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Statistical Process Control(SPC)
Quality Control (QC)Quality Control (QC)
Control – the activity of ensuring conformance to requirements and taking corrective action when necessary to correct problemsImportance
Daily management of processesPrerequisite to longer-term improvements
Control – the activity of ensuring conformance to requirements and taking corrective action when necessary to correct problemsImportance
Daily management of processesPrerequisite to longer-term improvements
Designing the QC SystemDesigning the QC System
Quality Policy and Quality ManualContract management, design control and purchasingProcess control, inspection and testingCorrective action and continual improvementControlling inspection, measuring and test equipment (metrology, measurement system analysis and calibration)Records, documentation and audits
Quality Policy and Quality ManualContract management, design control and purchasingProcess control, inspection and testingCorrective action and continual improvementControlling inspection, measuring and test equipment (metrology, measurement system analysis and calibration)Records, documentation and audits
Example of QC: HACCP SystemExample of QC: HACCP System1. Hazard analysis2. Critical control points3. Preventive measures with critical
limits for each control point4. Procedures to monitor the critical
control points5. Corrective actions when critical
limits are not met6. Verification procedures7. Effective record keeping and
documentation
1. Hazard analysis2. Critical control points3. Preventive measures with critical
limits for each control point4. Procedures to monitor the critical
control points5. Corrective actions when critical
limits are not met6. Verification procedures7. Effective record keeping and
documentation
5
Inspection/Testing Points
Receiving inspectionIn-process inspectionFinal inspection
6
Receiving Inspection
Spot check procedures100 percent inspectionAcceptance sampling
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Acceptance SamplingLot received for inspection
Sample selected and analyzed
Results compared with acceptance criteria
Accept the lot
Send to productionor to customer
Reject the lot
Decide on disposition
Pros and Cons of Acceptance Sampling
Pros and Cons of Acceptance SamplingArguments for:
Provides an assessment of riskInexpensive and suited for destructive testingRequires less time than other approachesRequires less handlingReduces inspector fatigue
Arguments for:Provides an assessment of riskInexpensive and suited for destructive testingRequires less time than other approachesRequires less handlingReduces inspector fatigue
Arguments against:Does not make sense for stable processesOnly detects poor quality; does not help to prevent itIs non-value-addedDoes not help suppliers improve
Arguments against:Does not make sense for stable processesOnly detects poor quality; does not help to prevent itIs non-value-addedDoes not help suppliers improve
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In-Process Inspection
What to inspect?Key quality characteristics that are related to cost or quality (customer requirements)
Where to inspect?Key processes, especially high-cost and value-added
How much to inspect?All, nothing, or a sample
10
Economic Model
C1 = cost of inspection and removal of nonconforming item
C2 = cost of repairp = true fraction nonconforming
Breakeven Analysis: p*C2 = C1
If p > C1 / C2 , use 100% inspection
If p < C1 / C2 , do nothing
Human Factors in Inspection
complexitydefect raterepeated inspectionsinspection rate
Inspection should never be a means of assuring quality. The purpose of inspection should be to gather information to understand and improve the processes that produce products and services.
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Gauges and Measuring InstrumentsVariable gaugesFixed gaugesCoordinate measuring machineVision systems
Examples of GaugesExamples of Gauges
Metrology - Science of Measurement
Accuracy - closeness of agreement between an observed value and a standardPrecision - closeness of agreement between randomly selected individual measurements
Repeatability and Reproducibility
Repeatability and Reproducibility
Repeatability (equipment variation) – variation in multiple measurements by an individual using the same instrument. Reproducibility (operator variation) -variation in the same measuring instrument used by different individuals
Repeatability (equipment variation) – variation in multiple measurements by an individual using the same instrument. Reproducibility (operator variation) -variation in the same measuring instrument used by different individuals
Repeatability and Reproducibility Studies
Repeatability and Reproducibility Studies
Quantify and evaluate the capability of a measurement system
Select m operators and n partsCalibrate the measuring instrumentRandomly measure each part by each operator for r trialsCompute key statistics to quantify repeatability and reproducibility
Quantify and evaluate the capability of a measurement system
Select m operators and n partsCalibrate the measuring instrumentRandomly measure each part by each operator for r trialsCompute key statistics to quantify repeatability and reproducibility
Reliability and Reproducibility Studies(2)
Reliability and Reproducibility Studies(2)
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Reliability and Reproducibility Studies(3)
Reliability and Reproducibility Studies(3)
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R&R ConstantsR&R Constants
2.082.302.703.65K2
5432Number of Operators
2.212.503.054.56K1
5432Number of Trials
R&R EvaluationR&R Evaluation
Under 10% error - OK10-30% error - may be OKover 30% error - unacceptable
Under 10% error - OK10-30% error - may be OKover 30% error - unacceptable
R&R ExampleR&R Example
R&R Study is to be conducted on a gauge being used to measure the thickness of a gasket having specification of 0.50 to 1.00 mm. We have three operators, each taking measurement on 10 parts in 2 separate trials.
