A modified variables repetitive group sampling plan with the consideration of preceding lots information
Various acceptance sampling plans have been developed for different objectives. A repetitive group sampling (RGS) plan has been shown to be an efficient and easy-to-implement scheme for lot sentencing. However, it does not consider the available information from preceding samples. As a result, it ma...
Gespeichert in:
| Veröffentlicht in: | Annals of operations research 2016-03, Vol.238 (1-2), p.355-373 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 373 |
|---|---|
| container_issue | 1-2 |
| container_start_page | 355 |
| container_title | Annals of operations research |
| container_volume | 238 |
| creator | Lee, Amy H. I. Wu, Chien-Wei Chen, Yen-Wen |
| description | Various acceptance sampling plans have been developed for different objectives. A repetitive group sampling (RGS) plan has been shown to be an efficient and easy-to-implement scheme for lot sentencing. However, it does not consider the available information from preceding samples. As a result, it may reduce the sampling efficiency in terms of cost and time. In this study, a modified variables RGS plan is proposed based on the commonly used capability index
C
p
k
for normally distributed processes with two-sided specification limits and to consider the sample results from preceding lots. The plan parameters for various required quality levels and allowable risks are tabulated for practical applications, and the advantages of the proposed plan is compared with existing variables sampling plans in terms of operating characteristic curve and average sample size. |
| doi_str_mv | 10.1007/s10479-015-2064-5 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1800496215</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A444240516</galeid><sourcerecordid>A444240516</sourcerecordid><originalsourceid>FETCH-LOGICAL-c523t-6e72c7c05f02d4f925a30e53d2d2073e08fe3c9dc6456ed460e97fab6a1d9f083</originalsourceid><addsrcrecordid>eNp1kkuLFTEQhRtR8Dr6A9wF3Liwx8qrH8th8AUDbnQdcpNK3wzdnTbVPeK_N-0VnBElkEDlO0Wd4lTVSw6XHKB9SxxU29fAdS2gUbV-VB24bkXdS9k9rg4gdClKCU-rZ0S3AMB5pw_V6YpNyccQ0bM7m6M9jkgs44JrXOMdsiGnbWFkp2WM88CW0c7se1xPbD0hc2mm6DHbNaaZpcCWjA79Do5pJRbnkPL06_d59STYkfDF7_ei-vr-3Zfrj_XN5w-frq9uaqeFXOsGW-FaBzqA8Cr0QlsJqKUXXkArEbqA0vXeNUo36FUD2LfBHhvLfR-gkxfV63PfJadvG9JqpkgOxzI3po0M7wBU3wiuC_rqL_Q2bXku0xnetpxDp0H8oQY7otkdrdm6vam5UkoJBZo3hbr8B1WOxymWNWGIpf5A8Oae4LhRnJHKRXE4rTTYjeghzs-4y4koYzBLjpPNPwwHsyfAnBNgSgLMngCz-xNnDRV2HjDf8_df0U-P17J7</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1771108502</pqid></control><display><type>article</type><title>A modified variables repetitive group sampling plan with the consideration of preceding lots information</title><source>EBSCOhost Business Source Complete</source><source>Springer Nature - Complete Springer Journals</source><creator>Lee, Amy H. I. ; Wu, Chien-Wei ; Chen, Yen-Wen</creator><creatorcontrib>Lee, Amy H. I. ; Wu, Chien-Wei ; Chen, Yen-Wen</creatorcontrib><description>Various acceptance sampling plans have been developed for different objectives. A repetitive group sampling (RGS) plan has been shown to be an efficient and easy-to-implement scheme for lot sentencing. However, it does not consider the available information from preceding samples. As a result, it may reduce the sampling efficiency in terms of cost and time. In this study, a modified variables RGS plan is proposed based on the commonly used capability index
C
p
k
for normally distributed processes with two-sided specification limits and to consider the sample results from preceding lots. The plan parameters for various required quality levels and allowable risks are tabulated for practical applications, and the advantages of the proposed plan is compared with existing variables sampling plans in terms of operating characteristic curve and average sample size.