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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
In association withBW (Ben) Marguglio, LLC
845-265-0123
Statistical Process Control Seminarat
Jireh Semiconductor
Instructor: John Breckline
January 24, 2018
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Topic Agenda
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
8 hoursoverview – what/why, not how
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
John Breckline
Retired but…
Motorola: Auto Electronics, Commercial, Telecom (pagers)
Nokia: MBB / Continuous Improvement Manager
AT&T: MBB – Transactional / Lean Projects
MBB Credentials: Stat-a-Matrix (99) / Nokia (again)
ASQ Certifications: CQE (87), CBB (03), CSQP (17)
Certification Preparation Instructor since 1997
30+ years in Quality Disciplines
– Inspection, Sampling, Data Systems
– SPC, Measurement, Supplier Quality
– Quality Systems Management
– Six Sigma Master Black Belt
Fort Worth TX Mobile: 817-401-0412
email: [email protected]
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Seminar Objectives
To reinforce the concepts and practices of SPC
To bring a fresh perspective of the utilization of SPC
To lay a foundation of statistical thinking as a basisfor effective SPC
To challenge those responsible for SPC to optimizethe use SPC to manage production operations
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Statistical Thinking
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Statistical Thinking Map
DesignFMEA
ProcessFMEA
ProcessControl
DefineCritical
Characteristics
ApprovalPlanning
MeasurementSystemAnalysis
ProcessCapabilityStudies
ProcessImprovement
ControlPlan
ProcessCapable
Yes
No
StatisticalProcessControl
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Statistical Process Control (SPC)
Objectives & Benefits
– To monitor, control, and improve process performanceover time by studying variation and its source.
– Focuses on monitoring and detecting process variation
– Provides ‘on-line’ process feedback and control signals
– Distinguished between common and special causes ofvariation
– Helps improve process to perform consistently andpredictably
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Review:
– Basic ‘rules’ for Out of Control performance:
– Point out of control – why?
– Shifts – why?
– Runs – why?
– Others – why?
30
40
50
60
70
80
90
X=60.2
UCL=87.7
LCL=32.7
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Batch
100
ABC
Application of Control Charts8
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Data Use
Why Collect and Track Data
– Data Information Decision
– Understand – Evaluate – Control – Predict
Objective of Statistical Usage
– Identifying problem areas through trend analysis
– Assisting in identifying and alleviating risk
– Improving the current process
– Preventing problems
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Data Graphics
Data Plotting vs Recording
– Plotting data into a chart is used for visibility andrecognition (easier to understand a visual aid than abunch of numbers
– Recording data is necessary to avoid risks:
• No record of adjustments
• Subtle changes are lost
• Measurement errors are lost
• Plotting errors missed
• Sampling errors missed
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Control Charts
– Line graphs that display a dynamic picture of processbehavior
– Focuses attention on monitoring and detecting processvariation over time
– Used to analyze variation in processes
– Distinguishes special from common causes of variationas a guide to action
Control Charts11
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Common Cause:
– ~85% of all process problems are due tocommon cause variation.
– Common cause variation is predictable
– Special Cause:
– ~15% of all process problems are due tospecial cause variation.
– Special cause variation is unpredictable
Theory of Variation
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Theory of Variation
Common Cause• Always present• Standard practices• Built into the process• Predictable variation
Special Causes• Unpredictable occurrences• Significant variation• Assignable cause
Understand the Difference• Different tools to improve / control each
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
The Sources of Variation
Process/System
Customer Satisfaction
Environment
Measurement
Man
Material
Machine
Methods
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Basic Statistics… a Refresher
Terms Description Symbol
Mean /Average
mathematical center of the sample/population
Median “geographic” center of the sample/population N/A
Range width of distribution (largest – smallest) R
StandardDeviation
“statistical” width of distributionmeasured by “sigma” increments s
Histogram
Normal Curve 4s 3s 2s 1s 0 1s 2s 3s 4s
99.73%
Normal Curve
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
If common causes of variationdominate, the output of a processforms a distribution that is stableand predictable over time.
