Process Validation (Stage 2)
Acceptance Criteria and
Sampling Plans
Jacalyn L. Schroeder
Statistician, Validation/Quality
Engineering Specialist
J.L. Schroeder , 3M, June 2015 4
• Sampling Plans to Meet Validation Stage 2
Objectives
• Understanding of sampling plan performance
levels, confidence levels, and associated risks
• Utilization of product and process understanding
studies (PPU) to determine sample size and
acceptance criteria needed for validation study
• Confidence statements to be made when passing a
validation study
• Interactive Exercises (Throughout)
AGENDA
Sampling Plans
• A sampling plan is a
procedure for making
accept/reject decisions:
– Take 300 samples from a lot
and accept if there are zero
defects
• Includes both a sample size
and acceptance criteria
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008
J.L. Schroeder , 3M, June 2015 8
•Accept = Pass validation study and go into production
•Reject = Fail validation study and must improve the product or process
Sampling Plans - Validation
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008
Objective of Validation
• Establishing by objective
evidence that a process
consistently produces a result
or product meeting its
predetermined specifications
(21 CFR Part 820)
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008
J.L. Schroeder , 3M, June 2015
Validation Stages
A Lifecycle Approach
Process Design
Stage 1
Process Qualification
Stage 2
Continued Process Verification
Stage 3
J.L. Schroeder , 3M, June 2015 12
• Per 21 CFR 820.250 – “Sampling plans,
when used, shall be written and based
on a valid statistical rationale”
• A sampling plan can be used to
demonstrate that a required
performance level (protection for
consumer) is met
Sampling Plans to Meet
Validation Stage 2 Objective(s)
J.L. Schroeder , 3M, June 2015 13
Sampling Plans to Meet
Validation Stage 2 Objectives
• CGMP regulations regarding sampling set
forth a number of requirements for
validation:
• Samples must represent the batch under analysis
(§ 211.160(b)(3))
• Sampling plan must result in statistical confidence
(§ 211.165(c) and (d))
• Batch must meet its predetermined specifications
(§ 211.165(a)).”
J.L. Schroeder , 3M, June 2015 14
• For validation we want a sample to represent production
• Need Representative Sample: Stratified and periodic sampling is desired over complete random sampling. Keep samples in time order for analysis.
• “Handful Sampling” is not representative sample
• Remember that validation is confirmation:
• Should not enter validation until you have an understanding that process is capable
– Design verification should verify
– Estimate of Ppk > 1
Sampling Plans to Meet
Validation Stage 2 Objectives
J.L. Schroeder , 3M, June 2015 16
Statistical Based Sampling Plans
(Based on OC Curve and Two Points)
(AQL, 1-α)
RQL, β)
Each sampling plan has it’s own OC curve
J.L. Schroeder , 3M, June 2015 21
• The AQL of a sampling plan
is a level of quality (percent defective, defects
per hundred units, etc.) routinely accepted by
the sampling plan
• If you want to be assured of passing the
validation study, your process percent
defective needs to be below the sampling
plan’s AQL
What is AQL?
AQL
What is routinely accepted 0.95
J.L. Schroeder , 3M, June 2015 22
• The LTPD of a sampling plan is a level of quality
(percent defective, defects per hundred units, etc.)
routinely rejected by the sampling plan
• Let LTPD0.05 (LTPDβ) be designated as the level of
performance (or performance level) that we want to
be below in order to pass the validation
What is LTPD (AKA RQL)?
LTPD
.05 or .10
What is routinely rejected
Why is AQL/LTPD Important?
• Why is AQL important?
– Effects chances of passing (Higher defective, need higher AQL to pass)
– Effects overall cost of validation
• Why is LTPD important?
