A variable sampling interval EWMA chart for attributes
Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model f...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Epprecht, Eugenio K. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Limited 2009 |
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| Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - London : Springer, 1985, 49(2009), 1-4 vom: 18. Nov., Seite 281-292 |
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| Übergeordnetes Werk: |
volume:49 ; year:2009 ; number:1-4 ; day:18 ; month:11 ; pages:281-292 |
| Links: |
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| DOI / URN: |
10.1007/s00170-009-2390-3 |
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| Katalog-ID: |
SPR001613553 |
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| 100 | 1 | |a Epprecht, Eugenio K. |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A variable sampling interval EWMA chart for attributes |
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| 520 | |a Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. | ||
| 650 | 4 | |a Variable sampling interval |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a EWMA control chart |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Attributes |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fraction nonconforming |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Adaptive control charts |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Statistical process control charts |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Poisson EWMA |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a VSI |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Simões, Bruno F. T. |4 aut | |
| 700 | 1 | |a Mendes, Flávia C. T. |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t The international journal of advanced manufacturing technology |d London : Springer, 1985 |g 49(2009), 1-4 vom: 18. Nov., Seite 281-292 |w (DE-627)270127712 |w (DE-600)1476510-X |x 1433-3015 |7 nnns |
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10.1007/s00170-009-2390-3 doi (DE-627)SPR001613553 (SPR)s00170-009-2390-3-e DE-627 ger DE-627 rakwb eng Epprecht, Eugenio K. verfasserin aut A variable sampling interval EWMA chart for attributes 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2009 Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. Variable sampling interval (dpeaa)DE-He213 EWMA control chart (dpeaa)DE-He213 Attributes (dpeaa)DE-He213 Fraction nonconforming (dpeaa)DE-He213 Adaptive control charts (dpeaa)DE-He213 Statistical process control charts (dpeaa)DE-He213 Poisson EWMA (dpeaa)DE-He213 VSI (dpeaa)DE-He213 Simões, Bruno F. T. aut Mendes, Flávia C. T. aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 49(2009), 1-4 vom: 18. Nov., Seite 281-292 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:49 year:2009 number:1-4 day:18 month:11 pages:281-292 https://dx.doi.org/10.1007/s00170-009-2390-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2009 1-4 18 11 281-292 |
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10.1007/s00170-009-2390-3 doi (DE-627)SPR001613553 (SPR)s00170-009-2390-3-e DE-627 ger DE-627 rakwb eng Epprecht, Eugenio K. verfasserin aut A variable sampling interval EWMA chart for attributes 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2009 Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. Variable sampling interval (dpeaa)DE-He213 EWMA control chart (dpeaa)DE-He213 Attributes (dpeaa)DE-He213 Fraction nonconforming (dpeaa)DE-He213 Adaptive control charts (dpeaa)DE-He213 Statistical process control charts (dpeaa)DE-He213 Poisson EWMA (dpeaa)DE-He213 VSI (dpeaa)DE-He213 Simões, Bruno F. T. aut Mendes, Flávia C. T. aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 49(2009), 1-4 vom: 18. Nov., Seite 281-292 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:49 year:2009 number:1-4 day:18 month:11 pages:281-292 https://dx.doi.org/10.1007/s00170-009-2390-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2009 1-4 18 11 281-292 |
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10.1007/s00170-009-2390-3 doi (DE-627)SPR001613553 (SPR)s00170-009-2390-3-e DE-627 ger DE-627 rakwb eng Epprecht, Eugenio K. verfasserin aut A variable sampling interval EWMA chart for attributes 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2009 Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. Variable sampling interval (dpeaa)DE-He213 EWMA control chart (dpeaa)DE-He213 Attributes (dpeaa)DE-He213 Fraction nonconforming (dpeaa)DE-He213 Adaptive control charts (dpeaa)DE-He213 Statistical process control charts (dpeaa)DE-He213 Poisson EWMA (dpeaa)DE-He213 VSI (dpeaa)DE-He213 Simões, Bruno F. T. aut Mendes, Flávia C. T. aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 49(2009), 1-4 vom: 18. Nov., Seite 281-292 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:49 year:2009 number:1-4 day:18 month:11 pages:281-292 https://dx.doi.org/10.1007/s00170-009-2390-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2009 1-4 18 11 281-292 |
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10.1007/s00170-009-2390-3 doi (DE-627)SPR001613553 (SPR)s00170-009-2390-3-e DE-627 ger DE-627 rakwb eng Epprecht, Eugenio K. verfasserin aut A variable sampling interval EWMA chart for attributes 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2009 Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. Variable sampling interval (dpeaa)DE-He213 EWMA control chart (dpeaa)DE-He213 Attributes (dpeaa)DE-He213 Fraction nonconforming (dpeaa)DE-He213 Adaptive control charts (dpeaa)DE-He213 Statistical process control charts (dpeaa)DE-He213 Poisson EWMA (dpeaa)DE-He213 VSI (dpeaa)DE-He213 Simões, Bruno F. T. aut Mendes, Flávia C. T. aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 49(2009), 1-4 vom: 18. Nov., Seite 281-292 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:49 year:2009 number:1-4 day:18 month:11 pages:281-292 https://dx.doi.org/10.1007/s00170-009-2390-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2009 1-4 18 11 281-292 |
