SlideShare une entreprise Scribd logo
1  sur  17
◦ Introduce the basic concepts of an attribute
measurement systems analysis (MSA).
◦ Understand operational definitions for inspection and
evaluation.
◦ Define attribute MSA terms.
◦ Define Procedure for conducting attribute MSA
◦ Demonstrate trial for conducting attribute MSA
2
 A measurement systems analysis is an evaluation
of the efficacy of a measurement system.
 The purpose of Measurement System Analysis is
to qualify a measurement system for use by
quantifying its accuracy, precision, and stability.
 It is applicable to both continuous and attribute
data.
 Most problematic
measurement system
issues come from
measuring attribute data
in terms that rely on
human judgment such
as good/bad, pass/fail,
etc. This is because it is
very difficult for all
testers to apply the same
operational definition of
what is “good” and what
is “bad.”
 When, we are not getting any measurement values then
the tool used for this kind of analysis is called Attribute
gage R&R.
 The R&R stands for repeatability and reproducibility.
 Repeatability : is the variation in measurements obtained
with one measurement instrument when used several
times by one appraiser while measuring the identical
characteristic on the same part.
 Reproducibility : It is defined as the variation in the
average of the measurements made by different
appraisers using the same measuring instrument when
measuring the identical characteristic on the same part.
 .
 To evaluate product features and make
accept/reject decisions.
 • Mandatory criteria for establishment and
use of operational definitions include:
 A) Criteria that can be applied to an object
(or a group of objects) which precisely
describes what is acceptable and
unacceptable.
 B) A written description of the process for
collecting data, including the method in
which accept/reject decisions will be made.
 C) Review of the accept/reject criteria
with people who will do the inspections to
ensure that the requirements are
understood.
 Select at least 20 parts to be evaluated during the study.
 • At least 5 of the parts should be defective in some way. If larger
sample sizes are used, include at least 25% defective parts.
 • Care should be taken when selecting defective parts – If possible
select parts which are slightly beyond the specification limits or
acceptance standards. Label each part with proper identification.
 • Three inspectors will evaluate each part thrice (Three trials).
 • A fourth person should record the data. Note down the observations
in the form of 1 or 0, 1 is OK, 0 is not ok.
 The order of inspections should be randomized after each group of
inspections to minimize the risk that the inspector will remember
previous accept/reject decisions. The inspectors must work
independently and cannot discuss their accept/reject decisions with
each other.
Appraiser A A A B B B C C C
Trials i ii iii i ii iii i ii iii
1 1 1 1 1 1 1 1 1 1
2 1 1 1 1 1 1 1 1 1
3 1 1 1 1 1 1 1 1 1
4 0 0 0 0 0 0 0 0 0
5 1 1 1 1 1 1 1 1 1
6 1 1 1 1 1 1 1 1 1
7 1 1 1 1 1 1 1 1 1
8 1 1 1 1 1 1 1 1 1
9 1 1 1 1 1 1 1 1 1
10 1 1 1 1 1 1 1 1 1
11 1 1 1 1 1 1 1 1 1
12 1 1 1 1 1 1 1 1 1
13 1 1 1 1 1 1 1 1 1
14 1 1 1 1 1 1 1 1 1
15 1 1 1 1 1 1 1 1 1
16 1 1 1 1 1 1 1 1 1
17 1 1 1 1 1 1 1 1 1
18 1 1 1 1 1 1 1 1 1
19 1 1 1 1 1 1 1 1 1
20 1 1 1 1 1 1 1 1 1
• The data recorder may use a table similar to the one given below.
0 Not Ok
1 Ok
 • Type 1 Errors: when a good part is rejected.
 • Type 1 errors increase ‐
 • Manufacturing costs. Incremental labor and material expenses
are necessary to re – inspect, repair, or dispose the suspect parts.
 • Type 1 errors are also called as “Producer’s Risk” or alpha
errors.
 • Type 2 Errors: when a bad part is accepted.
 • Type 2 errors may occur
 • Perhaps the inspector was poorly trained or rushed through the
inspection and inadvertently overlooked a Small defect on the
part.
 • When Type 2 errors occur, defects slip through the containment
net and are shipped to the customer.
 • Because Type 2 errors put the customer at risk of receiving
defective parts; customer may raised the complaint!
 • Type 2 errors are sometimes called as “Consumer’s Risk”.
 • Type 2 errors are also called as “beta” errors.
What is effectiveness?
The effectiveness of an inspection process is correct
call!
◦ Correct Call (Cc):- The number of times of
which the operator (s) identify a good sample
as a good one.
Effectiveness = number of correct evaluations
number of total opportunities
What is False Alarm?
 False Alarm (Fa) – The number of times of
which the operator (s) identify a good sample
as a bad one.
The probability of a false alarm, also known as
Type I error or producer’s risk, is given by:
Fa (False Alarm) = number of false alarms
number of non-defective items
What is Miss rate?
A miss is a defective item that is classified as non-
defective.
Miss rate (Mr) – The number of times of which
the operators identify a bad sample as a good
one.
The probability of a miss, also known as Type II
error or consumer’s risk, is given by:
Mr (Miss rate) = number of misses
number of defective items
 Acceptability criteria:
If all measurement results agree, the gage is
acceptable. If the measurement results do not
agree, the gage can not be accepted, it must be
improved and re-evaluated.
EFFECTIVENESS (< 80% - Not Acceptable)
MISS - RATE ( > 5% - Not Acceptable )
FALSE ALARM RATE( > 10% -Not Acceptable)
 What could have caused the poor agreement?
 What should be done to improve the measurement
system?
 What should be done to improve consistency?
 Do the Brain
Storming!
 If any of the decisions disagree, the
measurement system may need improvement.
 Improvement actions include:
 • Reworking the gage,
 • Re‐training the inspectors,
 • Clarifying the accept/reject criteria,
 • Adding more lighting
 After implementing the improvement actions,
repeat the study. If the error cannot be
eliminated,
 • Must take appropriate corrective actions, such
as switching to a new measurement system,
adding redundant inspections, or conducting a
more extensive study.
Exercise

