Introduction to Statistical Quality Control

Montgomery, D. C. (2019). Introduction to Statistical Quality Control. Wiley.

Type

Book

Intellectual base

Textbook

Year

2019

ISBN

9781119399308

Link

https://www.wiley.com/en-us/Introduction+to+Statistical+Quality+Control%2C+8th+Edition-p-9781119399308

Cited from

data_science, engineering_design, statistics_experimental_design

Cited by

10 citations across 10 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Baseline Deviation
  • In industrial quality control it is a measurement against a tolerance band with an in-spec/out-of-spec flag.

    This sourceStandard treatment of tolerance/specification limits and in-spec/out-of-spec judgment in industrial quality control.

• Instrument Interpretive Drift
  • The within-slice blindness is exact and demonstrable: a gauge repeatability-and-reproducibility (R&R) study run on any single day shows excellent agreement among operators and excellent test-retest reliability, because they are all drifting together against the same slowly-moving instrument.

    This sourceStandard text on gauge R&R studies showing high within-study operator agreement and reproducibility can coexist with a slowly drifting measurement system.

• Quality Control
  • A QA engineer designs a robust manufacturing process; a QC engineer measures the output of that process and triggers correction when variation exceeds bounds, a complementary pairing Montgomery (2019) treats as the central organizing principle of statistical quality control.

    This sourceStandard textbook treatment establishing that quality control (catching defects) and quality assurance (preventing them) are complementary necessities; develops the integrated SQC and DMAIC framework.

Domain-specific

• EWMA chart
  • … observations, an EWMA initialized at the target uses geometrically declining weights and time-varying variance approaching the steady-state limit. to A measurement laboratory can monitor a check standard over time using an EWMA chart to accumulate evidence of small calibration drift. demonstrates that continuity.
• Natural Process Variation
  • Shewhart charts estimate and monitor stable behavior; capability analysis asks the separate question whether that stable distribution meets requirements.
• Np-chart
  • Limits describe expected common-cause variation under the model; specification limits describe customer or engineering acceptability and are separate.
• Process performance index
  • Descriptive quality metric only; production release and safety decisions require validated measurement, stability analysis and qualified process engineering.
• Regression control chart
  • The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.
• U-chart
  • The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.
• X-bar chart
  • Conceptual quality-control identity only; production acceptance and safety decisions require validated measurement systems, domain limits and qualified process engineering.

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