Common and Special Causes
Time
Prediction
Metric = Lines on Time
If special causes of variation dominate,the output of a process is not stableover time and not predictable.
Time
Prediction
Metric = Lines on Time
?
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Normal Curve – Area Under the Curve
Normal Curve• Accounts for Common Cause variation
average+2*sigma
average-2*sigma
13.60 % 13.60 %
average-3*sigma
average+3*sigma
2.14 %2.14 %
0.13 % 0.13 %
Upper naturallimit (UNL)
Lower naturallimit (LNL)
average average+1*sigma
average-1*sigma
34.13 %34.13 %
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Distributions:
– Not all distributions are Normal
– Exponential Distribution is common for one-sided specs (PPB rates)
– Predictive statistics require Normal Distributions (SPC is predictive)
Basic Statistics… Distributions
Normal Distribution – not perfect Exponential Distribution – Jireh?
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Central Limit Theorem
Concept– The sample mean become normally distributed as sample
size increases– The spread of the sample means are less than the spread
of the individuals of the sample
Value– Non-normal distributions can be assessed using normal
distribution statistics and tools (X-bar-R, etc.)– Most inferential statistical tools assume normality of data
• Confidence Intervals• SPC / Control Charts
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Performance vs. Requirements
Requirements
– Customer Specifications
– Internal Operating Control Levels
– Compare Performance to Requirements
1615141312111098
USLLSL
O
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Taguchi Loss Function
Nominal
Lower SpecificationLimit (LSL)
Upper SpecificationLimit (USL)
Acceptable Product Rejected ProductRejected Product
BestOutput
The LossFunctioninvertednormal
distributioncurve
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
1. _____________________________________________
2. _____________________________________________
3. _____________________________________________
4. _____________________________________________
5. _____________________________________________
Key Learnings22
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Critical Characteristics
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Key Characteristics
What is Important• to End Customer• to Manufacturers• to Jireh Operations• to Supplier Operations
Identifying Characteristics• Design FMEA• Early Supplier Involvement• Process FMEA• White / Black Diamond Designation
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Product:
1. _____________________________________________
2. _____________________________________________
3. _____________________________________________
Process:
1. _____________________________________________
2. _____________________________________________
3. _____________________________________________
4. _____________________________________________
5. _____________________________________________
6. _____________________________________________
Key Characteristics25
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Key Process Characteristics
Measurement Machine Methods
. .
Mother Earth ManMaterials
Measurement Machine Methods
. .
Mother Earth ManMaterials
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Measurement / Process Capability
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Measurement
Measurement Systems Analysis (MSA)• Gage Repeatability & Reproducibility (GR&R)
Variable GR&R• Understand capability of measurement
• Percent of Contribution – Variance• Percent of Study – Std Dev• Percent of Tolerance (P/T Ratio)• Effect of sample selection• <10% acceptable• 10-30% marginal• >30% high risk
Attribute R&R• Understand capability of inspection
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Gage R&R Terms
Repeatability– The ability of a single instrument to generate accurate measurements consistently – same
operator, same part, same time
Reproducibility– The ability of a system to generate accurate measurements consistently – different
operators or times (accuracy/precision)
P/T Ratio– Precision to Tolerance – how much measurement error is related to specification
– Critical to product acceptance & capability studies (decision to Spec)
R&R Contribution– Measurement error related to process / characteristic variation
– Important to process control (SPC) and process improvement (DOE)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Variable Gage R&R
average
Observed =Variability
Observedvalues
total2
ProductVariability
Product Variability
product2 systemtmeasuremen
2+ Measurement Variability
Measurement Variability- Additive -
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Why care about Process Capability?
