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Statistical quality control: a loss minimization approach
While many books on quality espouse the Taguchi loss function, they do not examine its impact on statistical quality control (SQC). But using the Taguchi loss function sheds new light on questions relating to SQC and calls for some changes. This book covers SQC in a way that conforms with the need t...
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Lenguaje: | eng |
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World Scientific
1999
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Acceso en línea: | http://cds.cern.ch/record/1604138 |
_version_ | 1780931588134010880 |
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author | Trietsch, Dan |
author_facet | Trietsch, Dan |
author_sort | Trietsch, Dan |
collection | CERN |
description | While many books on quality espouse the Taguchi loss function, they do not examine its impact on statistical quality control (SQC). But using the Taguchi loss function sheds new light on questions relating to SQC and calls for some changes. This book covers SQC in a way that conforms with the need to minimize loss. Subjects often not covered elsewhere include: (i) measurements, (ii) determining how many points to sample to obtain reliable control charts (for which purpose a new graphic tool, diffidence charts, is introduced), (iii) the connection between process capability and tolerances, (iv) |
id | cern-1604138 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 1999 |
publisher | World Scientific |
record_format | invenio |
spelling | cern-16041382021-04-21T22:24:52Zhttp://cds.cern.ch/record/1604138engTrietsch, DanStatistical quality control: a loss minimization approachMathematical Physics and MathematicsWhile many books on quality espouse the Taguchi loss function, they do not examine its impact on statistical quality control (SQC). But using the Taguchi loss function sheds new light on questions relating to SQC and calls for some changes. This book covers SQC in a way that conforms with the need to minimize loss. Subjects often not covered elsewhere include: (i) measurements, (ii) determining how many points to sample to obtain reliable control charts (for which purpose a new graphic tool, diffidence charts, is introduced), (iii) the connection between process capability and tolerances, (iv)World Scientificoai:cds.cern.ch:16041381999 |
spellingShingle | Mathematical Physics and Mathematics Trietsch, Dan Statistical quality control: a loss minimization approach |
title | Statistical quality control: a loss minimization approach |
title_full | Statistical quality control: a loss minimization approach |
title_fullStr | Statistical quality control: a loss minimization approach |
title_full_unstemmed | Statistical quality control: a loss minimization approach |
title_short | Statistical quality control: a loss minimization approach |
title_sort | statistical quality control: a loss minimization approach |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/1604138 |
work_keys_str_mv | AT trietschdan statisticalqualitycontrolalossminimizationapproach |