New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information
The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating th...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Haq, Abdul [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2017 |
|---|
| Rechteinformationen: |
Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd. |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Quality and reliability engineering international - Chichester [u.a.] : Wiley, 1985, 33(2017), 7, Seite 1549-1565 |
|---|---|
| Übergeordnetes Werk: |
volume:33 ; year:2017 ; number:7 ; pages:1549-1565 |
| Links: |
|---|
| DOI / URN: |
10.1002/qre.2124 |
|---|
| Katalog-ID: |
OLC1997840472 |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | OLC1997840472 | ||
| 003 | DE-627 | ||
| 005 | 20220217093018.0 | ||
| 007 | tu | ||
| 008 | 171125s2017 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1002/qre.2124 |2 doi | |
| 028 | 5 | 2 | |a PQ20171228 |
| 035 | |a (DE-627)OLC1997840472 | ||
| 035 | |a (DE-599)GBVOLC1997840472 | ||
| 035 | |a (PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653 | ||
| 035 | |a (KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 650 |a 690 |q DNB |
| 084 | |a 50.16 |2 bkl | ||
| 084 | |a 85.38 |2 bkl | ||
| 100 | 1 | |a Haq, Abdul |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information |
| 264 | 1 | |c 2017 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 520 | |a The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. | ||
| 540 | |a Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd. | ||
| 650 | 4 | |a control chart | |
| 650 | 4 | |a synthetic chart | |
| 650 | 4 | |a statistical process control | |
| 650 | 4 | |a conforming run length | |
| 650 | 4 | |a average run length | |
| 650 | 4 | |a CUSUM | |
| 650 | 4 | |a auxiliary information | |
| 650 | 4 | |a EWMA | |
| 650 | 4 | |a Process controls | |
| 650 | 4 | |a Control charts | |
| 650 | 4 | |a Computer simulation | |
| 650 | 4 | |a Process parameters | |
| 650 | 4 | |a Monitoring | |
| 650 | 4 | |a Charts | |
| 650 | 4 | |a Optimal control | |
| 773 | 0 | 8 | |i Enthalten in |t Quality and reliability engineering international |d Chichester [u.a.] : Wiley, 1985 |g 33(2017), 7, Seite 1549-1565 |w (DE-627)129167614 |w (DE-600)50641-2 |w (DE-576)028403312 |x 0748-8017 |7 nnns |
| 773 | 1 | 8 | |g volume:33 |g year:2017 |g number:7 |g pages:1549-1565 |
| 856 | 4 | 1 | |u http://dx.doi.org/10.1002/qre.2124 |3 Volltext |
| 856 | 4 | 2 | |u http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract |
| 856 | 4 | 2 | |u https://search.proquest.com/docview/1955921429 |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-UMW | ||
| 912 | |a SSG-OLC-ARC | ||
| 912 | |a SSG-OLC-TEC | ||
| 912 | |a SSG-OLC-WIW | ||
| 912 | |a GBV_ILN_70 | ||
| 936 | b | k | |a 50.16 |q AVZ |
| 936 | b | k | |a 85.38 |q AVZ |
| 951 | |a AR | ||
| 952 | |d 33 |j 2017 |e 7 |h 1549-1565 | ||
| author_variant |
a h ah |
|---|---|
| matchkey_str |
article:07488017:2017----::esnhtcuuadyteiemcnrlhrsomntrntercsma |
| hierarchy_sort_str |
2017 |
| bklnumber |
50.16 85.38 |
| publishDate |
2017 |
| allfields |
10.1002/qre.2124 doi PQ20171228 (DE-627)OLC1997840472 (DE-599)GBVOLC1997840472 (PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653 (KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform DE-627 ger DE-627 rakwb eng 650 690 DNB 50.16 bkl 85.38 bkl Haq, Abdul verfasserin aut New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd. control chart synthetic chart statistical process control conforming run length average run length CUSUM auxiliary information EWMA Process controls Control charts Computer simulation Process parameters Monitoring Charts Optimal control Enthalten in Quality and reliability engineering international Chichester [u.a.] : Wiley, 1985 33(2017), 7, Seite 1549-1565 (DE-627)129167614 (DE-600)50641-2 (DE-576)028403312 0748-8017 nnns volume:33 year:2017 number:7 pages:1549-1565 http://dx.doi.org/10.1002/qre.2124 Volltext http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract https://search.proquest.com/docview/1955921429 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 50.16 AVZ 85.38 AVZ AR 33 2017 7 1549-1565 |
| spelling |
10.1002/qre.2124 doi PQ20171228 (DE-627)OLC1997840472 (DE-599)GBVOLC1997840472 (PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653 (KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform DE-627 ger DE-627 rakwb eng 650 690 DNB 50.16 bkl 85.38 bkl Haq, Abdul verfasserin aut New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd. control chart synthetic chart statistical process control conforming run length average run length CUSUM auxiliary information EWMA Process controls Control charts Computer simulation Process parameters Monitoring Charts Optimal control Enthalten in Quality and reliability engineering international Chichester [u.a.] : Wiley, 1985 33(2017), 7, Seite 1549-1565 (DE-627)129167614 (DE-600)50641-2 (DE-576)028403312 0748-8017 nnns volume:33 year:2017 number:7 pages:1549-1565 http://dx.doi.org/10.1002/qre.2124 Volltext http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract https://search.proquest.com/docview/1955921429 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 50.16 AVZ 85.38 AVZ AR 33 2017 7 1549-1565 |