• Satisfy our customers
• Understand our processes
• Prioritize areas in need of quality improvement (variationreduction) activities
• Verify that process improvements are successful
• Track improvements over time
• Give us information to set realistic tolerances
• Help us identify how to cost products
• Select the best qualified supplier
• We can improve our company Bottom Line
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Process Capability Roadmap
Improve
Improve
Select Characteristic
Study ScopeShort-term - Long-term
MeasurementCapability?
Is ProcessStable?
UnderstandConfidence Interval(based on sample size)
Improve /Transform
Segregate/Understand
ImproveProcess
Is DataNormal?
Maintain the Gain
MultipleSources?
Cpk / PpkAcceptable?
OK
No
No
Poor
Yes
OK
N/A
OK
Yes
No
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Measurement Machine Methods
Output
Mother Earth ManMaterials
Process Capability
Long Term vs. Short Term Variation• Fishbone diagram
5 Min Variation
10 Hr Variation
6 Mo Variation
Short Term
Long Term
Performance
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Stability
– Without stability, cannot use data as a predictor offuture
– Special Causes create instability – removal for study?
Normality:
– Calculations are based on Normal Distribution
– Further from ‘normal’ less accurate totally invalid
– Calculation Tests & Probability Plotting
Stability & Normality
Stability Question Normality Question
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Process Capability
• Cpk – ratio to the smallestvalue (USL/LSL)
• Ppk – ratio to the smallestvalue (USL/LSL)
How it’s measured
• Cp – capability index
• Pp – performance index
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Process Capability
Process Capability rule of thumb:– Cpk > 1.50 Process is Six Sigma
– Cpk > 1.00 All Product Meets Requirements
– Cpk = 1.00 Most Product Meets Requirements
– Cpk < 1.00 Some Product Does Not Meet Requirements
– Ppk typically 0.33 less than Cpk
Note: Above calculates take in 1.5 s shift of mean over time
What are Jireh standards for Cpk ?What is difference between Cpk & Ppk in Jireh?
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Process Capability
Objective of Process Capability Analysis
– Determine how the natural process limits compare with thespecification range
– Depending on the comparison to standard:
Study Outcome
Do nothing -1- -2- Change the specs
Center the process -3- -4- Reduce process variability
-5-
Accept the losses
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
1. _____________________________________________
2. _____________________________________________
3. _____________________________________________
4. _____________________________________________
5. _____________________________________________
Key Learnings38
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
SPC: Attribute & Variable Data
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Data Types
What About… %
Type Description Model Symbol
AttributeDiscrete
counted
VariableContinuous
measured
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Data Collection
Attribute Data– Counted:
• How many• How often• What kind
– Discrete
– Convert Attribute to Variable• Measure attribute (length/area)• Create a scale: Likert
Check Sheets – for Attribute data– NOT check-lists
– Defects / errors by time frame – ‘farmer’s count’
– Quick visual analysis – sum by column or row
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
• Binomial Distribution
– Defectives – number of pieces unacceptable
• Poisson Distribution
– Defects – errors to a single piece
Attribute Distributions42
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Attribute Control Charts
Defect: is each nonconformance to the specified acceptance criteria
Defective: is an item (unit) in a sample that has one or morenonconformance to the acceptance criteria
– A “defective” contains at least one “defect”
Defectives Control Charts
– np Plots number of non-conforming units (needs fixed n)
– p Plots proportion of non-conforming units (n varies)
Defects Control Charts
– c Plots number of defects (requires fixed n)
– u Plots number of defects per “inspection unit” (n varies)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Attribute Charts
Defectives(binomial)
Defects(Poisson)
Sample Size Varies Sample Size Fixed
p Chart (most common)
% or portion defective
np Chart
Number of defectives
u Chart
Average number of defects
c Chart
Actual number of defects
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Human Error Modes
1. Omission
2. Excessive / insufficient repetition
3. Wrong order
4. Early / late execution
5. Execution of restricted work
6. Incorrect selection
7. Incorrect counting
8. Misrecognition
9. Failing to sense danger
10. Incorrect holding
11. Incorrect positioning
12. Incorrect orientation
13. Incorrect motion
14. Improper holding
15. Inaccurate motion
16. Insufficient avoidance
BW (Ben) Marguglio, LLC845-265-0123
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Xbar-R (Xbar = average of readings; R = range)
– n sample size
– X or x reading (data)
– Xbar average of readings
– Xbarbar average of averages
– R range of data points
– Rbar average of ranges
– S or s standard deviation
NOTE: UCL/LCL are boundaries for 99.73% of the data population
Variable Data SPC Terms46
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
The Control Chart
Time
Measu
re
UCL
LCL
AVG
PLOT POINT
99.73%
Remember: Control limits are determined by the process average values...