</description><identifier>ISSN: 0254-5330</identifier><identifier>EISSN: 1572-9338</identifier><identifier>DOI: 10.1007/s10479-015-2064-5</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Acceptance ; Business and Management ; Combinatorics ; Cost engineering ; Decision making ; Mathematical research ; Normal distribution ; Operations research ; Operations Research/Decision Theory ; Purchasing contracts ; Risk ; Sample size ; Sampling ; Specifications ; Standard deviation ; Statistical sampling ; Studies ; Texts ; Theory of Computation ; Variables (Mathematics)</subject><ispartof>Annals of operations research, 2016-03, Vol.238 (1-2), p.355-373</ispartof><rights>Springer Science+Business Media New York 2015</rights><rights>COPYRIGHT 2016 Springer</rights><rights>Springer Science+Business Media New York 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c523t-6e72c7c05f02d4f925a30e53d2d2073e08fe3c9dc6456ed460e97fab6a1d9f083</citedby><cites>FETCH-LOGICAL-c523t-6e72c7c05f02d4f925a30e53d2d2073e08fe3c9dc6456ed460e97fab6a1d9f083</cites><orcidid>0000-0001-7965-1997</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10479-015-2064-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10479-015-2064-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Lee, Amy H. I.</creatorcontrib><creatorcontrib>Wu, Chien-Wei</creatorcontrib><creatorcontrib>Chen, Yen-Wen</creatorcontrib><title>A modified variables repetitive group sampling plan with the consideration of preceding lots information</title><title>Annals of operations research</title><addtitle>Ann Oper Res</addtitle><description>Various acceptance sampling plans have been developed for different objectives. A repetitive group sampling (RGS) plan has been shown to be an efficient and easy-to-implement scheme for lot sentencing. However, it does not consider the available information from preceding samples. As a result, it may reduce the sampling efficiency in terms of cost and time. In this study, a modified variables RGS plan is proposed based on the commonly used capability index
C
p
k
for normally distributed processes with two-sided specification limits and to consider the sample results from preceding lots. The plan parameters for various required quality levels and allowable risks are tabulated for practical applications, and the advantages of the proposed plan is compared with existing variables sampling plans in terms of operating characteristic curve and average sample size.</description><subject>Acceptance</subject><subject>Business and Management</subject><subject>Combinatorics</subject><subject>Cost engineering</subject><subject>Decision making</subject><subject>Mathematical research</subject><subject>Normal distribution</subject><subject>Operations research</subject><subject>Operations Research/Decision Theory</subject><subject>Purchasing contracts</subject><subject>Risk</subject><subject>Sample size</subject><subject>Sampling</subject><subject>Specifications</subject><subject>Standard deviation</subject><subject>Statistical sampling</subject><subject>Studies</subject><subject>Texts</subject><subject>Theory of Computation</subject><subject>Variables (Mathematics)</subject><issn>0254-5330</issn><issn>1572-9338</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kkuLFTEQhRtR8Dr6A9wF3Liwx8qrH8th8AUDbnQdcpNK3wzdnTbVPeK_N-0VnBElkEDlO0Wd4lTVSw6XHKB9SxxU29fAdS2gUbV-VB24bkXdS9k9rg4gdClKCU-rZ0S3AMB5pw_V6YpNyccQ0bM7m6M9jkgs44JrXOMdsiGnbWFkp2WM88CW0c7se1xPbD0hc2mm6DHbNaaZpcCWjA79Do5pJRbnkPL06_d59STYkfDF7_ei-vr-3Zfrj_XN5w-frq9uaqeFXOsGW-FaBzqA8Cr0QlsJqKUXXkArEbqA0vXeNUo36FUD2LfBHhvLfR-gkxfV63PfJadvG9JqpkgOxzI3po0M7wBU3wiuC_rqL_Q2bXku0xnetpxDp0H8oQY7otkdrdm6vam5UkoJBZo3hbr8B1WOxymWNWGIpf5A8Oae4LhRnJHKRXE4rTTYjeghzs-4y4koYzBLjpPNPwwHsyfAnBNgSgLMngCz-xNnDRV2HjDf8_df0U-P17J7</recordid><startdate>20160301</startdate><enddate>20160301</enddate><creator>Lee, Amy H. I.</creator><creator>Wu, Chien-Wei</creator><creator>Chen, Yen-Wen</creator><general>Springer US</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>N95</scope><scope>3V.