Contenu connexe

Tendances

Measurement System Analysis (MSA)
Measurement System Analysis (MSA)Measurement System Analysis (MSA)
Measurement System Analysis (MSA)Ram Kumar
 
Iqc incoming quality control
Iqc incoming quality controlIqc incoming quality control
Iqc incoming quality controlAshutoshKumar1262
 
Quality Management System
Quality Management System Quality Management System
Quality Management System Prasenjit Mitra
 
Corrective Action And Root Cause Analysis
Corrective Action And Root Cause AnalysisCorrective Action And Root Cause Analysis
Corrective Action And Root Cause Analysissjlines
 
02training material for msa
02training material for msa02training material for msa
02training material for msa營松 林
 
PDCA Plan Do Check Act
PDCA Plan Do Check ActPDCA Plan Do Check Act
PDCA Plan Do Check ActAnwarrChaudary
 
Corrective action preventive action (capa)
Corrective action preventive action (capa)Corrective action preventive action (capa)
Corrective action preventive action (capa)tanvikumbhar
 
Corrective & Preventive Action
Corrective & Preventive Action Corrective & Preventive Action
Corrective & Preventive Action Praneet Surti
 
Check Sheets
Check SheetsCheck Sheets
Check SheetsCIToolkit
 
MSA presentation
MSA presentationMSA presentation
MSA presentationsanjay deo
 

Tendances (20)

Ppap training ppt
Ppap training   ppt Ppap training   ppt
Ppap training ppt
 
MSA
MSAMSA
MSA
 
Measurement System Analysis (MSA)
Measurement System Analysis (MSA)Measurement System Analysis (MSA)
Measurement System Analysis (MSA)
 
Iqc incoming quality control
Iqc incoming quality controlIqc incoming quality control
Iqc incoming quality control
 
Quality Management System
Quality Management System Quality Management System
Quality Management System
 
Corrective Action And Root Cause Analysis
Corrective Action And Root Cause AnalysisCorrective Action And Root Cause Analysis
Corrective Action And Root Cause Analysis
 
Process and product inspection
Process and product inspectionProcess and product inspection
Process and product inspection
 
