A measurement systems analysis (MSA) is a thorough assessment of a measurement process, and typically includes a specially designed experiment that seeks to identify the components of variation in that measurement process.  If there are errors in our measurement system we will be making decisions based on incorrect data. We could be making incorrect decisions or producing non-conforming parts.  A properly planned and executed Measurement System Analysis (MSA) can help build a strong foundation for any data based decision making process. A measurement systems analysis considers the following: Selecting the correct measurement and approach Assessing the measuring device Assessing procedures and operators Assessing any measurement interactions Calculating the measurement uncertainty of individual measurement devices and/or measurement systems Common tools and techniques of measurement systems analysis include :- Calibration , Gage R&R , ATA /RTR , ANOVA , Calibration Requirement Alignment ATA –Audit the Auditor (RTR – Review the Reviewer) – name itself defines the check process for the auditor 1. QL(Quality Lead) to Re Audit the transaction audited by Quality Specialist Within 48 hrs of monitoring. 2. QL to track & publish variance report 3. Both Overall & Parameter Wise Variance is calculated 4. Any Variance >5% ( as defined in process ) should be documented & Should Reaudit another call within 72 Hrs 5. This should be weekly activity by TL's & below is the tracker Gage repeatability and reproducibility (GR&R) is defined as the process used to evaluate a gauging instrument’s accuracy by ensuring its measurements are repeatable and reproducible. The process includes taking a series of measurements to certify that the output is the same value as the input, and that the same measurements are obtained under the same operating conditions over a set duration. Standard GR&R Expanded GR&R Actual Process VariationMeasurement Variation Accuracy and Precision Accuracy: Precision: Linearity: Stability: Gage R & R for Continuous Data X Bar R Method Typically used in automobile industry Extreme values affect the method Short & Long Method Short Method does not measure operator and equipment variability separately Long method measures operator and equipment variability separately ANOVA Method Measures operator & equipment variability separately as well as combined effect of operator & parts More effective when extreme value are present Most tedious to perform manual calculations Analyzing Gage R&R Results R&R less than 10%–Measurement System “acceptable R&R 10% to 30%–May be acceptable–make decision based on classification of Characteristic , Application, Customer Input, etc. R&R over 30%–Not acceptable. Find problem, re-visit the Fishbone Diagram, remove Root Causes Bias Stability Linearity Repeatability The average of multiple measurements of an event are equal to the true value There is little variation in repeated measurements of the same

1. Quality Journey by Nilesh Jajoo
Quality Journey
Measurement System Analysis

2. Quality Journey by Nilesh Jajoo
Introduction to MSA
A measurement systems analysis (MSA) is a thorough assessment of a measurement process, and typically includes a
specially designed experiment that seeks to identify the components of variation in that measurement process.
If there are errors in our measurement system we will be making decisions based on incorrect data. We could be making
incorrect decisions or producing non-conforming parts.
A properly planned and executed Measurement System Analysis (MSA) can help build a strong foundation for any data based
decision making process.
A measurement systems analysis considers the following:
Selecting the correct measurement and approach
Assessing the measuring device
Assessing procedures and operators
Assessing any measurement interactions
Calculating the measurement uncertainty of individual measurement devices and/or measurement systems
Common tools and techniques of measurement systems analysis include :-
Calibration , Gage R&R , ATA /RTR , ANOVA ,

3. Quality Journey by Nilesh Jajoo
Calibration
Calibration is one of the primary processes used to maintain instrument /Measurement system accuracy . Its Process of
configuring process/instrument to provide result for sample within a acceptable range .
Eliminating or Minimizing factors that cause inaccurate measurement is a fundamental aspect of Calibration Process
Calibration may be required for the following reasons:
-- a new instrument/ new auditor
-- change in the instrument / change in the defined legend
-- moving from one location to another location
-- when a specified time period has elapsed
-- before and/or after a critical measurement
-- change in the process

4. Quality Journey by Nilesh Jajoo
Calibration Requirement
Alignment
Consistency
Clarity
Improvement
Feedback
Fairness
CALIBRATION
-- Build Calibration Process
-- Establish Baseline
-- Identify a Facilitator
( Master Calibrator)
-- Implement Agent Self
Scoring
-- Put the Data to work (Type
of Calibration Variance
calculation)
-- Perform Call Calibration
Regularly
There are three basic ways to approach this.
First, you could have reviewers review calls separately and then discuss them together.
Second, you could have reviewers review and discuss calls together.
Third,, you could have reviewers and agents come together to review and discuss calls.
Your baseline is how much your company allows for differences in reviewer ratings. The
average across call calibration for QA is about 5% to allow for minor fluctuations without
missing the big discrepancies..
Call calibration sessions, it’s time to decide what to do with the data you have. Don’t just
file it away or you’ll never get the benefits of the work you’re putting into this process.
The data gives you a chance to review and refine your process and give feedback to the
reviewers themselves. It’s also a great tool to help you refine your call QA scorecard.
The most important thing is that you use the results to make improvements
1) Overall Scores Variance 2) Parameter Wise Variance