</scope><scope>7TA</scope><scope>7TB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>KR7</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M0N</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0001-7965-1997</orcidid></search><sort><creationdate>20160301</creationdate><title>A modified variables repetitive group sampling plan with the consideration of preceding lots information</title><author>Lee, Amy H. I. ; Wu, Chien-Wei ; Chen, Yen-Wen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c523t-6e72c7c05f02d4f925a30e53d2d2073e08fe3c9dc6456ed460e97fab6a1d9f083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Acceptance</topic><topic>Business and Management</topic><topic>Combinatorics</topic><topic>Cost engineering</topic><topic>Decision making</topic><topic>Mathematical research</topic><topic>Normal distribution</topic><topic>Operations research</topic><topic>Operations Research/Decision Theory</topic><topic>Purchasing contracts</topic><topic>Risk</topic><topic>Sample size</topic><topic>Sampling</topic><topic>Specifications</topic><topic>Standard deviation</topic><topic>Statistical sampling</topic><topic>Studies</topic><topic>Texts</topic><topic>Theory of Computation</topic><topic>Variables (Mathematics)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Amy H. I.</creatorcontrib><creatorcontrib>Wu, Chien-Wei</creatorcontrib><creatorcontrib>Chen, Yen-Wen</creatorcontrib><collection>CrossRef</collection><collection>Gale Business: Insights</collection><collection>ProQuest Central (Corporate)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Science Database (ProQuest)</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Annals of operations research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Amy H. I.</au><au>Wu, Chien-Wei</au><au>Chen, Yen-Wen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A modified variables repetitive group sampling plan with the consideration of preceding lots information</atitle><jtitle>Annals of operations research</jtitle><stitle>Ann Oper Res</stitle><date>2016-03-01</date><risdate>2016</risdate><volume>238</volume><issue>1-2</issue><spage>355</spage><epage>373</epage><pages>355-373</pages><issn>0254-5330</issn><eissn>1572-9338</eissn><abstract>Various acceptance sampling plans have been developed for different objectives. A repetitive group sampling (RGS) plan has been shown to be an efficient and easy-to-implement scheme for lot sentencing. However, it does not consider the available information from preceding samples. As a result, it may reduce the sampling efficiency in terms of cost and time. In this study, a modified variables RGS plan is proposed based on the commonly used capability index
C
p
k
for normally distributed processes with two-sided specification limits and to consider the sample results from preceding lots. The plan parameters for various required quality levels and allowable risks are tabulated for practical applications, and the advantages of the proposed plan is compared with existing variables sampling plans in terms of operating characteristic curve and average sample size.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10479-015-2064-5</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0001-7965-1997</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0254-5330 |
| ispartof | Annals of operations research, 2016-03, Vol.238 (1-2), p.355-373 |
| issn | 0254-5330 1572-9338 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1800496215 |
| source | EBSCOhost Business Source Complete; Springer Nature - Complete Springer Journals |
| subjects | Acceptance Business and Management Combinatorics Cost engineering Decision making Mathematical research Normal distribution Operations research Operations Research/Decision Theory Purchasing contracts Risk Sample size Sampling Specifications Standard deviation Statistical sampling Studies Texts Theory of Computation Variables (Mathematics) |
| title | A modified variables repetitive group sampling plan with the consideration of preceding lots information |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-24T04%3A26%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20modified%20variables%20repetitive%20group%20sampling%20plan%20with%20the%20consideration%20of%20preceding%20lots%20information&rft.jtitle=Annals%20of%20operations%20research&rft.au=Lee,%20Amy%20H.%20I.&rft.date=2016-03-01&rft.volume=238&rft.issue=1-2&rft.spage=355&rft.epage=373&rft.pages=355-373&rft.issn=0254-5330&rft.eissn=1572-9338&rft_id=info:doi/10.1007/s10479-015-2064-5&rft_dat=%3Cgale_proqu%3EA444240516%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1771108502&rft_id=info:pmid/&rft_galeid=A444240516&rfr_iscdi=true |