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Acceptance SamplingTab IV pages 3 to 29

Sampling ConceptsByJohn A. Conte, P.E.

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The ASQ CQE BoK

IV Product and Process Control– C. Acceptance Sampling

1. Sampling Concepts– Define, describe, and apply the concepts of producer and

consumer risk and related terms, including operating characteristic (OC) curves, acceptable quality limit (AQL), lot tolerance percent defective (LTPD), average outgoing quality (AOQ), average outgoing quality limit (AOQL), etc. (Analyze)

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The ASQ CQE BoK

IV Product and Process Control– C. Acceptance Sampling

2. Sampling standards and plans– Interpret and apply ANSI/ASQ Z1.4 and Z1.9 standards

for attributes and variables sampling. Identify and distinguish between single, double, multiple, sequential, and continuous sampling methods.

– Identify characteristics of Dodge-Romig sampling tables and when they should be used. (Analyze)

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Acceptance Sampling

Inspection of “Lots” of either incoming raw materials or outgoing product

Decision to accept or reject based on sample All sampling plans have two components

– The sample size (n)– The maximum number of defectives allowed in

the sample (c or Ac) for acceptance of the lot

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Producer’s Risk

The risk of making an incorrect decision by rejecting a “good” lot

For sampling plans in Z1.4 that risk is set at about 5% for a given AQL

AQL is the Acceptable Quality Limit formally known as the Acceptable Quality Level

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CQE Handbook, page 198

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Consumer’s Risk

The probability of making an incorrect decision by accepting a “bad” lot

For Dodge-Romig sampling plans that risk is set at about 10% for a given LTPD

LTPD - Lot Tolerance Percent Defective

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CQE Handbook, page 198

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Acceptance Sampling Risks

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Operating Characteristic Curve

First text given to me as a new engineer at Western Electric Company in 1966

“Sampling Inspection Tables” by Harold Dodge and Harry Romig

115 out of 200 pages devoted to OC curves

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The Operating Characteristic Curve

Allows a sampling plan to be almost completely evaluated at a glace

Gives a pictorial view of the probabilities of accepting lots submitted a varying levels of percent non-conforming.

The OC Curve illustrate the risks of acceptance sampling

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The Operating Characteristic Curve

Curves are based either the Binomial or Poisson distribution

Poisson approximation to the binomial was often used as the binomial computations were quite complex before the age of electronic calculators

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Probability of Acceptance (Pa)

Formula or statistical tables

Most Poisson tables are cumulative and provide the probability for c or fewer given np (λ)

cx

x

npx

a xenpP

0 !)(

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Percent defective

np or λ P(Acceptance)=P(finding 3 or fewer defectives in the sample)

.02 40(.02)=.80 0.991

.04 40(.04)=1.6 0.921

.06 40(.06)=2.4 0.779

.08 40(.08)=3.2 0.603

.10 40(.10)=4.0 0.433

.12 40(.12)=4.8 0.294

.14 40(.14)=5.6 0.191

OC Curve with Poisson Probabilities(λ=0.8, c ≤ 3)

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Percent defective

np or λ P(Acceptance)=P(finding 3 or fewer defectives in the sample)

.02 40(.02)=.80 0.991

.04 40(.04)=1.6 0.921

.06 40(.06)=2.4 0.779

.08 40(.08)=3.2 0.603

.10 40(.10)=4.0 0.433

.12 40(.12)=4.8 0.294

.14 40(.14)=5.6 0.191

OC Curve with Poisson Probabilities(λ = 1.6, c ≤ 3)

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Percent defective

np or λ P(Acceptance)=P(finding 3 or fewer defectives in the sample)

.02 40(.02)=.80 0.991

.04 40(.04)=1.6 0.921

.06 40(.06)=2.4 0.779

.08 40(.08)=3.2 0.603

.10 40(.10)=4.0 0.433

.12 40(.12)=4.8 0.294

.14 40(.14)=5.6 0.191

OC Curve with Poisson Probabilities(λ=2.4, 3.2, 4.0, 4.8, 5.6, c ≤ 3)

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Operating Characteristic (OC) CurveSample Size = 40, Acceptance Number = 3

Percent defective np or λ P(Acceptance)=P(finding 3 or fewer defectives in the sample)

.02 40(.02)=.80 0.991

.04 40(.04)=1.6 0.921

.06 40(.06)=2.4 0.779

.08 40(.08)=3.2 0.603

.10 40(.10)=4.0 0.433

.12 40(.12)=4.8 0.294

.14 40(.14)=5.6 0.191

Draw the OC Curve using probabilities

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Acceptable Quality Level (AQL)

From Z1.4 – Acceptance Quality Limit (AQL) “4.2 Definition: The AQL is the quality level

that is the worst tolerable process average average whena continuing series of lots is submitted for acceptance sample.”

“Note: The use of the abbreviation AQL to mean Acceptable Quality level is no longer recommended.”