ACCEPTANCE SAMPLING
ACCEPTANCE SAMPLINGACCEPTANCE SAMPLING
ACCEPTANCE SAMPLING
 
CONTROL CHARTS
CONTROL CHARTSCONTROL CHARTS
CONTROL CHARTS
 
02training material for msa
02training material for msa02training material for msa
02training material for msa
 
PDCA Plan Do Check Act
PDCA Plan Do Check ActPDCA Plan Do Check Act
PDCA Plan Do Check Act
 
Corrective action preventive action (capa)
Corrective action preventive action (capa)Corrective action preventive action (capa)
Corrective action preventive action (capa)
 
MSA (GR&R)
MSA (GR&R)MSA (GR&R)
MSA (GR&R)
 
MRM - Management Review Meeting Presentation
MRM - Management Review Meeting PresentationMRM - Management Review Meeting Presentation
MRM - Management Review Meeting Presentation
 
ISO 17025.pptx
ISO 17025.pptxISO 17025.pptx
ISO 17025.pptx
 
Corrective & Preventive Action
Corrective & Preventive Action Corrective & Preventive Action
Corrective & Preventive Action
 
Quality inspection presentation
Quality inspection presentationQuality inspection presentation
Quality inspection presentation
 
Check Sheets
Check SheetsCheck Sheets
Check Sheets
 
MSA presentation
MSA presentationMSA presentation
MSA presentation
 
Msa training
Msa trainingMsa training
Msa training
 

Similaire à Attribute measurement analysis

Managing non conformance colonel sri(titto sunny)
Managing non conformance colonel sri(titto sunny)Managing non conformance colonel sri(titto sunny)
Managing non conformance colonel sri(titto sunny)Traum Academy
 
Control charts in statistical quality control
Control charts in statistical quality controlControl charts in statistical quality control
Control charts in statistical quality controlrakheechhibber1971
 
Measurement system analysis
Measurement system analysisMeasurement system analysis
Measurement system analysisTina Arora
 
Statistical Process Control & Operations Management
Statistical Process Control & Operations ManagementStatistical Process Control & Operations Management
Statistical Process Control & Operations Managementajithsrc
 
Managing Quality
Managing QualityManaging Quality
Managing QualityAli BARAN
 
Module_1_Sampling_Plan__AQL_V02_7Sep2018.ppt
Module_1_Sampling_Plan__AQL_V02_7Sep2018.pptModule_1_Sampling_Plan__AQL_V02_7Sep2018.ppt
Module_1_Sampling_Plan__AQL_V02_7Sep2018.pptViet Tran
 
inspection , test and measurement
inspection , test and measurementinspection , test and measurement
inspection , test and measurementtanvikumbhar
 
Final-Audit-Sampling.pdf
Final-Audit-Sampling.pdfFinal-Audit-Sampling.pdf
Final-Audit-Sampling.pdfssuser5945a3
 
FAILURE MODE EFFECT ANALYSIS
FAILURE MODE EFFECT ANALYSISFAILURE MODE EFFECT ANALYSIS
FAILURE MODE EFFECT ANALYSISANOOPA NARAYANAN
 
Dilshod Achilov Gage R&R
Dilshod Achilov Gage R&RDilshod Achilov Gage R&R
Dilshod Achilov Gage R&Rahmad bassiouny
 
Risk Based Supplier quality management
Risk Based Supplier quality managementRisk Based Supplier quality management
Risk Based Supplier quality managementSanjay Dhal , MS, MBA
 
Acceptance sampling
Acceptance samplingAcceptance sampling
Acceptance samplingHassan Habib
 

Similaire à Attribute measurement analysis (20)

Managing non conformance colonel sri(titto sunny)
Managing non conformance colonel sri(titto sunny)Managing non conformance colonel sri(titto sunny)
Managing non conformance colonel sri(titto sunny)
 
Audit sampling
Audit samplingAudit sampling
Audit sampling
 
Samling plan
Samling planSamling plan
Samling plan
 
Control charts in statistical quality control
Control charts in statistical quality controlControl charts in statistical quality control
Control charts in statistical quality control
 
Acceptance Sampling[1]
Acceptance Sampling[1]Acceptance Sampling[1]
Acceptance Sampling[1]
 
Acceptance Sampling[1]
Acceptance Sampling[1]Acceptance Sampling[1]
Acceptance Sampling[1]
 
