Introduction to Statistical Quality Control¶
Montgomery, D. C. (2013). Introduction to Statistical Quality Control. John Wiley & Sons.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Verification
- The pattern is what lets a software team transfer practices from manufacturing QC (statistical process control, root-cause analysis, gauge studies) into CI/CD without re-deriving them from scratch, as Montgomery (2012) documents in his treatment of SPC across manufacturing and service domains.
This sourceStandard reference on statistical quality control: develops SPC charts, acceptance sampling, gauge R&R, and DMAIC as procedures for verifying conformance to specification across both manufacturing and service operations, including the transfer of these methods to software process improvement.
- The pattern is what lets a software team transfer practices from manufacturing QC (statistical process control, root-cause analysis, gauge studies) into CI/CD without re-deriving them from scratch, as Montgomery (2012) documents in his treatment of SPC across manufacturing and service domains.
Mechanisms¶
- Risk-Stratified Acceptance Sampling Plan
- Its central deception is that a sample sized for the average defect says almost nothing about a rare, clustered, or critical one — the operating-characteristic curve that governs the plan buys down producer's and consumer's risk only for the defect rate it was designed around.
This sourceExplains how an acceptance-sampling plan's operating-characteristic curve relates acceptance probability to specified defect levels and the associated producer and consumer risks.
- Its central deception is that a sample sized for the average defect says almost nothing about a rare, clustered, or critical one — the operating-characteristic curve that governs the plan buys down producer's and consumer's risk only for the defect rate it was designed around.
Verification¶
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