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10.1007/s00170-009-2390-3 doi (DE-627)SPR001613553 (SPR)s00170-009-2390-3-e DE-627 ger DE-627 rakwb eng Epprecht, Eugenio K. verfasserin aut A variable sampling interval EWMA chart for attributes 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2009 Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. Variable sampling interval (dpeaa)DE-He213 EWMA control chart (dpeaa)DE-He213 Attributes (dpeaa)DE-He213 Fraction nonconforming (dpeaa)DE-He213 Adaptive control charts (dpeaa)DE-He213 Statistical process control charts (dpeaa)DE-He213 Poisson EWMA (dpeaa)DE-He213 VSI (dpeaa)DE-He213 Simões, Bruno F. T. aut Mendes, Flávia C. T. aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 49(2009), 1-4 vom: 18. Nov., Seite 281-292 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:49 year:2009 number:1-4 day:18 month:11 pages:281-292 https://dx.doi.org/10.1007/s00170-009-2390-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2009 1-4 18 11 281-292 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR001613553</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230327143125.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201001s2009 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00170-009-2390-3</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR001613553</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00170-009-2390-3-e</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="100" ind1="1" ind2=" "><subfield code="a">Epprecht, Eugenio K.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A variable sampling interval EWMA chart for attributes</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2009</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">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag London Limited 2009</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. 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Epprecht, Eugenio K. |
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Epprecht, Eugenio K. misc Variable sampling interval misc EWMA control chart misc Attributes misc Fraction nonconforming misc Adaptive control charts misc Statistical process control charts misc Poisson EWMA misc VSI A variable sampling interval EWMA chart for attributes |
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A variable sampling interval EWMA chart for attributes Variable sampling interval (dpeaa)DE-He213 EWMA control chart (dpeaa)DE-He213 Attributes (dpeaa)DE-He213 Fraction nonconforming (dpeaa)DE-He213 Adaptive control charts (dpeaa)DE-He213 Statistical process control charts (dpeaa)DE-He213 Poisson EWMA (dpeaa)DE-He213 VSI (dpeaa)DE-He213 |
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A variable sampling interval EWMA chart for attributes |
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Epprecht, Eugenio K. Simões, Bruno F. T. Mendes, Flávia C. T. |
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Epprecht, Eugenio K. |
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variable sampling interval ewma chart for attributes |
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A variable sampling interval EWMA chart for attributes |
| abstract |
Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. © Springer-Verlag London Limited 2009 |
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Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. © Springer-Verlag London Limited 2009 |
| abstract_unstemmed |
Abstract We propose a variable sampling interval exponentially weighted moving average (VSI c EWMA) chart for the average number of nonconformities in the sample, with the objective of improved detection of small to moderate increases in the process nonconformities rate. Using a Markov chain model for the calculations, we obtain optimal designs for this chart as well as for the fixed sampling interval c EWMA chart and compare the performances of the two control schemes in terms of their expected times to signal an out-of-control condition. The designs are optimal in the sense that they minimize the expected delay in the detection of upward shifts of a specified magnitude in the process nonconformities rate, while keeping the false alarm rate and the average sampling frequency at specified levels. The results reveal considerable gains in detection speed with the use of the VSI scheme. The optimal parameters found for each case are tabulated and may be used directly in practice. The results of the analysis, including the optimal design parameters tabulated, can also be extended to a VSI np EWMA chart for improved detection of small to moderate increases in the fraction nonconforming of the process provided that in-control fraction nonconforming is small. © Springer-Verlag London Limited 2009 |
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| title_short |
A variable sampling interval EWMA chart for attributes |
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Simões, Bruno F. T. Mendes, Flávia C. T. |
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|
| score |
7.400528 |