R&R Study is to be conducted on a gauge being used to measure the thickness of a gasket having specification of 0.50 to 1.00 mm. We have three operators, each taking measurement on 10 parts in 2 separate trials.
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CalibrationCalibration
Calibration - comparing a measurement device or system to one having a known relationship to national standardsTraceability to national standards maintained by NIST, National Institute of Standards and Technology
Calibration - comparing a measurement device or system to one having a known relationship to national standardsTraceability to national standards maintained by NIST, National Institute of Standards and Technology
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Statistical Process Control (SPC)
A methodology for monitoring a process to identify special causes of variation and signal the need to take corrective action when appropriateSPC relies on control charts
Common Causes
Special Causes
Histograms do not take into account changes over time.
Control charts can tell us when a process changes
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Control Chart Applications
Establish state of statistical controlMonitor a process and signal when it goes out of controlDetermine process capability
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Commonly Used Control Charts
Variables datax-bar and R-chartsx-bar and s-chartsCharts for individuals (x-charts)
Attribute dataFor “defectives” (p-chart, np-chart)For “defects” (c-chart, u-chart)
Developing Control ChartsDeveloping Control Charts
1. PrepareChoose measurementDetermine how to collect data, sample size, and frequency of samplingSet up an initial control chart
2. Collect DataRecord dataCalculate appropriate statisticsPlot statistics on chart
1. PrepareChoose measurementDetermine how to collect data, sample size, and frequency of samplingSet up an initial control chart
2. Collect DataRecord dataCalculate appropriate statisticsPlot statistics on chart
Next StepsNext Steps
3. Determine trial control limitsCenter line (process average)Compute UCL, LCL
4. Analyze and interpret resultsDetermine if in controlEliminate out-of-control pointsRecompute control limits as necessary
3. Determine trial control limitsCenter line (process average)Compute UCL, LCL
4. Analyze and interpret resultsDetermine if in controlEliminate out-of-control pointsRecompute control limits as necessary
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Typical Out-of-Control Patterns
Point outside control limitsSudden shift in process averageCyclesTrendsHugging the center lineHugging the control limitsInstability
Shift in Process AverageShift in Process Average
Identifying Potential ShiftsIdentifying Potential Shifts
CyclesCycles
TrendTrend
Final StepsFinal Steps
5. Use as a problem-solving tool
Continue to collect and plot dataTake corrective action when necessary
6. Compute process capability
5. Use as a problem-solving tool
Continue to collect and plot dataTake corrective action when necessary
6. Compute process capability
Process CapabilityProcess Capability
Capability IndicesCapability Indices
mmmmmm
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Process Capability (2)Process Capability (2)
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Capability Versus Control
Control
Capability
Capable
Not Capable
In Control Out of Control
IDEAL
Process Capability Calculations
Process Capability Calculations
Excel Template Excel Template
Special Variables Control ChartsSpecial Variables Control Charts
x-bar and s chartsx-chart for individualsx-bar and s chartsx-chart for individuals
Charts for AttributesCharts for AttributesFraction nonconforming (p-chart)
Fixed sample sizeVariable sample size
np-chart for number nonconforming
Charts for defectsc-chartu-chart
Fraction nonconforming (p-chart)Fixed sample sizeVariable sample size
np-chart for number nonconforming
Charts for defectsc-chartu-chart
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Control Chart SelectionQuality Characteristic
variable attribute
n>1?
n>=10 or computer?
x and MRno
yes
x and s
x and Rno
yes
defective defect
constantsamplesize?
p-chart withvariable samplesize
no
p ornp
yes constantsampling
unit?
c u
yes no
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Control Chart Design Issues
Basis for samplingSample sizeFrequency of samplingLocation of control limits
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Pre-Control
nominalvalue
Green Zone
Yellow Zones
RedZone
RedZone
LTL UTL
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SPC Implementation Requirements
Top management commitmentProject championInitial workable projectEmployee education and trainingAccurate measurement system
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