5. Quality Journey by Nilesh Jajoo
Sample Audit Sheet 1 Weightage
Master
Calibrator
Participan
t A
Participan
t B
Call
Opening
Opened the call without dead air (<5 s) 10 Yes Yes Yes
Greeted the customer 5 No Yes No
Comprehen
sion
Understood the purpose of call (Customer query identification) 5 Yes Yes No
Procured the relevant information from customer (Probing skills
demonstrated by the associate)
5 Yes No Yes
Verification Accurate and Complete Verification 5 Yes Yes Yes
Resolution
Accurate Resolution 10 Yes Yes Yes
Completeness of Resolution 10 Yes Yes Yes
Clear Explanations/ Avoiding usage of Jargon 5 Yes Yes Yes
Ability of an agent to handle objection 10 No No No
Communica
tion Skills
Usage of courteous language, Acknowledgement 10 NA No NA
Not Talking over the customer, Pace of speech, Dead air 10 Yes Yes Yes
Attentive Listening 5 Yes Yes Yes
Call Closing
&
Documenta
tion
Checked the Caller for any other query 5 Yes Yes No
Accurate Non SR Tagging 5 Yes Yes Yes
100 85 75 75
Method 1 10 10
Method 2
Total
Opportunity
14 3 2
21.43% 14.29%
Calibration Variance
Method 1:-
Overall Variance -- Overall Quality
scores given my Master calibrator is 85
and Participant A is 75 and Participant
B is 75 -- Variance of 10%
Method 2:-
Parameter wise variance is marking
process – Total Opportunity / audit is
14 ( parameter )
Participant A has the variance on 3
parameter 21% variance
Participant B has the variance of on 2
parameter , 14% variance
Method 2 is the Most Preferred/
suggested

6. Quality Journey by Nilesh Jajoo
ATA/RTR
ATA –Audit the Auditor (RTR – Review the Reviewer) – name itself defines the check process for the auditor
1. QL(Quality Lead) to Re Audit the transaction audited by Quality Specialist Within 48 hrs of monitoring.
2. QL to track & publish variance report
3. Both Overall & Parameter Wise Variance is calculated
4. Any Variance >5% ( as defined in process ) should be documented & Should Reaudit another call within 72 Hrs
5. This should be weekly activity by TL's & below is the tracker
Audit Process Is Followed as
Defined as per Process
Defined Sampling Process is
adhered
Feedback Opportunity for
auditor
Compliance Check on the Audit
process followed
Value addition and improvement
opportunity
Governance around the
Transactional Audit Process

7. Quality Journey by Nilesh Jajoo
Gage R&R
Gage repeatability and reproducibility (GR&R) is defined as the process used to evaluate a gauging instrument’s accuracy by
ensuring its measurements are repeatable and reproducible. The process includes taking a series of measurements to certify
that the output is the same value as the input, and that the same measurements are obtained under the same operating
conditions over a set duration.
Repeatability Reproducibility
Transaction
Transaction
• Gage repeatability is a measure of how consistently the same
person (or system) measures the same event over time using
the same measurement system.
• To find this value, we record how the same operator or
system repeatedly measures the same event with the same
measurement system.
• Since the event does not change, any change in the
measurements must be due to variation in the measurement
process.
• Gage reproducibility is a measure of how consistently
several operators or measurement systems measure the same
event over time.
• To find this value, we have several people or systems
repeatedly measure the same event. We then look for
differences in the results between the people or systems.