| allfields_unstemmed |
10.1002/qre.2124 doi PQ20171228 (DE-627)OLC1997840472 (DE-599)GBVOLC1997840472 (PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653 (KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform DE-627 ger DE-627 rakwb eng 650 690 DNB 50.16 bkl 85.38 bkl Haq, Abdul verfasserin aut New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd. control chart synthetic chart statistical process control conforming run length average run length CUSUM auxiliary information EWMA Process controls Control charts Computer simulation Process parameters Monitoring Charts Optimal control Enthalten in Quality and reliability engineering international Chichester [u.a.] : Wiley, 1985 33(2017), 7, Seite 1549-1565 (DE-627)129167614 (DE-600)50641-2 (DE-576)028403312 0748-8017 nnns volume:33 year:2017 number:7 pages:1549-1565 http://dx.doi.org/10.1002/qre.2124 Volltext http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract https://search.proquest.com/docview/1955921429 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 50.16 AVZ 85.38 AVZ AR 33 2017 7 1549-1565 |
| allfieldsGer |
10.1002/qre.2124 doi PQ20171228 (DE-627)OLC1997840472 (DE-599)GBVOLC1997840472 (PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653 (KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform DE-627 ger DE-627 rakwb eng 650 690 DNB 50.16 bkl 85.38 bkl Haq, Abdul verfasserin aut New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd. control chart synthetic chart statistical process control conforming run length average run length CUSUM auxiliary information EWMA Process controls Control charts Computer simulation Process parameters Monitoring Charts Optimal control Enthalten in Quality and reliability engineering international Chichester [u.a.] : Wiley, 1985 33(2017), 7, Seite 1549-1565 (DE-627)129167614 (DE-600)50641-2 (DE-576)028403312 0748-8017 nnns volume:33 year:2017 number:7 pages:1549-1565 http://dx.doi.org/10.1002/qre.2124 Volltext http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract https://search.proquest.com/docview/1955921429 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 50.16 AVZ 85.38 AVZ AR 33 2017 7 1549-1565 |
| allfieldsSound |
10.1002/qre.2124 doi PQ20171228 (DE-627)OLC1997840472 (DE-599)GBVOLC1997840472 (PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653 (KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform DE-627 ger DE-627 rakwb eng 650 690 DNB 50.16 bkl 85.38 bkl Haq, Abdul verfasserin aut New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd. control chart synthetic chart statistical process control conforming run length average run length CUSUM auxiliary information EWMA Process controls Control charts Computer simulation Process parameters Monitoring Charts Optimal control Enthalten in Quality and reliability engineering international Chichester [u.a.] : Wiley, 1985 33(2017), 7, Seite 1549-1565 (DE-627)129167614 (DE-600)50641-2 (DE-576)028403312 0748-8017 nnns volume:33 year:2017 number:7 pages:1549-1565 http://dx.doi.org/10.1002/qre.2124 Volltext http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract https://search.proquest.com/docview/1955921429 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 50.16 AVZ 85.38 AVZ AR 33 2017 7 1549-1565 |
| language |
English |
| source |
Enthalten in Quality and reliability engineering international 33(2017), 7, Seite 1549-1565 volume:33 year:2017 number:7 pages:1549-1565 |
| sourceStr |
Enthalten in Quality and reliability engineering international 33(2017), 7, Seite 1549-1565 volume:33 year:2017 number:7 pages:1549-1565 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
control chart synthetic chart statistical process control conforming run length average run length CUSUM auxiliary information EWMA Process controls Control charts Computer simulation Process parameters Monitoring Charts Optimal control |
| dewey-raw |
650 |
| isfreeaccess_bool |
false |
| container_title |
Quality and reliability engineering international |
| authorswithroles_txt_mv |
Haq, Abdul @@aut@@ |
| publishDateDaySort_date |
2017-01-01T00:00:00Z |
| hierarchy_top_id |
129167614 |
| dewey-sort |
3650 |
| id |
OLC1997840472 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1997840472</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220217093018.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">171125s2017 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/qre.2124</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20171228</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1997840472</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1997840472</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">650</subfield><subfield code="a">690</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.16</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">85.38</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Haq, Abdul</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">control chart</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">synthetic chart</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">statistical process control</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">conforming run