NOT SPECIFICATIONS
NOTE: Process spread is equal to a +/– 3 sigma from the mean
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
• Constructing a chart– Historic Data: minimum 20 data-sets (time increments)– Reference table values
• Calculate / post UCL / LCL
• Visualize Zones (+/– 3 std deviation)
• Plot data points
• Interpret Immediately
Using Variable Data Charts
Variable Charts
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Variables Control Charts
X-Bar and R Chart (2 charts)
– Plot (1) subgroup average
– Plot (2) subgroup range
X-Bar and S Chart (2 charts)
– Plot (1) subgroup average
– Plot (2) subgroup standard deviation – typically when n>9
ImR/ XmR Chart (individuals moving range – 2 charts)
– Plot (1) individual value
– Plot (2) difference between 2 consecutive individuals
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
1. _____________________________________________
2. _____________________________________________
3. _____________________________________________
4. _____________________________________________
5. _____________________________________________
Key Learnings50
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Operational SPC
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Control Plan / SPC
Based on Capability & Stability• Understand source of input variation• Understand frequency of input variation• SPC: Run-time, Set-up, Special Event
Control Plan• Document who, what, when, sample• Out of Control Action Plan
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Control Plan
Components of a Control Plan– Process Step to be ‘controlled’ (critical to process/output)– Variable to control (input or output)
– Specification / acceptable ‘management limits’– Measurement Method
– Control Method – SPC / other monitoring– Sample Size / Sample Frequency
– OCAP – Out-of-Control Action Plan• Who to contact – initiate responsibility for action• What action to take (investigative or prescribed)• What documentation (SOP or records)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Key Process Characteristics
Measurement Machine Methods
. .
Mother Earth ManMaterials
Per YOUR determination of Key Process Inputs
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Variable Data
– Xbar – R
– Xbar – S
– X – MR
– Median
Types of Control Charts
Attribute Data
– p Chart
– np Chart
– c Chart
– u Chart
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Antenna AssemblyLong Term Process Capability
-150%
-100%
-50%
0%
50%
100%
150%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Tool Wear Direction
Locating Slot Width Upper Crush Rib Snap Height
Upper Spec
Lower Spec
Nom-
X
XX
SuggestedMonitoring
XX
X
X
X
X
XX
X
Lower Crush Rib
X
AssemblyFeatures
Effective SPC
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Set up controls at:• Changes of authority
• Start of significant, irreversible activity
• After critical quality feature created
• Vital few process inputs (Xs)
• Significant cost decision points
• Service gates
• Set-up operations
• Material Introduction
Use your process flow chart to identify control points
Where Should I Control ?57
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Subgrouping
– Select SPC samples in a way that makes each subgroupas homogeneous (same) as possible
– A sampling process that reflects the actual process
Sources of Variability
–Time-to-Time (lot-to-lot)
–Within Piece
–Between Pieces
SPC Sampling - Rational Subgrouping
M T W T F S S M T W T F S S M T W T F S S M T W T F S S
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
1. _____________________________________________
2. _____________________________________________
3. _____________________________________________
4. _____________________________________________
5. _____________________________________________
Key Learnings59
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpretation of SPC Charts
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
60
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Statistical Thinking Map
DesignFMEA
ProcessFMEA
ProcessControl
DefineCritical
Characteristics
ApprovalPlanning
MeasurementSystemAnalysis
ProcessCapabilityStudies
ProcessImprovement
ControlPlan
ProcessCapable
Yes
No
StatisticalProcessControl
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Control Chart Interpretation
Control Charts– Average and control limits are a function of past history
common cause variation– If process remains stable, only common cause variation
is existent in the process– Special Cause conditions create Out-of-Control signals
on the control chart– Four general rules:
1. Average: Out-of-Control Range: In-Control2. Average: In-Control Range: Out-of-Control3. Average: Out-of-Control Range: Out-of-Control4. Average: In-Control Range: In-Control
– 5+ Specific Rules (sigma zones)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
“Out of Control”
– Special causes of variation are present
– Is detected by either having any point outside thecontrol limits or by unnatural patterns