Measurement system analysis
Measurement system analysisMeasurement system analysis
Measurement system analysis
 
Statistical Process Control & Operations Management
Statistical Process Control & Operations ManagementStatistical Process Control & Operations Management
Statistical Process Control & Operations Management
 
Six sigma
Six sigmaSix sigma
Six sigma
 
Managing Quality
Managing QualityManaging Quality
Managing Quality
 
Module_1_Sampling_Plan__AQL_V02_7Sep2018.ppt
Module_1_Sampling_Plan__AQL_V02_7Sep2018.pptModule_1_Sampling_Plan__AQL_V02_7Sep2018.ppt
Module_1_Sampling_Plan__AQL_V02_7Sep2018.ppt
 
inspection , test and measurement
inspection , test and measurementinspection , test and measurement
inspection , test and measurement
 
Sampling plan
Sampling planSampling plan
Sampling plan
 
Final-Audit-Sampling.pdf
Final-Audit-Sampling.pdfFinal-Audit-Sampling.pdf
Final-Audit-Sampling.pdf
 
FAILURE MODE EFFECT ANALYSIS
FAILURE MODE EFFECT ANALYSISFAILURE MODE EFFECT ANALYSIS
FAILURE MODE EFFECT ANALYSIS
 
Dilshod Achilov Gage R&R
Dilshod Achilov Gage R&RDilshod Achilov Gage R&R
Dilshod Achilov Gage R&R
 
Risk Based Supplier quality management
Risk Based Supplier quality managementRisk Based Supplier quality management
Risk Based Supplier quality management
 
Acceptance sampling
Acceptance samplingAcceptance sampling
Acceptance sampling
 
7645006.pptx
7645006.pptx7645006.pptx
7645006.pptx
 
qms
qmsqms
qms
 

Plus de PRASHANT KSHIRSAGAR

Plus de PRASHANT KSHIRSAGAR (9)

Steel Presentation
Steel PresentationSteel Presentation
Steel Presentation
 
7 QC Tools Training
7 QC Tools Training7 QC Tools Training
7 QC Tools Training
 
Spc training
Spc trainingSpc training
Spc training
 
Stainless steel presentation
Stainless steel presentationStainless steel presentation
Stainless steel presentation
 
8D analysis presentation
8D analysis presentation8D analysis presentation
8D analysis presentation
 
Advanced Product Quality Planning presentation
Advanced Product Quality Planning presentationAdvanced Product Quality Planning presentation
Advanced Product Quality Planning presentation
 
Annealing presentation
Annealing presentationAnnealing presentation
Annealing presentation
 
7 QC Tools training presentation
7 QC Tools training presentation7 QC Tools training presentation
7 QC Tools training presentation
 
Stainless steel
Stainless steelStainless steel
Stainless steel
 

Dernier

Hostel management system project report..pdf
Hostel management system project report..pdfHostel management system project report..pdf
Hostel management system project report..pdfKamal Acharya
 
A CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptx
A CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptxA CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptx
A CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptxmaisarahman1
 
kiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadkiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadhamedmustafa094
 
Unleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leapUnleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leapRishantSharmaFr
 
Verification of thevenin's theorem for BEEE Lab (1).pptx
Verification of thevenin's theorem for BEEE Lab (1).pptxVerification of thevenin's theorem for BEEE Lab (1).pptx
Verification of thevenin's theorem for BEEE Lab (1).pptxchumtiyababu
 
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXssuser89054b
 
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments""Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"mphochane1998
 
Thermal Engineering Unit - I & II . ppt
Thermal Engineering  Unit - I & II . pptThermal Engineering  Unit - I & II . ppt
Thermal Engineering Unit - I & II . pptDineshKumar4165
 
Thermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptThermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptDineshKumar4165
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Arindam Chakraborty, Ph.D., P.E. (CA, TX)
 
Hospital management system project report.pdf
Hospital management system project report.pdfHospital management system project report.pdf
Hospital management system project report.pdfKamal Acharya
 
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptxHOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptxSCMS School of Architecture
 
Online food ordering system project report.pdf
Online food ordering system project report.pdfOnline food ordering system project report.pdf
Online food ordering system project report.pdfKamal Acharya
 
A Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna MunicipalityA Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna MunicipalityMorshed Ahmed Rahath
 
data_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfdata_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfJiananWang21
 
Online electricity billing project report..pdf
Online electricity billing project report..pdfOnline electricity billing project report..pdf
Online electricity billing project report..pdfKamal Acharya
 
HAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKAR
HAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKARHAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKAR
HAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKARKOUSTAV SARKAR
 
Employee leave management system project.
Employee leave management system project.Employee leave management system project.
Employee leave management system project.Kamal Acharya
 
DC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equationDC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equationBhangaleSonal
 

Dernier (20)

Hostel management system project report..pdf
Hostel management system project report..pdfHostel management system project report..pdf
Hostel management system project report..pdf
 
A CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptx
A CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptxA CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptx
A CASE STUDY ON CERAMIC INDUSTRY OF BANGLADESH.pptx
 
kiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadkiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal load
 
Unleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leapUnleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leap
 
Verification of thevenin's theorem for BEEE Lab (1).pptx
Verification of thevenin's theorem for BEEE Lab (1).pptxVerification of thevenin's theorem for BEEE Lab (1).pptx
Verification of thevenin's theorem for BEEE Lab (1).pptx
 
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
 
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments""Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"
 
Thermal Engineering Unit - I & II . ppt
Thermal Engineering  Unit - I & II . pptThermal Engineering  Unit - I & II . ppt
Thermal Engineering Unit - I & II . ppt
 
Thermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptThermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.ppt
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
 
Hospital management system project report.pdf
Hospital management system project report.pdfHospital management system project report.pdf
Hospital management system project report.pdf
 
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptxHOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
 
Online food ordering system project report.pdf
Online food ordering system project report.pdfOnline food ordering system project report.pdf
Online food ordering system project report.pdf
 
A Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna MunicipalityA Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna Municipality
 
data_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfdata_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdf
 
Online electricity billing project report..pdf
Online electricity billing project report..pdfOnline electricity billing project report..pdf
Online electricity billing project report..pdf
 
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced LoadsFEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
 
HAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKAR
HAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKARHAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKAR
HAND TOOLS USED AT ELECTRONICS WORK PRESENTED BY KOUSTAV SARKAR
 
Employee leave management system project.
Employee leave management system project.Employee leave management system project.
Employee leave management system project.
 
DC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equationDC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equation
 