length</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">average run length</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">CUSUM</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">auxiliary information</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">EWMA</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Process controls</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Control charts</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Process parameters</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monitoring</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Charts</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Optimal control</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Quality and reliability engineering international</subfield><subfield code="d">Chichester [u.a.] : Wiley, 1985</subfield><subfield code="g">33(2017), 7, Seite 1549-1565</subfield><subfield code="w">(DE-627)129167614</subfield><subfield code="w">(DE-600)50641-2</subfield><subfield code="w">(DE-576)028403312</subfield><subfield code="x">0748-8017</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:33</subfield><subfield code="g">year:2017</subfield><subfield code="g">number:7</subfield><subfield code="g">pages:1549-1565</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1002/qre.2124</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://search.proquest.com/docview/1955921429</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-UMW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-ARC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.16</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">85.38</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">33</subfield><subfield code="j">2017</subfield><subfield code="e">7</subfield><subfield code="h">1549-1565</subfield></datafield></record></collection>
|
| author |
Haq, Abdul |
| spellingShingle |
Haq, Abdul ddc 650 bkl 50.16 bkl 85.38 misc control chart misc synthetic chart misc statistical process control misc conforming run length misc average run length misc CUSUM misc auxiliary information misc EWMA misc Process controls misc Control charts misc Computer simulation misc Process parameters misc Monitoring misc Charts misc Optimal control New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information |
| authorStr |
Haq, Abdul |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)129167614 |
| format |
Article |
| dewey-ones |
650 - Management & auxiliary services 690 - Buildings |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0748-8017 |
| topic_title |
650 690 DNB 50.16 bkl 85.38 bkl New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information control chart synthetic chart statistical process control conforming run length average run length CUSUM auxiliary information EWMA Process controls Control charts Computer simulation Process parameters Monitoring Charts Optimal control |
| topic |
ddc 650 bkl 50.16 bkl 85.38 misc control chart misc synthetic chart misc statistical process control misc conforming run length misc average run length misc CUSUM misc auxiliary information misc EWMA misc Process controls misc Control charts misc Computer simulation misc Process parameters misc Monitoring misc Charts misc Optimal control |
| topic_unstemmed |
ddc 650 bkl 50.16 bkl 85.38 misc control chart misc synthetic chart misc statistical process control misc conforming run length misc average run length misc CUSUM misc auxiliary information misc EWMA misc Process controls misc Control charts misc Computer simulation misc Process parameters misc Monitoring misc Charts misc Optimal control |
| topic_browse |
ddc 650 bkl 50.16 bkl 85.38 misc control chart misc synthetic chart misc statistical process control misc conforming run length misc average run length misc CUSUM misc auxiliary information misc EWMA misc Process controls misc Control charts misc Computer simulation misc Process parameters misc Monitoring misc Charts misc Optimal control |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
Quality and reliability engineering international |
| hierarchy_parent_id |
129167614 |
| dewey-tens |
650 - Management & public relations 690 - Building & construction |
| hierarchy_top_title |
Quality and reliability engineering international |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)129167614 (DE-600)50641-2 (DE-576)028403312 |
| title |
New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information |
| ctrlnum |
(DE-627)OLC1997840472 (DE-599)GBVOLC1997840472 (PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653 (KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform |
| title_full |
New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information |
| author_sort |
Haq, Abdul |
| journal |
Quality and reliability engineering international |
| journalStr |
Quality and reliability engineering international |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2017 |
| contenttype_str_mv |
txt |
| container_start_page |
1549 |
| author_browse |
Haq, Abdul |
| container_volume |
33 |
| class |
650 690 DNB 50.16 bkl 85.38 bkl |
| format_se |
Aufsätze |
| author-letter |
Haq, Abdul |
| doi_str_mv |
10.1002/qre.2124 |
| dewey-full |
650 690 |
| title_sort |