– Products or processes at or worse than the LTPD fail most of the time
– Provides plan protection
• Example of Different Plans
– All these plans have different chances of passing (AQL) but provide the
same protection (LTPD0.05)
Sampling Plan AQL LTPD0.05
n=300, a=0 0.017% 1.0%
n=470, a=1 0.076% 1.0%
n=630, a=2 0.13% 1.0%
n=770, a=3 0.18% 1.0%23
Steps To Choose Statistical Based
Validation Sampling Plans to Meet
Validation Stage 2 Objectives
J.L. Schroeder , 3M, June 2015
Steps to Choose Statistical Based
Sampling Plan for Validation
J.L. Schroeder , 3M, June 2015
1. Determine Protection Required
a. Select Performance Level (What will FAIL
plan?). Select sampling plans that have
Performance level = LTPDβ =LTPD.05
b. Select Confidence Level (1-β)
2. Select Best Sampling Plan based on
estimated AQL (Ppk for variables data) and
sample size
Steps To Choose Validation Sampling Plans
Resource: Dr. Wayne Taylor Validation
Sampling Plan Class – 2008
Step 1a:
Select Performance Level
• Performance Level should be selected
based on risk
• Should be consistent with AQLs used in
manufacturing
– Validated performance level should also be
consistent with on-going inspection performed
during manufacturing
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008
Step 1a: Performance Levels
[LTPDβ] for PQ
• Commonly used in pharmaceutical and medical device industries for disposablesare:
– For Defect (Health and Safety)0.065%, 0.1%
– For Defects (Functional)0.25%, 0.4%, 0.65%, 1.0%
– For Defects (Cosmetic)2.5%, 4.0%
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008 29
Step 1a: Performance Levels
[LTPDβ] for PQ
• Commonly used in medical device industry for hardware and very expensive devices are:
– For Critical Defect (Health and Safety)0.1% (99.9% reliability), 0.3% (99.7% reliability), 1% (99% reliability)
– For Major Defects (Functional)1% (99% reliability), 3% (97% reliability), 5% (95% reliability)
– For Minor Defects (Cosmetic)5.0% (95% reliability), 10% (90% reliability)
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008
Step 1a: Performance Levels at LTPD.05
Risk OQ PQ
Critical 5% (95% Conformance) 1% (99% Conformance)
Major 10% (90%
Conformance)
3% (97% Conformance)
Minor 20% (80%
Conformance)
5% (95% Conformance)
31
Resource: Taylor Enterprises
Statistical Procedures For
Medical Device Industry 2013
J.L. Schroeder , 3M, June 2015
�Confidence Level Recommendations:
�Recommend using Consumer Risk (β) of
� β=5% or 10%
�Equates to (1-β)
�95% or 90% Confidence Level
Step 1b:
Determine Confidence Level (1-β)
to make CONFIDENCE STATEMENT
Confidence Statements
• Conclusion when pass a sampling plan
• Sampling plans are designed to demonstrate that the product tested meets a specified performance level (LTPDβ)with certain confidence (typically 1 – β or 95%)
– Passing the plan n=300, a=0 allows one to state: “With 95% confidence the defect level is below 1% defective.”
34
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008 LTPD
J.L. Schroeder , 3M, June 2015
�For Variables Data: Use estimated
Ppk to estimate AQL
�For Attribute Data: Estimate quality
level (typically in percent defective)
that customer will find acceptable
95% of the time
Step 2: Determine BEST Sampling
Plan based on ESTIMATED AQL
J.L. Schroeder , 3M, June 2015
• Choose Attribute or Variables Plans
• Use Validation Sampling Plan Tables
(www.variation.com)
Step 2:
Select Validation Sampling Plans
36
Tables of Plans
