A high-dimensional control chart for profile monitoring
Profile monitoring is an important and rapidly emerging area of statistical process control. In many industries, the quality of processes or products can be characterized by a profile that describes a relationship or a function between a response variable and one or more independent variables. A cha...
Gespeichert in:
| Veröffentlicht in: | Quality and reliability engineering international 2011-06, Vol.27 (4), p.451-464 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 464 |
|---|---|
| container_issue | 4 |
| container_start_page | 451 |
| container_title | Quality and reliability engineering international |
| container_volume | 27 |
| creator | Chen, Shuohui Nembhard, Harriet Black |
| description | Profile monitoring is an important and rapidly emerging area of statistical process control. In many industries, the quality of processes or products can be characterized by a profile that describes a relationship or a function between a response variable and one or more independent variables. A change in the profile relationship can indicate a change in the quality characteristic of the process or product and, therefore, needs to be monitored for control purposes. We propose a high‐dimensional (HD) control chart approach for profile monitoring that is based on the adaptive Neyman test statistic for the coefficients of discrete Fourier transform of profiles. We investigate both linear and nonlinear profiles, and we study the robustness of the HD control chart for monitoring profiles with stationary noise. We apply our control chart to monitor the process of nonlinear woodboard vertical density profile data of Walker and Wright (J. Qual. Technol. 2002; 34:118–129) and compare the results with those presented in Williams et al. (Qual. Reliab. Eng. Int. 2007; to appear). Copyright © 2010 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/qre.1140 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1031286874</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1031286874</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3360-2b94b5353a33799517fa08f0aec69f2552608eb60f5412dd44f2ef06472038ca3</originalsourceid><addsrcrecordid>eNp10EtLAzEUBeAgCtYq-BNm6WbqTTJ5LUupVSy-8AFuQjpN2uh00iZTtP_eKRXFhauz-bicexA6xdDDAOR8FW0P4wL2UAeDUjnmVO6jDohC5hKwOERHKb0BtFjJDhL9bO5n83zqF7ZOPtSmyspQNzG0OTexyVyI2TIG5yubLULtmxB9PTtGB85UyZ58Zxc9XQwfB5f5-HZ0NeiP85JSDjmZqGLCKKOGUqEUw8IZkA6MLblyhDHCQdoJB8cKTKbTonDEOuCFIEBlaWgXne3uthVWa5savfCptFVlahvWSWOgmEguRfFLyxhSitbpZfQLEzct0tttdLuN3m7T0nxHP9qvNv86ff8w_Ot9auznjzfxXXNBBdMvNyP9zF6VJPJa39EvoQNynw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1031286874</pqid></control><display><type>article</type><title>A high-dimensional control chart for profile monitoring</title><source>Wiley Online Library All Journals</source><creator>Chen, Shuohui ; Nembhard, Harriet Black</creator><creatorcontrib>Chen, Shuohui ; Nembhard, Harriet Black</creatorcontrib><description>Profile monitoring is an important and rapidly emerging area of statistical process control. In many industries, the quality of processes or products can be characterized by a profile that describes a relationship or a function between a response variable and one or more independent variables. A change in the profile relationship can indicate a change in the quality characteristic of the process or product and, therefore, needs to be monitored for control purposes. We propose a high‐dimensional (HD) control chart approach for profile monitoring that is based on the adaptive Neyman test statistic for the coefficients of discrete Fourier transform of profiles. We investigate both linear and nonlinear profiles, and we study the robustness of the HD control chart for monitoring profiles with stationary noise. We apply our control chart to monitor the process of nonlinear woodboard vertical density profile data of Walker and Wright (J. Qual. Technol. 2002; 34:118–129) and compare the results with those presented in Williams et al. (Qual. Reliab. Eng. Int. 2007; to appear). Copyright © 2010 John Wiley & Sons, Ltd.</description><identifier>ISSN: 0748-8017</identifier><identifier>ISSN: 1099-1638</identifier><identifier>EISSN: 1099-1638</identifier><identifier>DOI: 10.1002/qre.1140</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>Adaptive control systems ; adaptive Neyman test statistic ; autoregressive models ; Control charts ; Density ; discrete Fourier transform ; INT ; Monitoring ; multivariate statistical process control ; Nonlinearity ; profile data ; Robustness ; Statistics ; time series models</subject><ispartof>Quality and reliability engineering international, 2011-06, Vol.27 (4), p.451-464</ispartof><rights>Copyright © 2010 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3360-2b94b5353a33799517fa08f0aec69f2552608eb60f5412dd44f2ef06472038ca3</citedby><cites>FETCH-LOGICAL-c3360-2b94b5353a33799517fa08f0aec69f2552608eb60f5412dd44f2ef06472038ca3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fqre.1140$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fqre.1140$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,27923,27924,45573,45574</link.rule.ids></links><search><creatorcontrib>Chen, Shuohui</creatorcontrib><creatorcontrib>Nembhard, Harriet Black</creatorcontrib><title>A high-dimensional control chart for profile monitoring</title><title>Quality and reliability engineering international</title><addtitle>Qual. Reliab. Engng. Int</addtitle><description>Profile monitoring is an important and rapidly emerging area of statistical process control. In many industries, the quality of processes or products can be characterized by a profile that describes a relationship or a function between a response variable and one or more independent variables. A change in the profile relationship can indicate a change in the quality characteristic of the process or product and, therefore, needs to be monitored for control purposes. We propose a high‐dimensional (HD) control chart approach for profile monitoring that is based on the adaptive Neyman test statistic for the coefficients of discrete Fourier transform of profiles. We investigate both linear and nonlinear profiles, and we study the robustness of the HD control chart for monitoring profiles with stationary noise. We apply our control chart to monitor the process of nonlinear woodboard vertical density profile data of Walker and Wright (J. Qual. Technol. 