{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T04:51:37Z","timestamp":1777956697907,"version":"3.51.4"},"reference-count":56,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100008536","name":"Lanzhou University of Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008536","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72561018"],"award-info":[{"award-number":["72561018"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72231008"],"award-info":[{"award-number":["72231008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72561019"],"award-info":[{"award-number":["72561019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004775","name":"Gansu Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["20JR5RA432"],"award-info":[{"award-number":["20JR5RA432"]}],"id":[{"id":"10.13039\/501100004775","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Industrial Engineering"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.cie.2026.112015","type":"journal-article","created":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T23:52:17Z","timestamp":1775260337000},"page":"112015","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A Data-Driven nonparametric control chart for multivariate serially correlated data monitoring in advanced industrial scenarios"],"prefix":"10.1016","volume":"216","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6556-4195","authenticated-orcid":false,"given":"Cang","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5391-0808","authenticated-orcid":false,"given":"Dong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9022-9954","authenticated-orcid":false,"given":"Yongjun","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenpo","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lijun","family":"Shang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2297-4423","authenticated-orcid":false,"given":"Shubin","family":"Si","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0005","doi-asserted-by":"crossref","first-page":"2091","DOI":"10.32604\/cmes.2023.022201","article-title":"Ranked-Set Sampling based distribution Free Control Chart with Application in CSTR Process","volume":"135","author":"Almanjahie","year":"2023","journal-title":"Computer Modeling in Engineering & Sciences"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0010","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-023-46719-3","article-title":"Support vector data description with kernel density estimation (SVDD-KDE) control chart for network intrusion monitoring","volume":"13","author":"Ahsan","year":"2024","journal-title":"Scientific Reports"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0015","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1080\/00224065.2002.11980131","article-title":"The autoregressive T2 chart for monitoring univariate autocorrelated processes","volume":"34","author":"Apley","year":"2002","journal-title":"Journal of Quality Technology"},{"key":"10.1016\/j.cie.2026.112015_b0020","doi-asserted-by":"crossref","unstructured":"Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). John Wiley & Sons. Doi:10.1111\/jtsa.12194.","DOI":"10.1111\/jtsa.12194"},{"issue":"11","key":"10.1016\/j.cie.2026.112015_b0025","doi-asserted-by":"crossref","first-page":"5406","DOI":"10.1080\/03610918.2023.2185932","article-title":"A control chart based on data depth for monitoring the variability in a multivariate process","volume":"53","author":"Barale","year":"2023","journal-title":"Communications in Statistics-Simulation and Computation"},{"key":"10.1016\/j.cie.2026.112015_b0030","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Machine Learning"},{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0035","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1198\/004017008000000280","article-title":"Practical design of generalized likelihood ratio control charts for autocorrelated data","volume":"50","author":"Capizzi","year":"2008","journal-title":"Technometrics"},{"issue":"7","key":"10.1016\/j.cie.2026.112015_b0040","doi-asserted-by":"crossref","first-page":"4068","DOI":"10.1002\/qre.3619","article-title":"Distribution-free multivariate process monitoring: A rank-energy statistic-based approach","volume":"40","author":"Chakraborty","year":"2024","journal-title":"Quality and Reliability Engineering International"},{"issue":"4","key":"10.1016\/j.cie.2026.112015_b0045","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1080\/00401706.2015.1049750","article-title":"A distribution-free multivariate control chart","volume":"58","author":"Chen","year":"2016","journal-title":"Technometrics"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0050","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1080\/10485252.2024.2365212","article-title":"A phase-II change-point-based distribution-free scheme for monitoring of three process aspects","volume":"37","author":"Chen","year":"2024","journal-title":"Journal of Nonparametric Statistics"},{"key":"10.1016\/j.cie.2026.112015_b0055","doi-asserted-by":"crossref","unstructured":"Desa, N.H.M., & Jemain, A.A. (2013). Eliminating the Influence of Serial Correlation on Statistical Process Control Charts Using Trend