• From Design Verification and Process Validation Sampling Plans SOP
• LTPD:
– 20%, 10%, 6.5%, 5%, 4%, 3%, 2.5%, 1.5%, 1%, 0.65%, 0.4%, 0.3%, 0.25%, 0.15%, 0.1%, 0.065%
• Tables:
– Attribute 90% Confidence
– Attribute 95% Confidence
– Variables 1-Sided 95% Confidence
– Variables 2-Sided 95% ConfidenceResource: Dr. Wayne Taylor
Validation Sampling Plan Class -
2008
J.L. Schroeder , 3M, June 2015
LTPD = 1%
Attribute Plans with 90% Confidence Attribute Plans with 95% Confidence
Type Parameters AQL LTPD 0.1 Type Parameters AQL LTPD 0.05
Single n=230, a=0 0.02% 1% Single n=300, a=0 0.02% 1%
Single n=390, a=1 0.09% 1% Single n=470, a=1 0.08% 1%
Double n1=250, a1=0, r1=2, n2=400, a2=2 0.11% 1% Double n1=325, a1=0, r1=2, n2=400, a2=2 0.09% 1%
Single n=530, a=2 0.15% 1% Single n=630, a=2 0.13% 1%
Double n1=250, a1=0, r1=3, n2=560, a2=3 0.18% 1% Double n1=325, a1=0, r1=3, n2=580, a2=3 0.15% 1%
Single n=670, a=3 0.20% 1% Single n=770, a=3 0.18% 1%
Double n1=250, a1=0, r1=3, n2=720, a2=4 0.21% 1% Double n1=325, a1=0, r1=3, n2=720, a2=4 0.18% 1%
Variables – 1-sided – 95% Confidence Variables – 2-sided – 95% Confidence
Parameters AQL LTPD 0.05 Parameters AQL LTPD 0.05
n=15, Ppk=1.17 0.00017% (Ppk=1.55) 1% (Ppk=0.78) n=15, Ppk=1.17, Pp=1.17 0.00016% (Ppk=1.55) 1% (Ppk=0.78)
n=20, Ppk=1.10 0.0012% (Ppk=1.41) 1% (Ppk=0.78) n=20, Ppk=1.11, Pp=1.13 0.001% (Ppk=1.42) 1% (Ppk=0.78)
n=30, Ppk=1.02 0.008% (Ppk=1.26) 1% (Ppk=0.78) n=30, Ppk=1.03, Pp=1.07 0.007% (Ppk=1.27) 1% (Ppk=0.78)
n=40, Ppk=0.98 0.02% (Ppk=1.18) 1% (Ppk=0.78) n=40, Ppk=0.99, Pp=1.04 0.018% (Ppk=1.19) 1% (Ppk=0.78)
n=50, Ppk=0.95 0.04% (Ppk=1.12) 1% (Ppk=0.78) n=50, Ppk=0.96, Pp=1.02 0.033% (Ppk=1.13) 1% (Ppk=0.78)
n=60, Ppk=0.94 0.05% (Ppk=1.10) 1% (Ppk=0.78) n=60, Ppk=0.95, Pp=1.01 0.044% (Ppk=1.11) 1% (Ppk=0.78)
n=80, Ppk=0.91 0.09% (Ppk=1.04) 1% (Ppk=0.78) n=80, Ppk=0.92, Pp=0.99 0.08% (Ppk=1.05) 1% (Ppk=0.78)
n=100, Ppk=0.89 0.13% (Ppk=1.01) 1% (Ppk=0.78) n=100, Ppk=0. 90, Pp=0.97 0.11% (Ppk=1.02) 1% (Ppk=0.78)
Tables Developed from Validated “Sampling Plan Analyzer”
– Version 2.0
Copyright 2001 Taylor Enterprises Inc.
J.L. Schroeder , 3M, June 2015
Summary:
Steps to Choose Statistical Based
Sampling Plan for Validation
J.L. Schroeder , 3M, June 2015
• In order to pass a validation study ,
the process must be significantly
better than the validation performance level
• Two Questions You Should Always Ask:
– Answered by LTPD:
• If I pass the validation study, what confidence
statement can I make?
– Answered by AQL:
• If my process is good, what are the chances of
passing the validation study?
Key Points
Resource: Dr. Wayne Taylor
Validation Sampling Plan Class -
200840
• Desire to validate a product characteristic (disposable medical
device) with risk of MAJOR.
• Per local SOP, to validate a characteristic that could have an effect
on functionality (MAJOR risk), the protection required is
– Performance Level: LTPD0.05 =1%
– Confidence Level (1 – β = .95) or 95%
• To determine BEST Sampling plan, SOP states to estimate AQL:
– Variables data: An estimated AQL may be determined by
estimated process Ppk.
– Attributes data: An estimated AQL may be determined from
history or estimated from experimental runs.
• Engineer will use sampling plan tables in local SOP to determine
sample size and acceptance criteria for validation
Exercise
41
J.L. Schroeder , 3M, June 2015
• Variables data
• Disposable medical device with risk of MAJOR.