2002; 34:118–129) and compare the results with those presented in Williams et al. (Qual. Reliab. Eng. Int. 2007; to appear). Copyright © 2010 John Wiley & Sons, Ltd.</description><subject>Adaptive control systems</subject><subject>adaptive Neyman test statistic</subject><subject>autoregressive models</subject><subject>Control charts</subject><subject>Density</subject><subject>discrete Fourier transform</subject><subject>INT</subject><subject>Monitoring</subject><subject>multivariate statistical process control</subject><subject>Nonlinearity</subject><subject>profile data</subject><subject>Robustness</subject><subject>Statistics</subject><subject>time series models</subject><issn>0748-8017</issn><issn>1099-1638</issn><issn>1099-1638</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNp10EtLAzEUBeAgCtYq-BNm6WbqTTJ5LUupVSy-8AFuQjpN2uh00iZTtP_eKRXFhauz-bicexA6xdDDAOR8FW0P4wL2UAeDUjnmVO6jDohC5hKwOERHKb0BtFjJDhL9bO5n83zqF7ZOPtSmyspQNzG0OTexyVyI2TIG5yubLULtmxB9PTtGB85UyZ58Zxc9XQwfB5f5-HZ0NeiP85JSDjmZqGLCKKOGUqEUw8IZkA6MLblyhDHCQdoJB8cKTKbTonDEOuCFIEBlaWgXne3uthVWa5savfCptFVlahvWSWOgmEguRfFLyxhSitbpZfQLEzct0tttdLuN3m7T0nxHP9qvNv86ff8w_Ot9auznjzfxXXNBBdMvNyP9zF6VJPJa39EvoQNynw</recordid><startdate>201106</startdate><enddate>201106</enddate><creator>Chen, Shuohui</creator><creator>Nembhard, Harriet Black</creator><general>John Wiley & Sons, Ltd</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope></search><sort><creationdate>201106</creationdate><title>A high-dimensional control chart for profile monitoring</title><author>Chen, Shuohui ; Nembhard, Harriet Black</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3360-2b94b5353a33799517fa08f0aec69f2552608eb60f5412dd44f2ef06472038ca3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Adaptive control systems</topic><topic>adaptive Neyman test statistic</topic><topic>autoregressive models</topic><topic>Control charts</topic><topic>Density</topic><topic>discrete Fourier transform</topic><topic>INT</topic><topic>Monitoring</topic><topic>multivariate statistical process control</topic><topic>Nonlinearity</topic><topic>profile data</topic><topic>Robustness</topic><topic>Statistics</topic><topic>time series models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Shuohui</creatorcontrib><creatorcontrib>Nembhard, Harriet Black</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><jtitle>Quality and reliability engineering international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Shuohui</au><au>Nembhard, Harriet Black</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A high-dimensional control chart for profile monitoring</atitle><jtitle>Quality and reliability engineering international</jtitle><addtitle>Qual. Reliab. Engng. Int</addtitle><date>2011-06</date><risdate>2011</risdate><volume>27</volume><issue>4</issue><spage>451</spage><epage>464</epage><pages>451-464</pages><issn>0748-8017</issn><issn>1099-1638</issn><eissn>1099-1638</eissn><abstract>Profile monitoring is an important and rapidly emerging area of statistical process control. In many industries, the quality of processes or products can be characterized by a profile that describes a relationship or a function between a response variable and one or more independent variables. A change in the profile relationship can indicate a change in the quality characteristic of the process or product and, therefore, needs to be monitored for control purposes. We propose a high‐dimensional (HD) control chart approach for profile monitoring that is based on the adaptive Neyman test statistic for the coefficients of discrete Fourier transform of profiles. We investigate both linear and nonlinear profiles, and we study the robustness of the HD control chart for monitoring profiles with stationary noise. We apply our control chart to monitor the process of nonlinear woodboard vertical density profile data of Walker and Wright (J. Qual. Technol. 2002; 34:118–129) and compare the results with those presented in Williams et al. (Qual. Reliab. Eng. Int. 2007; to appear). Copyright © 2010 John Wiley & Sons, Ltd.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/qre.1140</doi><tpages>14</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0748-8017 |
| ispartof | Quality and reliability engineering international, 2011-06, Vol.27 (4), p.451-464 |
| issn | 0748-8017 1099-1638 1099-1638 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1031286874 |
| source | Wiley Online Library All Journals |
| subjects | Adaptive control systems adaptive Neyman test statistic autoregressive models Control charts Density discrete Fourier transform INT Monitoring multivariate statistical process control Nonlinearity profile data Robustness Statistics time series models |
| title | A high-dimensional control chart for profile monitoring |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-13T00%3A16%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20high-dimensional%20control%20chart%20for%20profile%20monitoring&rft.jtitle=Quality%20and%20reliability%20engineering%20international&rft.au=Chen,%20Shuohui&rft.date=2011-06&rft.volume=27&rft.issue=4&rft.spage=451&rft.epage=464&rft.pages=451-464&rft.issn=0748-8017&rft.eissn=1099-1638&rft_id=info:doi/10.1002/qre.1140&rft_dat=%3Cproquest_cross%3E1031286874%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1031286874&rft_id=info:pmid/&rfr_iscdi=true |