1. Other Acceptance Sampling Techniques
Chapter 15
Other Acceptance Sampling Techniques
Introduction to Statistical Quality Control, 4th Edition

2. 15-1. Acceptance Sampling by Variables
Advantages and Disadvantages of Variables Sampling
Advantages
Smaller sample sizes are required
Measurement data usually provide more information about the manufacturing process
When AQLs are very small, the sample sizes required by attributes sampling plans are very large.
Introduction to Statistical Quality Control, 4th Edition

3. 15-1. Acceptance Sampling by Variables
Advantages and Disadvantages of Variables Sampling
Disadvantages
The distribution of the quality characteristic must be known
A separate sampling plan must be employed for each quality characteristic that is being inspected.
It is possible that the use of a variables sampling plan will lead to rejection of a lot even though the actual sample inspected does not contain any defective items.
Introduction to Statistical Quality Control, 4th Edition

4. 15-1. Acceptance Sampling by Variables
Types of Sampling Plans Available
Two types of variables sampling procedures
Plans that control the lot or process fraction defective (or nonconforming). [Procedure 1]
Plans that control a lot or process parameter (usually the mean). [Procedure 2]
Introduction to Statistical Quality Control, 4th Edition

5. 15-1. Acceptance Sampling by Variables
Caution in the Use of Variables Sampling
The distribution of the quality characteristic must be known in order to use variables sampling
The usual assumption is that the parameter of interest follows the normal distribution. This is a critical assumption.
If the normality assumption is not satisfied, then estimates of the fraction defective based on the sample mean and standard deviation will not be the same as if the parameter were normally distributed.
Introduction to Statistical Quality Control, 4th Edition

6. 15-1. Acceptance Sampling by Variables
Caution in the Use of Variables Sampling
It is possible to use variables sampling plans when the parameter of interest does not have a normal distribution.
If the form of the distribution is known, it is possible to devise a procedure for applying a variables sampling plan.
Introduction to Statistical Quality Control, 4th Edition

7. Introduction to Statistical Quality Control, 4th Edition
15-3. MIL STD (ANSI/ASQC Z1.9)
General Description of the Standard
MIL STD 414 is a lot-by-lot acceptance-sampling plan for variables introduced in 1957.
Sample size code letters are used as in MIL STD 105E, but the same code letter does not imply the same sample size in both standards.
Sample sizes are a function of the lot size and the inspection level.
All sampling plans assume the quality characteristic of interest is normally distributed.
Introduction to Statistical Quality Control, 4th Edition

8. Introduction to Statistical Quality Control, 4th Edition
15-3. MIL STD (ANSI/ASQC Z1.9)
General Description of the Standard
MIL STD 414 is divided into four sections:
A: general description of the sampling plans including definitions, sample size code letters, and OC curves for the plans.
B: variables sampling plans based on the sample standard deviation for the case in which the process or lot variability is unknown.
C: variables sampling plans based on the sample range method
D: variables sampling plans for the case where the process standard deviation is known.
Introduction to Statistical Quality Control, 4th Edition

9. Introduction to Statistical Quality Control, 4th Edition
15-3. MIL STD (ANSI/ASQC Z1.9)
Discussion of MIL STD 414 and ANSI/ASQC Z1.9
ANSI/ASQC Z1.9 is the civilian counterpart of MIL STD 414.
Differences and revisions
Lot size ranges were adjusted to correspond to MIL STD 105D
Code letters assigned to the various lot size ranges were arranged to make protection equal to that of MIL STD 105E
AQLs of 0.04, 0.065, and 15 were deleted
Original inspection levels I, II, III, IV, and V were relabeled S3, S4, I, II, III, respectively.
Original switching rules were replaced by thos eof MIL STD 105E, with slight revisions.
Introduction to Statistical Quality Control, 4th Edition