• Experimentation determined estimated Ppk for CQA of 1.26
• SOP requires Performance Level of LTPD0.05 =1%
• Engineer goes to LTPD0.05 =1% sampling plan tables to
determine sample size and acceptance criteria
Exercise
Sampling Plan AQL LTPD 0.05
n=15, Ppk=1.17 0.00017% (Ppk=1.55) 1% (Ppk=0.78)
n=20, Ppk=1.10 0.0012% (Ppk=1.41) 1% (Ppk=0.78)
n=30, Ppk=1.02 0.008% (Ppk=1.26) 1% (Ppk=0.78)
Sample Size &Ppk to pass plan
Ppk value that will fail
Process Ppk estimate (accept 95% of time)
Resource: Dr. Wayne Taylor Validation
Sampling Plan Class - 2008
J.L. Schroeder , 3M, June 2015
LTPD = 1%
Attribute Plans with 90% Confidence Attribute Plans with 95% Confidence
Type Parameters AQL LTPD 0.1 Type Parameters AQL LTPD 0.05
Single n=230, a=0 0.02% 1% Single n=300, a=0 0.02% 1%
Single n=390, a=1 0.09% 1% Single n=470, a=1 0.08% 1%
Double n1=250, a1=0, r1=2, n2=400, a2=2 0.11% 1% Double n1=325, a1=0, r1=2, n2=400, a2=2 0.09% 1%
Single n=530, a=2 0.15% 1% Single n=630, a=2 0.13% 1%
Double n1=250, a1=0, r1=3, n2=560, a2=3 0.18% 1% Double n1=325, a1=0, r1=3, n2=580, a2=3 0.15% 1%
Single n=670, a=3 0.20% 1% Single n=770, a=3 0.18% 1%
Double n1=250, a1=0, r1=3, n2=720, a2=4 0.21% 1% Double n1=325, a1=0, r1=3, n2=720, a2=4 0.18% 1%
Variables – 1-sided – 95% Confidence Variables – 2-sided – 95% Confidence
Parameters AQL LTPD 0.05 Parameters AQL LTPD 0.05
n=15, Ppk=1.17 0.00017% (Ppk=1.55) 1% (Ppk=0.78) n=15, Ppk=1.17, Pp=1.17 0.00016% (Ppk=1.55) 1% (Ppk=0.78)
n=20, Ppk=1.10 0.0012% (Ppk=1.41) 1% (Ppk=0.78) n=20, Ppk=1.11, Pp=1.13 0.001% (Ppk=1.42) 1% (Ppk=0.78)
n=30, Ppk=1.02 0.008% (Ppk=1.26) 1% (Ppk=0.78) n=30, Ppk=1.03, Pp=1.07 0.007% (Ppk=1.27) 1% (Ppk=0.78)
n=40, Ppk=0.98 0.02% (Ppk=1.18) 1% (Ppk=0.78) n=40, Ppk=0.99, Pp=1.04 0.018% (Ppk=1.19) 1% (Ppk=0.78)
n=50, Ppk=0.95 0.04% (Ppk=1.12) 1% (Ppk=0.78) n=50, Ppk=0.96, Pp=1.02 0.033% (Ppk=1.13) 1% (Ppk=0.78)
n=60, Ppk=0.94 0.05% (Ppk=1.10) 1% (Ppk=0.78) n=60, Ppk=0.95, Pp=1.01 0.044% (Ppk=1.11) 1% (Ppk=0.78)
n=80, Ppk=0.91 0.09% (Ppk=1.04) 1% (Ppk=0.78) n=80, Ppk=0.92, Pp=0.99 0.08% (Ppk=1.05) 1% (Ppk=0.78)
n=100, Ppk=0.89 0.13% (Ppk=1.01) 1% (Ppk=0.78) n=100, Ppk=0. 90, Pp=0.97 0.11% (Ppk=1.02) 1% (Ppk=0.78)
Tables Developed from Validated “Sampling Plan Analyzer”
– Version 2.0
Copyright 2001 Taylor Enterprises Inc.
J.L. Schroeder , 3M, June 2015
• Suppose:
– 2-sided Spec
– LTPD.05 = 1%
– Have processwherePpk = 1.28
• What sample size should be selected to provide 95% of passing?
• What is corresponding AQL?
• What confidence statement can be made?
Interactive Exercise
J.L. Schroeder , 3M, June 2015
• Suppose:
– 1-sided Spec
– LTPD.05 = 1%
– Have processwherePpk = 1.05
• What sample size should be selected to provide 95% of passing?
• What is corresponding AQL?
• What confidence statement can be made?
Interactive Exercise
Using Selected Plan in Stage 2
Validation Protocol
J.L. Schroeder , 3M, June 2015 47
• Document Sampling Plan and Analysis Methods in Protocol
• Document PPU work to determine estimated process capability. Ppk should be > 1.0
• Make sure that work has been completed to show that good product can be made at extremes; validate at nominal
• Select Sampling Plan based on AQL or Ppkestimate for variables data
• Document Confidence Statements to meet Validation Objectives.
Document and Execute
J.L. Schroeder , 3M, June 2015
• “Per 95% Confidence Sampling Plan for
LTPD.05 = 1%, the validation will pass for
fill volume if the Ppk is 1.11 or greater.”
• If this validation passes one can state
with 95% confidence that the process for
controlling fill volume is less than 1%
defective.”