8. Quality Journey by Nilesh Jajoo
Measurement System Analysis–Objectives
• Recognize that observed variation of a product/process includes the true variation of the product/process & the variation due to the
measurement system
• Identify & describe possible sources of variation in a measurement process
• Describe the importance of a validated measurement system
• Describe the terms precision, accuracy & resolution in relation to MSA
• Use appropriate tools to validate measurement system, analyze, and interpret results
--- Gage R&R for continuous data
--- Attribute R&R for discrete data
Why is MSA important?
• Data is only as good as the process that MSA identifies how much variation is present in the measurement process. Understanding
measurement variation is necessary for identifying “true” process variation and maximizing true Y improvements.
• Without MSA, you run the risk of making decisions based on an inaccurate picture of your MSA helps direct efforts aimed at decreasing
measurement variation.
• Excessive measurement variation distorts our understanding of what the customer feels

9. Quality Journey by Nilesh Jajoo
Gage R&R
Standard GR&R
Gage
Variation(repeatability )
Variation Due to Measurement
Procedure (reproducibility)
Operator to Operator
variation
Operator to part variation
Expanded GR&R
Gage
Variation(repeatability )
Variation Due to
Measurement Procedure
(reproducibility)
Within Gage Variation
Gage to Gage Variation
Part to Gage Variation
Operator to Operator
Variation
Operator to parts
Variation
Operator to Gage
Variation

10. Quality Journey by Nilesh Jajoo
Measurement system analysis
Observed Process Variation
Actual Process
Variation
Measurement
Variation
Variation
due to
Operators
Variation
due to
Gage
Reproducibility
Bias Stability Linearity Repeatability
To address actual Process Variability , the variation due to the Measurement System must first be identified & separated from that of the
Process
Tools To be used for MSA
Continuous Gage R&R,
Test/Retest,
Attribute R&R

11. Quality Journey by Nilesh Jajoo
Accuracy and Precision
Measurement System Error
Accuracy Precision
Bias Stability Linearity Repeatability Reproducibility
Good measurement systems have the
following characteristics…
Accuracy:
The average of multiple
measurements of an event are
equal to the true value
Stability:
Linearity:
Precision:
The measurement system
maintains its performance over
time
The measurement system
maintains its performance over a
range of events
There is little variation in
repeated measurements of the
same event

12. Quality Journey by Nilesh Jajoo
Prevision v/s Accuracy

13. Quality Journey by Nilesh Jajoo
Gage R & R for Continuous Data
X Bar R Method
–Typically used in automobile industry
–Extreme values affect the method
–Short & Long Method
• Short Method does not measure operator and equipment variability separately
• Long method measures operator and equipment variability separately
ANOVA Method
• Measures operator & equipment variability separately as well as combined effect of operator & parts
• More effective when extreme value are present
• Most tedious to perform manual calculations

14. Quality Journey by Nilesh Jajoo
Gage R and R ANOVA Method: Example

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Gage R and R ANOVA Method: Example
Two-Way ANOVA Table With Interaction
Source DF SS MS F P
Call Number 2 592.667 296.333 205.154 0.000
Operator Num 2 6.889 3.444 2.385 0.208
Call Number * Operator Num 4 5.778 1.444 7.800 0.001
Repeatability 18 3.333 0.185
Total 26 608.667
Gage R&R
%Contribution
Source VarComp (of VarComp)
Total Gage R&R 0.8272 2.46
Repeatability 0.1852 0.55
Reproducibility 0.6420 1.91
Operator Num 0.2222 0.66
Operator Num*Call Number 0.4198 1.25
Part-To-Part 32.7654 97.54
Total Variation 33.5926 100.00
Study Var %Study Var
Source StdDev (SD) (6 * SD) (%SV)
Total Gage R&R 0.90948 5.4569 15.69
Repeatability 0.43033 2.5820 7.42
Reproducibility 0.80123 4.8074 13.82
Operator Num 0.47140 2.8284 8.13
Operator Num*Call Number 0.64788 3.8873 11.18
Part-To-Part 5.72411 34.3447 98.76
Total Variation 5.79591 34.7755 100.00
Number of Distinct Categories = 8
The Total Gage R&R value under %
contribution shows the measurement
system error for this test, in this case 2.46%
of the variation in the data comes from the
measurement system. We like it to be less
than 10%, so this measurement system is
acceptable.
The remaining variation comes from Part-to-
Part variation. In this study, 97.54% of the
variation was due to variation in
performance of the actual call cycle time –
true process variation.
Rules of Thumb–Acceptable Ranges
Analyzing Gage R&R Results
• R&R less than 10%–Measurement System
“acceptable
• R&R 10% to 30%–May be acceptable–make
decision based on classification of Characteristic ,
Application, Customer Input, etc.
• R&R over 30%–Not acceptable. Find problem, re-
visit the Fishbone Diagram, remove Root Causes

16. Quality Journey by Nilesh Jajoo