國立虎尾科技大學 |

Statistical Methods for Quality Assurance = Basics, Measurement, Control, Capability, and Improvement /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Statistical Methods for Quality Assurance/ by Stephen B. Vardeman, J. Marcus Jobe.
Reminder of title:	Basics, Measurement, Control, Capability, and Improvement /
Author:	Vardeman, Stephen B.
other author:	Jobe, J. Marcus.
Description:	XIV, 437 p. 104 illus., 99 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-0-387-79106-7
ISBN:	9780387791067

Statistical Methods for Quality Assurance = Basics, Measurement, Control, Capability, and Improvement /
Vardeman, Stephen B.

Statistical Methods for Quality AssuranceBasics, Measurement, Control, Capability, and Improvement /[electronic resource] :by Stephen B. Vardeman, J. Marcus Jobe. - 2nd ed. 2016. - XIV, 437 p. 104 illus., 99 illus. in color.online resource. - Springer Texts in Statistics,1431-875X. - Springer Texts in Statistics,.

Introduction -- Statistics and Measurement -- Process Monitoring -- Process Characterization and Capability Analysis -- Experiment Design and Analysis for Process Improvement Part 1: Basics -- Experiment Design and Analysis for Process Improvement Part 2: Advanced Topics -- A Tables.

This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings.

ISBN: 9780387791067

Standard No.: 10.1007/978-0-387-79106-7doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Statistical Methods for Quality Assurance = Basics, Measurement, Control, Capability, and Improvement /
LDR:03588nam a22003975i 4500 001 975614
003 DE-He213
005 20200704002326.0
007 cr nn 008mamaa
008 201211s2016 xxu| s |||| 0|eng d
020 $a 9780387791067 $9 978-0-387-79106-7
024 7 $a 10.1007/978-0-387-79106-7 $2 doi
035 $a 978-0-387-79106-7
050 4 $a QA276-280
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
100 1 $a Vardeman, Stephen B. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 908535
245 1 0 $a Statistical Methods for Quality Assurance $h [electronic resource] : $b Basics, Measurement, Control, Capability, and Improvement / $c by Stephen B. Vardeman, J. Marcus Jobe.
250 $a 2nd ed. 2016.
264 1 $a New York, NY : $b Springer New York : $b Imprint: Springer, $c 2016.
300 $a XIV, 437 p. 104 illus., 99 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Springer Texts in Statistics, $x 1431-875X
505 0 $a Introduction -- Statistics and Measurement -- Process Monitoring -- Process Characterization and Capability Analysis -- Experiment Design and Analysis for Process Improvement Part 1: Basics -- Experiment Design and Analysis for Process Improvement Part 2: Advanced Topics -- A Tables.
520 $a This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings.
650 0 $a Statistics . $3 1253516
650 1 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
700 1 $a Jobe, J. Marcus. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1112823
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9780387791050
776 0 8 $i Printed edition: $z 9780387570747
830 0 $a Springer Texts in Statistics, $x 1431-875X $3 1257998
856 4 0 $u https://doi.org/10.1007/978-0-387-79106-7
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)