of Intelligent Manufacturing"},{"key":"498_CR2","first-page":"123","volume":"24","author":"L. Breiman","year":"1996","unstructured":"Breiman L. (1996) Bagging predictors. Machine Learning 24: 123\u2013140","journal-title":"Machine Learning"},{"issue":"4","key":"498_CR3","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1115\/1.2902133","volume":"116","author":"D. Ceglarek","year":"1994","unstructured":"Ceglarek D., Shi J., Wu S. M. (1994) A knowledge-based diagnosis approach for the launch of the auto-body assembly process. ASME Transactions. Journal of Engineering for Industry 116(4): 491\u2013499","journal-title":"ASME Transactions. Journal of Engineering for Industry"},{"issue":"4","key":"498_CR4","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/S0360-8352(01)00031-6","volume":"40","author":"C. S. Cheng","year":"2001","unstructured":"Cheng C. S., Cheng S. S. (2001) A neural network-based procedure for the monitoring of exponential mean. Computers & Industrial Engineering 40(4): 309\u2013321","journal-title":"Computers & Industrial Engineering"},{"key":"498_CR5","doi-asserted-by":"crossref","first-page":"966","DOI":"10.1007\/s00170-007-1030-z","volume":"37","author":"N. Das","year":"2008","unstructured":"Das N., Prakash V. (2008) Interpreting the out-of-control signal in multivariate control chart\u2014a comparative study. International Journal of Advanced Manufacturing Technology 37: 966\u2013979","journal-title":"International Journal of Advanced Manufacturing Technology"},{"issue":"2\u20133","key":"498_CR6","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.compind.2007.06.023","volume":"59","author":"S. Du","year":"2008","unstructured":"Du S., Xi L., Ni J., Pan E., Liu R. (2008) Product lifecycle-oriented quality and productivity improvement based on stream of variation methodology. Computers in Industry 59(2\u20133): 180\u2013192","journal-title":"Computers in Industry"},{"key":"498_CR7","unstructured":"Eberhart, C. R., & Kennedy. J. (1995). Particle swarm optimization. In Proceedings IEEE international conference on neural networks (pp. 1942\u20131948). Piscataway, NJ."},{"key":"498_CR8","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s10845-008-0230-1","volume":"20","author":"\u0130. Ertu\u011frul","year":"2009","unstructured":"Ertu\u011frul \u0130., Ayta\u00e7 E. (2009) Construction of quality control charts by using probability and fuzzy approaches and an application in a textile company. Journal of Intelligent Manufacturing 20: 139\u2013149","journal-title":"Journal of Intelligent Manufacturing"},{"key":"498_CR9","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1002\/qre.796","volume":"23","author":"R. S. Guh","year":"2007","unstructured":"Guh R. S. (2007) On-line identification and quantification of mean shifts in bivariate processes using a neural network-based approach. Quality and Reliability Engineering International 23: 367\u2013385","journal-title":"Quality and Reliability Engineering International"},{"key":"498_CR10","doi-asserted-by":"crossref","unstructured":"Gutta, S., & Wechsler, H. (1996). Face recognition using hybrid classifier systems. In: Proceedings of the ICNN-96 (pp. 1017\u20131022). Washington, DC: IEEE Computer Society Press, Los Alamitos, CA.","DOI":"10.1109\/ICNN.1996.549037"},{"key":"498_CR11","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1109\/34.58871","volume":"12","author":"L. K. Hansen","year":"1990","unstructured":"Hansen L. K., Salamon P. (1990) Neural network ensembles. IEEE Transactions on Pattern Analysis and Machine Intelligence 12: 993\u20131001","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"7","key":"498_CR12","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1080\/0020754021000049844","volume":"41","author":"A. Hassan","year":"2003","unstructured":"Hassan A., Shariff N. B. M., Shaharoun A. M., Jamaluddin H. (2003) Improved SPC chart pattern recognition using statistical features. International Journal of Production Research 41(7): 1587\u20131603","journal-title":"International Journal of Production Research"},{"issue":"3","key":"498_CR13","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s10845-008-0083-7","volume":"19","author":"Y. Huang","year":"2008","unstructured":"Huang Y., McMurran R., Dhadyalla G., Jones R. P. (2008) Probability based vehicle fault diagnosis: Bayesian network method. Journal of Intelligent Manufacturing 19(3): 301\u2013311","journal-title":"Journal of Intelligent Manufacturing"},{"key":"498_CR14","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1007\/s10845-008-0152-y","volume":"20","author":"P. Y. Jiang","year":"2009","unstructured":"Jiang P. Y., Liu D. Y., Zeng Z. J. (2009) Recognizing control chart patterns with neural network and numerical fitting. Journal of Intelligent Manufacturing 20: 625\u2013635","journal-title":"Journal of Intelligent Manufacturing"},{"key":"498_CR15","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/S0924-0136(02)00691-X","volume":"129","author":"J. Lian","year":"2002","unstructured":"Lian J., Lai X., Lin Z., Yao F. S. (2002) Application of data mining and process knowledge discovery in sheet metal assembly dimensional variation diagnosis. Journal of Materials Processing Technology 129: 315\u2013320","journal-title":"Journal of Materials Processing Technology"},{"key":"498_CR16","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1115\/1.1852572","volume":"127","author":"G. Liu","year":"2005","unstructured":"Liu G., Hu S. J. (2005) Assembly fixture diagnosis using designated component analysis. Journal of Manufacturing Science and Engineering 