49
Document Confidence StatementIn Validation Protocol
J.L. Schroeder , 3M, June 2015 50
Example – PQ Protocol
J.L. Schroeder , 3M, June 2015 51
Example – PQ Protocol
Prod_W
Prod_X
Prod_Y
Prod_Z
All Greater than
Ppk of 1.0
J.L. Schroeder , 3M, June 2015 52
Example – PQ Protocol
53
LTPD = 1%
Attribute Plans with 90% Confidence Attribute Plans with 95% Confidence
Type Parameters AQL LTPD 0.1 Type Parameters AQL LTPD 0.05
Single n=230, a=0 0.02% 1% Single n=300, a=0 0.02% 1%
Single n=390, a=1 0.09% 1% Single n=470, a=1 0.08% 1%
Double n1=250, a1=0, r1=2, n2=400, a2=2 0.11% 1% Double n1=325, a1=0, r1=2, n2=400, a2=2 0.09% 1%
Single n=530, a=2 0.15% 1% Single n=630, a=2 0.13% 1%
Double n1=250, a1=0, r1=3, n2=560, a2=3 0.18% 1% Double n1=325, a1=0, r1=3, n2=580, a2=3 0.15% 1%
Single n=670, a=3 0.20% 1% Single n=770, a=3 0.18% 1%
Double n1=250, a1=0, r1=3, n2=720, a2=4 0.21% 1% Double n1=325, a1=0, r1=3, n2=720, a2=4 0.18% 1%
Variables – 1-sided – 95% Confidence Variables – 2-sided – 95% Confidence
Parameters AQL LTPD 0.05 Parameters AQL LTPD 0.05
n=15, Ppk=1.17 0.00017% (Ppk=1.55) 1% (Ppk=0.78) n=15, Ppk=1.17, Pp=1.17 0.00016% (Ppk=1.55) 1% (Ppk=0.78)
n=20, Ppk=1.10 0.0012% (Ppk=1.41) 1% (Ppk=0.78) n=20, Ppk=1.11, Pp=1.13 0.001% (Ppk=1.42) 1% (Ppk=0.78)
n=30, Ppk=1.02 0.008% (Ppk=1.26) 1% (Ppk=0.78) n=30, Ppk=1.03, Pp=1.07 0.007% (Ppk=1.27) 1% (Ppk=0.78)
n=40, Ppk=0.98 0.02% (Ppk=1.18) 1% (Ppk=0.78) n=40, Ppk=0.99, Pp=1.04 0.018% (Ppk=1.19) 1% (Ppk=0.78)
n=50, Ppk=0.95 0.04% (Ppk=1.12) 1% (Ppk=0.78) n=50, Ppk=0.96, Pp=1.02 0.033% (Ppk=1.13) 1% (Ppk=0.78)
n=60, Ppk=0.94 0.05% (Ppk=1.10) 1% (Ppk=0.78) n=60, Ppk=0.95, Pp=1.01 0.044% (Ppk=1.11) 1% (Ppk=0.78)
n=80, Ppk=0.91 0.09% (Ppk=1.04) 1% (Ppk=0.78) n=80, Ppk=0.92, Pp=0.99 0.08% (Ppk=1.05) 1% (Ppk=0.78)
n=100, Ppk=0.89 0.13% (Ppk=1.01) 1% (Ppk=0.78) n=100, Ppk=0. 90, Pp=0.97 0.11% (Ppk=1.02) 1% (Ppk=0.78)
Tables Developed from Validated “Sampling Plan Analyzer” – Version 2.0
Copyright 2001 Taylor Enterprises Inc.
Interactive Exercise
All
Greater
than
Ppk of 1.0
J.L. Schroeder , 3M, June 2015 54
• Data
• Analysis and Conclusions
–Was acceptance criteria met?
–Did validation pass?
–What confidence statement can be
made if criteria was met?
Results: Validation Report
J.L. Schroeder , 3M, June 2015 55
Example – PQ Report
Prod_W
Prod_X
Prod_Y
Prod_Z
J.L. Schroeder , 3M, June 2015 56
Example – PQ Report
Prod_W
J.L. Schroeder , 3M, June 2015
• Critical to Quality Attribute – Attribute Data
• Validation Plan requires LTPD0.05 = 1% and
95% Confidence Level
• AQL estimate from PPU: 0.09%
• Determine:
– Sample Size?
– Ppk to Pass Validation?
– What confidence statement can be made for
Attribute CQA if validation passes?