Free Pre-Whitening (TFPW) Method. Universiti-Kebangsaan-Malaysia, Faculty-of-Science-and-Technology Postgraduate Colloquium, 1571, 1049-1054. Doi:10.1063\/1.4858792.","DOI":"10.1063\/1.4858792"},{"issue":"2","key":"10.1016\/j.cie.2026.112015_b0060","doi-asserted-by":"crossref","DOI":"10.1002\/cem.70004","article-title":"Nonparametric Threshold Estimation of Autocorrelated Statistics in Multivariate Statistical Process monitoring","volume":"39","author":"Grimm","year":"2025","journal-title":"Journal of Chemometrics"},{"key":"10.1016\/j.cie.2026.112015_b0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118260","article-title":"Real-time change-point detection: A deep neural network-based adaptive approach for detecting changes in multivariate time series data","volume":"209","author":"Gupta","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.cie.2026.112015_b0070","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/0024-3795(88)90223-6","article-title":"Computing a nearest symmetric positive semidefinite matrix","volume":"103","author":"Higham","year":"1988","journal-title":"Linear Algebra and its Applications"},{"issue":"4","key":"10.1016\/j.cie.2026.112015_b0075","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1080\/08982112.2024.2311253","article-title":"A distribution-free phase II control chart for multivariate individual data with simple post signal diagnostics","volume":"36","author":"Holcombe","year":"2024","journal-title":"Quality Engineering"},{"key":"10.1016\/j.cie.2026.112015_b0080","series-title":"Multivariate Quality Control-illustrated by the air testing of sample bombsights. Techniques of Statistical Analysis","first-page":"111","author":"Hotelling","year":"1947"},{"issue":"6","key":"10.1016\/j.cie.2026.112015_b0085","doi-asserted-by":"crossref","first-page":"1716","DOI":"10.1002\/qre.2471","article-title":"A spatial rank-based multivariate EWMA chart for monitoring process shape matrices","volume":"35","author":"Huwang","year":"2019","journal-title":"Quality and Reliability Engineering International"},{"issue":"8","key":"10.1016\/j.cie.2026.112015_b0090","doi-asserted-by":"crossref","first-page":"4365","DOI":"10.1002\/qre.3635","article-title":"Surveillance of high-yield processes using deep learning models","volume":"40","author":"Ibrahim","year":"2024","journal-title":"Quality and Reliability Engineering International"},{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0095","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1080\/16843703.2021.2015834","article-title":"Online monitoring of autocorrelated multivariate linear profiles via multivariate mixed models","volume":"19","author":"Khalili","year":"2022","journal-title":"Quality Technology & Quantitative Management"},{"key":"10.1016\/j.cie.2026.112015_b0100","article-title":"Cost-effective dynamic sampling in high dimensional online monitoring with advantage actor-critic","author":"Li","year":"2025","journal-title":"International Journal of Production Research"},{"issue":"2","key":"10.1016\/j.cie.2026.112015_b0105","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1002\/qre.2427","article-title":"A wavelet-based nonparametric CUSUM control chart for autocorrelated processes with applications to network surveillance","volume":"35","author":"Li","year":"2019","journal-title":"Quality and Reliability Engineering International"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0110","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1080\/24725854.2018.1557794","article-title":"A general charting scheme for monitoring serially correlated data with short-memory dependence and nonparametric distributions","volume":"52","author":"Li","year":"2020","journal-title":"IISE Transactions"},{"key":"10.1016\/j.cie.2026.112015_b0115","article-title":"An image-based nonparametric multivariate EWMA control chart for metal additive manufacturing process monitoring","volume":"242","author":"Liu","year":"2025","journal-title":"Measurement"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0120","first-page":"46","article-title":"A Multivariate Exponentially Weighted moving Average Control Chart","volume":"34","author":"Lowry","year":"1992","journal-title":"Technometrics"},{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0125","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1080\/00207543.2023.2173508","article-title":"An efficient adaptive r-MD multivariate single control chart for nonlinear multiple quality characteristics","volume":"62","author":"Maji","year":"2024","journal-title":"International Journal of Production Research"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0130","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1080\/00401706.2023.2239886","article-title":"Statistical Process monitoring of Artificial Neural Networks","volume":"66","author":"Malinovskaya","year":"2024","journal-title":"Technometrics"},{"key":"10.1016\/j.cie.2026.112015_b0135","doi-asserted-by":"crossref","unstructured":"May, G., & Spanos, C. (2006). Fundamentals of Semiconductor Manufacturing and Process Control. Hoboken, NJ: Wiley. Doi:10.1002\/0471790281.","DOI":"10.1002\/0471790281"},{"issue":"8","key":"10.1016\/j.cie.2026.112015_b0140","doi-asserted-by":"crossref","first-page":"3044","DOI":"10.1016\/j.eswa.2012.12.020","article-title":"Principal component analysis-based control charts for multivariate nonnormal distributions","volume":"40","author":"Phaladiganon","year":"2013","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.cie.2026.112015_b0145","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.measurement.2016.01.004","article-title":"Adaptive sliding kalman filter using nonparametric change point detection","volume":"82","author":"Poddar","year":"2016","journal-title":"Measurement"},{"issue":"7","key":"10.1016\/j.cie.2026.112015_b0150","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1080\/07408170701744843","article-title":"Distribution-free multivariate process control based on log-linear modeling","volume":"40","author":"Qiu","year":"2008","journal-title":"IIE Transactions"},{"key":"10.1016\/j.cie.2026.112015_b0155","doi-asserted-by":"crossref","unstructured":"Qiu, P. (2014). Introduction to statistical process control. Boca Raton, FL: Chapman Hall\/CRC. Doi:10.1201\/b15016.","DOI":"10.1201\/b15016"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0160","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1080\/00401706.2018.1562988","article-title":"A new process control chart for monitoring short-range serially correlated data","volume":"62","author":"Qiu","year":"2020","journal-title":"Technometrics"},{"issue":"4","key":"10.1016\/j.cie.2026.112015_b0165","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1080\/00401706.2021.1929493","article-title":"Transparent sequential learning for statistical process control of serially correlated data","volume":"64","author":"Qiu","year":"2022","journal-title":"Technometrics"},{"key":"10.1016\/j.cie.2026.112015_b0170","doi-asserted-by":"crossref","DOI":"10.1155\/2021\/2570198","article-title":"An Efficient Robust Nonparametric Triple EWMA Wilcoxon Signed-Rank Control Chart for Process Location","volume":"2021","author":"Rasheed","year":"2021","journal-title":"Mathematical Problems in Engineering"},{"issue":"2","key":"10.1016\/j.cie.2026.112015_b0175","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1080\/16843703.2022.2075193","article-title":"Monitoring the multivariate coefficient of variation in presence of autocorrelation with variable parameters control charts","volume":"20","author":"Sabahno","year":"2023","journal-title":"Quality Technology & Quantitative Management"},{"key":"10.1016\/j.cie.2026.112015_b0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.jwpe.2024.106126","article-title":"Artificial Neural Networks and Multivariate Statistical Process Control to improve ammonia removal on membrane bioreactors treating refinery wastewater","volume":"67","author":"Santos","year":"2024","journal-title":"Journal of Water Process Engineering"},{"key":"10.1016\/j.cie.2026.112015_b0185","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2023.109469","article-title":"Two robust multivariate exponentially weighted moving average charts to facilitate distinctive product quality features assessment","volume":"183","author":"Song","year":"2023","journal-title":"Computers & Industrial Engineering"},{"issue":"5","key":"10.1016\/j.cie.2026.112015_b0190","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1080\/16843703.2023.2244213","article-title":"An EWMA chart for high dimensional process with multi-class out-of-control information via random forest learning","volume":"21","author":"Sun","year":"2024","journal-title":"Quality Technology and Quantitative Management"},{"issue":"5","key":"10.1016\/j.cie.2026.112015_bib276","doi-asserted-by":"crossref","first-page":"1985","DOI":"10.1002\/qre.3755","article-title":"Modified EWMA Chart With Restarting Mechanism for Monitoring Serially Correlated Sequential Processes","volume":"41","author":"Tian","year":"2025","journal-title":"Quality and Reliability Engineering International"},{"issue":"4","key":"10.1016\/j.cie.2026.112015_b0195","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1002\/qre.3278","article-title":"Multivariate auto\u2010correlated process control by a residual\u2010based mixed CUSUM\u2010EWMA model","volume":"39","author":"Wang","year":"2023","journal-title":"Quality and Reliability Engineering International"},{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0200","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1080\/16843703.2024.2356970","article-title":"Monitoring of high-dimensional and high-frequency data streams: A nonparametric approach","volume":"22","author":"Wang","year":"2025","journal-title":"Quality Technology & Quantitative Management"},{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0205","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1080\/00401706.1985.10488053","article-title":"Multivariate CUSUM Quality-Control Procedures","volume":"27","author":"Woodall","year":"1985","journal-title":"Technometrics"},{"key":"10.1016\/j.cie.2026.112015_b0210","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2025.111111","article-title":"Nonparametric monitoring of high-dimensional processes via EWMA control charts based on random forest