Attribute measurement analysis

  • 1.
  • 2. ◦ Introduce the basic concepts of an attribute measurement systems analysis (MSA). ◦ Understand operational definitions for inspection and evaluation. ◦ Define attribute MSA terms. ◦ Define Procedure for conducting attribute MSA ◦ Demonstrate trial for conducting attribute MSA 2
  • 3.  A measurement systems analysis is an evaluation of the efficacy of a measurement system.  The purpose of Measurement System Analysis is to qualify a measurement system for use by quantifying its accuracy, precision, and stability.  It is applicable to both continuous and attribute data.
  • 4.
  • 5.  Most problematic measurement system issues come from measuring attribute data in terms that rely on human judgment such as good/bad, pass/fail, etc. This is because it is very difficult for all testers to apply the same operational definition of what is “good” and what is “bad.”
  • 6.  When, we are not getting any measurement values then the tool used for this kind of analysis is called Attribute gage R&R.  The R&R stands for repeatability and reproducibility.  Repeatability : is the variation in measurements obtained with one measurement instrument when used several times by one appraiser while measuring the identical characteristic on the same part.  Reproducibility : It is defined as the variation in the average of the measurements made by different appraisers using the same measuring instrument when measuring the identical characteristic on the same part.  .
  • 7.  To evaluate product features and make accept/reject decisions.  • Mandatory criteria for establishment and use of operational definitions include:  A) Criteria that can be applied to an object (or a group of objects) which precisely describes what is acceptable and unacceptable.  B) A written description of the process for collecting data, including the method in which accept/reject decisions will be made.  C) Review of the accept/reject criteria with people who will do the inspections to ensure that the requirements are understood.
  • 8.  Select at least 20 parts to be evaluated during the study.  • At least 5 of the parts should be defective in some way. If larger sample sizes are used, include at least 25% defective parts.  • Care should be taken when selecting defective parts – If possible select parts which are slightly beyond the specification limits or acceptance standards. Label each part with proper identification.  • Three inspectors will evaluate each part thrice (Three trials).  • A fourth person should record the data. Note down the observations in the form of 1 or 0, 1 is OK, 0 is not ok.  The order of inspections should be randomized after each group of inspections to minimize the risk that the inspector will remember previous accept/reject decisions. The inspectors must work independently and cannot discuss their accept/reject decisions with each other.
  • 9. Appraiser A A A B B B C C C Trials i ii iii i ii iii i ii iii 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 4 0 0 0 0 0 0 0 0 0 5 1 1 1 1 1 1 1 1 1 6 1 1 1 1 1 1 1 1 1 7 1 1 1 1 1 1 1 1 1 8 1 1 1 1 1 1 1 1 1 9 1 1 1 1 1 1 1 1 1 10 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 12 1 1 1 1 1 1 1 1 1 13 1 1 1 1 1 1 1 1 1 14 1 1 1 1 1 1 1 1 1 15 1 1 1 1 1 1 1 1 1 16 1 1 1 1 1 1 1 1 1 17 1 1 1 1 1 1 1 1 1 18 1 1 1 1 1 1 1 1 1 19 1 1 1 1 1 1 1 1 1 20 1 1 1 1 1 1 1 1 1 • The data recorder may use a table similar to the one given below. 0 Not Ok 1 Ok
  • 10.  • Type 1 Errors: when a good part is rejected.  • Type 1 errors increase ‐  • Manufacturing costs. Incremental labor and material expenses are necessary to re – inspect, repair, or dispose the suspect parts.  • Type 1 errors are also called as “Producer’s Risk” or alpha errors.  • Type 2 Errors: when a bad part is accepted.  • Type 2 errors may occur  • Perhaps the inspector was poorly trained or rushed through the inspection and inadvertently overlooked a Small defect on the part.  • When Type 2 errors occur, defects slip through the containment net and are shipped to the customer.  • Because Type 2 errors put the customer at risk of receiving defective parts; customer may raised the complaint!  • Type 2 errors are sometimes called as “Consumer’s Risk”.  • Type 2 errors are also called as “beta” errors.
  • 11. What is effectiveness? The effectiveness of an inspection process is correct call! ◦ Correct Call (Cc):- The number of times of which the operator (s) identify a good sample as a good one. Effectiveness = number of correct evaluations number of total opportunities
  • 12. What is False Alarm?  False Alarm (Fa) – The number of times of which the operator (s) identify a good sample as a bad one. The probability of a false alarm, also known as Type I error or producer’s risk, is given by: Fa (False Alarm) = number of false alarms number of non-defective items
  • 13. What is Miss rate? A miss is a defective item that is classified as non- defective. Miss rate (Mr) – The number of times of which the operators identify a bad sample as a good one. The probability of a miss, also known as Type II error or consumer’s risk, is given by: Mr (Miss rate) = number of misses number of defective items
  • 14.  Acceptability criteria: If all measurement results agree, the gage is acceptable. If the measurement results do not agree, the gage can not be accepted, it must be improved and re-evaluated. EFFECTIVENESS (< 80% - Not Acceptable) MISS - RATE ( > 5% - Not Acceptable ) FALSE ALARM RATE( > 10% -Not Acceptable)
  • 15.  What could have caused the poor agreement?  What should be done to improve the measurement system?  What should be done to improve consistency?  Do the Brain Storming!
  • 16.  If any of the decisions disagree, the measurement system may need improvement.  Improvement actions include:  • Reworking the gage,  • Re‐training the inspectors,  • Clarifying the accept/reject criteria,  • Adding more lighting  After implementing the improvement actions, repeat the study. If the error cannot be eliminated,  • Must take appropriate corrective actions, such as switching to a new measurement system, adding redundant inspections, or conducting a more extensive study.

Notes de l'éditeur

  1. Given the results of the MSA study, what could have caused the poor agreement? And what should be done to improve the measurement system? The measurement system must be improved and tested again (with another MSA study) to reach at least 90% agreement before the data can be used for base-lining process performance or further analysis.