127: 358\u2013368","journal-title":"Journal of Manufacturing Science and Engineering"},{"key":"498_CR17","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/S0925-2312(02)00623-9","volume":"51","author":"W. Z. Lu","year":"2003","unstructured":"Lu W. Z., Fan H. Y., Lo S. M. (2003) Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong. Neurocomputing 51: 387\u2013400","journal-title":"Neurocomputing"},{"key":"498_CR18","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1007\/s00521-004-0413-4","volume":"13","author":"I. Maqsood","year":"2004","unstructured":"Maqsood I., Khan M. R., Abraham A. (2004) An ensemble of neural networks for weather forecasting. Neural Computing and Application 13: 112\u2013122","journal-title":"Neural Computing and Application"},{"key":"498_CR19","volume-title":"Generalized, linear, and mixed models","author":"C. McCulloch","year":"2001","unstructured":"McCulloch C., Searle S. R. (2001) Generalized, linear, and mixed models. Wiley, New York, NY"},{"key":"498_CR20","volume-title":"Introduction to statistical quality control","author":"D. C. Montgomery","year":"2005","unstructured":"Montgomery D. C. (2005) Introduction to statistical quality control. Wiley, New York, NY","edition":"5"},{"key":"498_CR21","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1007\/s00170-005-0007-z","volume":"29","author":"V. Pandey","year":"2006","unstructured":"Pandey V., Tiwari M. K., Kumar S. (2006) An interactive approach to solve the operation sequencing problem using simulated annealing. International Journal of Advanced Manufacturing Technology 29: 1212\u20131231","journal-title":"International Journal of Advanced Manufacturing Technology"},{"key":"498_CR22","first-page":"126","volume-title":"Artificial neural networks for speed and vision","author":"M. P Perrone","year":"1993","unstructured":"Perrone M. P, Cooper L. (1993) When networks disagree: Ensemble method for neural networks. In: Mammone R. J. (eds) Artificial neural networks for speed and vision. Chapman & Hill, New York, pp 126\u2013142"},{"key":"498_CR23","first-page":"197","volume":"5","author":"R. E. Schapire","year":"1990","unstructured":"Schapire R. E. (1990) The strength of weak learnability. Machine Learning 5: 197\u2013227","journal-title":"Machine Learning"},{"issue":"1","key":"498_CR24","first-page":"33","volume":"46","author":"M. Shanker","year":"1996","unstructured":"Shanker M., Hu M. (1996) Cutoff values for two-group classification using neural networks. Industrial Mathematics 46(1): 33\u201345","journal-title":"Industrial Mathematics"},{"key":"498_CR25","first-page":"9,744","volume":"41","author":"J. Shi","year":"2009","unstructured":"Shi J., Zhou S. (2009) Quality control and improvement for multistage systems: A survey. IIE Transactions 41: 9,744\u20139,753","journal-title":"IIE Transactions"},{"key":"498_CR26","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/00207549408956935","volume":"32","author":"A. E. Smith","year":"1994","unstructured":"Smith A. E. (1994) X-Bar and R control chart interpretation using neural computing. International Journal of Production Research 32: 309\u2013320","journal-title":"International Journal of Production Research"},{"issue":"3","key":"498_CR27","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1023\/A:1015738906895","volume":"13","author":"T. Y. Wang","year":"2002","unstructured":"Wang T. Y., Chen L. H. (2002) Mean shifts detection and classification in multivariate process: A neural-fuzzy approach. Journal of Intelligent Manufacturing 13(3): 211\u2013221","journal-title":"Journal of Intelligent Manufacturing"},{"key":"498_CR28","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1023\/B:JIMS.0000037718.43289.62","volume":"15","author":"C. H. Yen","year":"2004","unstructured":"Yen C. H., Wong D. S. H., Jang S. S. (2004) Solution of trim-loss problem by an integrated simulated annealing and ordinal optimization approach. Journal of Intelligent Manufacturing 15: 701\u2013709","journal-title":"Journal of Intelligent Manufacturing"},{"key":"498_CR29","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/S0004-3702(02)00190-X","volume":"137","author":"Z. H. Zhou","year":"2002","unstructured":"Zhou Z. H., Wu J. X., Tang W. (2002) Ensembling neural networks: Many could be better than all. Artificial Intelligence 137: 239\u2013263","journal-title":"Artificial Intelligence"},{"issue":"1","key":"498_CR30","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1109\/TASE.2004.829427","volume":"1","author":"S. Zhou","year":"2004","unstructured":"Zhou S., Chen Y., Shi J. (2004) Root cause estimation and statistical testing for quality improvement of multistage manufacturing processes. IEEE Transactions on Automation Science and Engineering 1(1): 73\u201383","journal-title":"IEEE Transactions on Automation Science and Engineering"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-010-0498-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10845-010-0498-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-010-0498-9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T02:11:50Z","timestamp":1559268710000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10845-010-0498-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,12,28]]},"references-count":30,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2012,10]]}},"alternative-id":["498"],"URL":"https:\/\/doi.org\/10.1007\/s10845-010-0498-9","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"value":"0956-5515","type":"print"},{"value":"1572-8145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,12,28]]}}}