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Acceptable Quality Level

From Z1.4 - “Although individual lots with quality as bad as the AQL can be accepted with a fairly high probability, the designation of a n AQL does not suggest that this is necessary a desirable quality level. The AQL is a parameter of the sampling scheme …”

The probability of acceptance of a lot with a process average equal to the AQL is normally set at 0.95

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Operating Characteristic (OC) CurveSample Size = 40, Acceptance Number = 3

Percent defective np or λ P(Acceptance)=P(finding 3 or fewer defectives in the sample)

.02 40(.02)=.80 0.991

.04 40(.04)=1.6 0.921

.06 40(.06)=2.4 0.779

.08 40(.08)=3.2 0.603

.10 40(.10)=4.0 0.433

.12 40(.12)=4.8 0.294

.14 40(.14)=5.6 0.191

Draw the OC Curve using probabilities

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Minitab SoftwareCreate or Compare Sampling Plan

Stat– Quality Tools

Acceptance Sampling by Attributes

Default Screen– Create based on input of AQL, LTPD, and N– Or Compare based on input of n, c, and N – Measurement type percent defective– Acceptable Quality Level (AQL) 0.05– Rejectable Quality Level (RQL or LTPD) 0.10

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Minitab Example - Compare

Acceptance Sampling by Attributes

Measurement type: Go/no go Lot quality in percent defective Lot size: 100000 Use binomial distribution to calculate probability of acceptance

Compare User Defined Plan(s)

Sample Size 40 Acceptance Number 3

Accept lot if defective items in 40 sampled <= 3; Otherwise reject. Average outgoing quality limit (AOQL) = 4.860 at 7.241 percent defective.

Graphs - Acceptance Sampling by Attributes

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Operating Characteristic (OC) Curve Average Outgoing Quality (AOQ) Curve

Average Total Inspection (ATI) Curve

Sample Size = 40, Acceptance Number = 3

Minitab Example – CompareInput of n, c, and N

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Mintab Example – Create Plan

Acceptance Sampling by Attributes Measurement type: Go/no go Lot quality in percent defective Lot size: 1000 Use binomial distribution to calculate probability of acceptance Acceptable Quality Level (AQL) 1 Producer's Risk (Alpha) 0.05 Rejectable Quality Level (RQL or LTPD) 5 Consumer's Risk (Beta) 0.1 Generated Plan(s) Sample Size 132 Acceptance Number 3 Accept lot if defective items in 132 sampled <= 3; Otherwise reject. Percent Probability Probability Defective Accepting Rejecting AOQ ATI 1 0.956 0.044 0.830 170.4 5 0.099 0.901 0.431 913.9 Average outgoing quality limit (AOQL) = 1.278 at 2.220 percent defective.

Graphs - Acceptance Sampling by Attributes

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Operating Characteristic (OC) Curve Average Outgoing Quality (AOQ) Curve

Average Total Inspection (ATI) Curve

Sample Size = 132, Acceptance Number = 3

Minitab Create (AQL=1%, LTPD=5%)

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AOQ and AOQL

Average Outgoing Quality (AOQ) AOQ dependent on the Incoming Quality Average Outgoing Quality Limit AOQL highest value of AOQ

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AOQ - Average Outgoing Quality

The expected average quality of all products, including all accepted lots, plus all rejected lots that have been sorted 10% and have had all defective units replaced

Will always be less than the submitted quality AOQ = Pa * p ( 1 –n/N ) AOQL is the maximum value of AAOQ

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AOQL in Z1.4 – Table XI

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Minitab Software

Stat– Quality Tools

Acceptance Sampling by Attributes

Default Screen– Create Sampling Plan– Measurement type percent defective– Acceptable Quality Level (AQL) 0.05– Rejectable Quality Level (RQL or LTPD) 0.10

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CQE Exam Questions

A single sampling plan calls for a sample size of 80 with an acceptance number of 5 and a rejection number of 6. If the quality of the submitted lots is ten percent defective, then the percent of lots expected to be accepted in the long run is approximately: A. 6% B. 10% C. 30% D. 0% E. 20%

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Which of the following sampling plans gives the greatest protection against accepting lots of poor quality?

1. Sample size = 200, c = 14 2. Sample size = 100, c = 7 3. Sample size = 200, c = 21 4. Sample size = 200, c = 12

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Where to find out more

The Certified Quality Engineer Handbook, Connie M. Borror, editor, ASQ Press, pages 193 to 226

ANSI/ASQ Z1.4

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CQE Exam Question

The two quantities that uniquely determine a attribute sampling plan are:

A. AQL and LTPD B. sample size and rejection number C. AQL and producer's risk D. LTPD and consumer's risk

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CQE Exam Question

The diagram shows operating characteristic (OC) curves for two sampling plans. The dashed curve is:

A. Better. B. Worse. C. Better fro the consumer. D. Better for the producer.

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Z1.4 Sample Size Code LettersLot Size = 1000, GIL=II → J

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Z1.4 Table II-ASample J, AQL 4.0 → n=80, c= 7

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Minitab Demo

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CQE Exam Problem

The AOQL for the single sampling plan with sample size of 200, an acceptance number of 14 and rejection number of 15 for a lot size of 4000 is approximately:

A. 10.0% B. 4.5% C. 4.0% D. 7.2%

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Z 1.4 Table II-A

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Z 1.4 Table V-A

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Z 1.4 Table V-A Note

4.7% times (1-200/4000)= 4.7 x 0.95 = 4.5%

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Operating Characteristic (OC) Curve Average Outgoing Quality (AOQ) Curve

Average Total Inspection (ATI) Curve

Sample Size = 200, Acceptance Number = 14

Minitab output

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