new synthetic cusum and synthetic ewma control charts for monitoring the process mean using auxiliary information |
| title_auth |
New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information |
| abstract |
The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. |
| abstractGer |
The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. |
| abstract_unstemmed |
The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 |
| container_issue |
7 |
| title_short |
New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information |
| url |
http://dx.doi.org/10.1002/qre.2124 http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract https://search.proquest.com/docview/1955921429 |
| remote_bool |
false |
| ppnlink |
129167614 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1002/qre.2124 |
| up_date |
2024-07-04T03:48:55.072Z |
| _version_ |
1803618809367494656 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1997840472</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220217093018.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">171125s2017 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/qre.2124</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20171228</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1997840472</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1997840472</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)p1314-3efffb46d119ee3e88d488699a8c158a2b0f811775a9f10c1bffa53ae77d50653</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0136540120170000033000701549newsyntheticcusumandsyntheticewmacontrolchartsform</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">650</subfield><subfield code="a">690</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.16</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">85.38</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Haq, Abdul</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are potentially powerful process monitoring tool because of their excellent speed in detecting small to moderate shifts in the process parameters. These control charts can be further improved by integrating them with the conforming run length control chart, resulting in the synthetic CUSUM (SynCUSUM) and synthetic EWMA (SynEWMA) charts. In this paper, we enhance the detection abilities of the SynCUSUM and SynEWMA charts using the auxiliary information. With suitable assumptions, the proposed control charts encompass the existing SynCUSUM, SynEWMA, CUSUM, and EWMA charts. Extensive Monte Carlo simulations are used to study the run length profiles of the proposed control charts. It turns out that the proposed near‐optimal control charts with the auxiliary information perform uniformly and substantially better than the existing near‐optimal SynCUSUM, SynEWMA, CUSUM, and EWMA charts. The proposed and existing control charts are also illustrated with the help of an example. Copyright © 2017 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © 2017 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">control chart</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">synthetic chart</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">statistical process control</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">conforming run length</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">average run length</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">CUSUM</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">auxiliary information</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">EWMA</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Process controls</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Control charts</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Process parameters</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monitoring</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Charts</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Optimal control</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Quality and reliability engineering international</subfield><subfield code="d">Chichester [u.a.] : Wiley, 1985</subfield><subfield code="g">33(2017), 7, Seite 1549-1565</subfield><subfield code="w">(DE-627)129167614</subfield><subfield code="w">(DE-600)50641-2</subfield><subfield code="w">(DE-576)028403312</subfield><subfield code="x">0748-8017</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:33</subfield><subfield code="g">year:2017</subfield><subfield code="g">number:7</subfield><subfield code="g">pages:1549-1565</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1002/qre.2124</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1002/qre.2124/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://search.proquest.com/docview/1955921429</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-UMW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-ARC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.16</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">85.38</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">33</subfield><subfield code="j">2017</subfield><subfield code="e">7</subfield><subfield code="h">1549-1565</subfield></datafield></record></collection>
|
| score |
7.4017506 |