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Statistical Methods for Quality Assurance - Basics, Measurement, Control, Capability, and Improvement (Paperback, 2nd ed. 2016)
Loot Price: R4,776
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Statistical Methods for Quality Assurance - Basics, Measurement, Control, Capability, and Improvement (Paperback, 2nd ed. 2016)
Series: Springer Texts in Statistics
Expected to ship within 18 - 22 working days
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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
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