learning","volume":"204","author":"Wu","year":"2025","journal-title":"Computers & Industrial Engineering"},{"key":"10.1016\/j.cie.2026.112015_b0215","article-title":"Identifying different types of urban land use dynamics using Point-of-interest (POI) and Random Forest algorithm: The case of Huizhou","volume":"114","author":"Wu","year":"2021","journal-title":"China. Cities"},{"issue":"6","key":"10.1016\/j.cie.2026.112015_b0220","doi-asserted-by":"crossref","first-page":"2279","DOI":"10.1002\/qre.3786","article-title":"Adaptive LASSO-Based Robust Multivariate Process monitoring and Diagnostics","volume":"41","author":"Xie","year":"2025","journal-title":"Quality and Reliability Engineering International"},{"key":"10.1016\/j.cie.2026.112015_b0225","series-title":"Control Charts and Machine Learning for Anomaly Detection in Manufacturing","first-page":"131","article-title":"Machine learning control charts for monitoring serially correlated data","author":"Xie","year":"2022"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0230","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1214\/22-AOAS1615","article-title":"Control charts for dynamic process monitoring with an application to air pollution surveillance","volume":"17","author":"Xie","year":"2023","journal-title":"The Annals of Applied Statistics"},{"issue":"1","key":"10.1016\/j.cie.2026.112015_b0235","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1080\/00401706.2023.2224411","article-title":"A general framework for robust monitoring of multivariate correlated processes","volume":"66","author":"Xie","year":"2024","journal-title":"Technometrics"},{"issue":"8","key":"10.1016\/j.cie.2026.112015_b0240","doi-asserted-by":"crossref","first-page":"4196","DOI":"10.1002\/qre.3199","article-title":"Robust monitoring of multivariate processes with short-ranged serial data correlation","volume":"38","author":"Xie","year":"2022","journal-title":"Quality and Reliability Engineering International"},{"issue":"4","key":"10.1016\/j.cie.2026.112015_b0245","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1080\/00224065.2020.1778430","article-title":"A nonparametric CUSUM chart for monitoring multivariate serially correlated processes","volume":"53","author":"Xue","year":"2021","journal-title":"Journal of Quality Technology"},{"key":"10.1016\/j.cie.2026.112015_b0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2024.109930","article-title":"A nonparametric adaptive EWMA control chart for monitoring mixed continuous and categorical data using self-starting strategy","volume":"188","author":"Xue","year":"2024","journal-title":"Computers & Industrial Engineering"},{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0255","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.1109\/TASE.2022.3146391","article-title":"A generic online nonparametric monitoring and sampling strategy for high-dimensional heterogeneous processes","volume":"19","author":"Ye","year":"2022","journal-title":"Ieee Transactions on Automation Science and Engineering"},{"issue":"3","key":"10.1016\/j.cie.2026.112015_b0260","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1080\/00207543.2023.2172474","article-title":"Online monitoring of high-dimensional asynchronous and heterogeneous data streams for shifts in location and scale","volume":"62","author":"Ye","year":"2024","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.cie.2026.112015_b0265","doi-asserted-by":"crossref","first-page":"4873","DOI":"10.1007\/s00500-023-09047-2","article-title":"Evolutionary support vector regression for monitoring Poisson profiles","volume":"28","author":"Yeganeh","year":"2024","journal-title":"Soft Computing"},{"key":"10.1016\/j.cie.2026.112015_b0270","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2024.110725","article-title":"Monitoring bivariate autocorrelated process using a deep learning-based control chart: A case study on the car manufacturing industry","volume":"199","author":"Yeganeh","year":"2025","journal-title":"Computers & Industrial Engineering"},{"key":"10.1016\/j.cie.2026.112015_b0275","article-title":"A Distribution-Free THWMA Control Chart under Ranked Set Sampling","volume":"2022","author":"Zhang","year":"2022","journal-title":"Mathematical Problems in Engineering"}],"container-title":["Computers & Industrial Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835226002160?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835226002160?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T03:34:46Z","timestamp":1777952086000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0360835226002160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":56,"alternative-id":["S0360835226002160"],"URL":"https:\/\/doi.org\/10.1016\/j.cie.2026.112015","relation":{},"ISSN":["0360-8352"],"issn-type":[{"value":"0360-8352","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A Data-Driven nonparametric control chart for multivariate serially correlated data monitoring in advanced industrial scenarios","name":"articletitle","label":"Article Title"},{"value":"Computers & Industrial Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cie.2026.112015","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"112015"}}