Break Out Exercise
J.L. Schroeder , 3M, June 2015
LTPD = 1%
Attribute Plans with 90% Confidence Attribute Plans with 95% Confidence
Type Parameters AQL LTPD 0.1 Type Parameters AQL LTPD 0.05
Single n=230, a=0 0.02% 1% Single n=300, a=0 0.02% 1%
Single n=390, a=1 0.09% 1% Single n=470, a=1 0.08% 1%
Double n1=250, a1=0, r1=2, n2=400, a2=2 0.11% 1% Double n1=325, a1=0, r1=2, n2=400, a2=2 0.09% 1%
Single n=530, a=2 0.15% 1% Single n=630, a=2 0.13% 1%
Double n1=250, a1=0, r1=3, n2=560, a2=3 0.18% 1% Double n1=325, a1=0, r1=3, n2=580, a2=3 0.15% 1%
Single n=670, a=3 0.20% 1% Single n=770, a=3 0.18% 1%
Double n1=250, a1=0, r1=3, n2=720, a2=4 0.21% 1% Double n1=325, a1=0, r1=3, n2=720, a2=4 0.18% 1%
Variables – 1-sided – 95% Confidence Variables – 2-sided – 95% Confidence
Parameters AQL LTPD 0.05 Parameters AQL LTPD 0.05
n=15, Ppk=1.17 0.00017% (Ppk=1.55) 1% (Ppk=0.78) n=15, Ppk=1.17, Pp=1.17 0.00016% (Ppk=1.55) 1% (Ppk=0.78)
n=20, Ppk=1.10 0.0012% (Ppk=1.41) 1% (Ppk=0.78) n=20, Ppk=1.11, Pp=1.13 0.001% (Ppk=1.42) 1% (Ppk=0.78)
n=30, Ppk=1.02 0.008% (Ppk=1.26) 1% (Ppk=0.78) n=30, Ppk=1.03, Pp=1.07 0.007% (Ppk=1.27) 1% (Ppk=0.78)
n=40, Ppk=0.98 0.02% (Ppk=1.18) 1% (Ppk=0.78) n=40, Ppk=0.99, Pp=1.04 0.018% (Ppk=1.19) 1% (Ppk=0.78)
n=50, Ppk=0.95 0.04% (Ppk=1.12) 1% (Ppk=0.78) n=50, Ppk=0.96, Pp=1.02 0.033% (Ppk=1.13) 1% (Ppk=0.78)
n=60, Ppk=0.94 0.05% (Ppk=1.10) 1% (Ppk=0.78) n=60, Ppk=0.95, Pp=1.01 0.044% (Ppk=1.11) 1% (Ppk=0.78)
n=80, Ppk=0.91 0.09% (Ppk=1.04) 1% (Ppk=0.78) n=80, Ppk=0.92, Pp=0.99 0.08% (Ppk=1.05) 1% (Ppk=0.78)
n=100, Ppk=0.89 0.13% (Ppk=1.01) 1% (Ppk=0.78) n=100, Ppk=0. 90, Pp=0.97 0.11% (Ppk=1.02) 1% (Ppk=0.78)
Tables Developed from Validated “Sampling Plan Analyzer”
– Version 2.0
Copyright 2001 Taylor Enterprises Inc.AQL estimate from PPU: 0.09%
J.L. Schroeder , 3M, June 2015
Break Out Exercise
• Critical to Quality Attribute – Variables Data (2-
Sided Specification)
• Validation Plan requires LTPD0.05 = 0.4% and 95%
Confidence Level
• Estimated Ppk : 1.31
• Determine:
• Sample Size?
• Ppk to Pass Validation?
• What confidence statement can be made for Variables
CQA if validation passes?
60Estimated Ppk : 1.31
J.L. Schroeder , 3M, June 2015 61
Questions?
J.L. Schroeder , 3M, June 2015 62
Jacalyn L. Schroeder – 3M Company
Title: Quality Engineering Specialist; MS
Applied Statistics 2013
E-mail: [email protected]
Work Phone: 605-696-1355
Contact Information
J.L. Schroeder , 3M, June 2015 63
1. Dr. Wayne A. Taylor, “Guide to Acceptance Sampling”, version 1, www.variation.com, Taylor Enterprises,Inc. Note: Version 2 of new book 2014-2015.
2. GHTF/SG3/N99-10:2004 (Edition 2) , “Quality Management Systems - Process Validation Guidance”, January 2004
3. Validation Sampling Plan Course, Wayne Taylor, March 2008
4. Vladimir, Veselov, Helen Roytman, Lori Alquier, “Medical Device Regulations for Process Validation: Review of FDA, GHTF, and GAMP Requirements”, Journal of Validation Technology, spring 2012
References
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