7 Rules to interpret control charts
Out of Control63
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpreting a Control Chart
Time
Measu
re
UCL
LCL
AVE
1. A lack of control is indicated whenever a single point fallsoutside the control limits.
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpreting a Control Chart
Time
Measu
re
UCL
LCL
AVE
2. 4 out of 5 points in zone B
(A)
(B)
(C)
(A)
(B)
(C)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpreting a Control Chart
3. 2 out of 3 points in zone A
Time
Measu
re
UCL
LCL
AVE
(A)
(B)
(C)
(A)
(B)
(C)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpreting a Control Chart
4. 8 or more consecutive points on one side of centerline
Time
Measu
re
UCL
LCL
AVE
(A)
(B)
(C)
(A)
(B)
(C)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpreting a Control Chart
5. A trend of 6 or more consecutive pointsincreasing or decreasing
Time
Measu
re
UCL
LCL
AVE
(A)
(B)
(C)
(A)
(B)
(C)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpreting a Control Chart
6. Stratification, 15 or more points in zone C
Time
Measu
re
UCL
LCL
AVE
(A)
(B)
(C)
(A)
(B)
(C)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Interpreting a Control Chart
7. Mixture or systematic variation
Time
Measu
re
UCL
LCL
AVE
(A)
(B)
(C)
(A)
(B)
(C)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Out-of-Control Action Plan (OCAP)
Activators
Activators - out-of-control decision rules
Checkpoints
Checkpoints - list of possible assignable causes
Terminators
Terminators - corrective actions
Start
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
End
No
No
Out-of-Control Action Plan (OCAP)
Actions:Who to contact – initiate responsibility for actionWhat action to take (investigative or prescribed)What documentation (SOP or records)
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Engagement Renewal
• SPC / Stats Review• Critical Characteristics
• Product or Process
• Measurement Capability• Process Capability
• SPC: Attribute / Variable• Establishing SPC in Operations
• SPC Interpretation• Renewed Engagement
72
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Taguchi Loss Function
Nominal
Lower SpecificationLimit (LSL)
Upper SpecificationLimit (USL)
Acceptable Product Rejected ProductRejected Product
BestOutput
The LossFunctioninvertednormal
distributioncurve
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Multi-Vari Studies
Studying Relationships– Between suspect input variables and the output variables of
a process while in normal operation
Passive Data Collection– Process is monitored in its natural state
– without intervention or can be done with historical data
Full Range of Variation– To allow inputs to vary so we can observe their effects on
the outputs
Inherent Issues– To identify process problems and limitations
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Data Collection
The identified inputs (Xs) are monitored in concert with thecritical outputs (Ys)
– Relate variation in the inputs to variation inoutputs
Xs Ys
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SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Multi-Vari Study - Graphical
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3,m
ax)
3-(m
ed, Q
3)
2-(Q
1,m
ed)
1-(m
in, Q
1)
4-(Q
3,max
)
3-(m
ed, Q
3)
2-(Q
1,m
ed)
1-(m
in, Q
1)
Day
Mean
Shift Product Opr Exp Lot Code Color Booth SolCode TempCode RHCode SpeedCode
Main Effects Plot for ThicknessData Means
76
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
54321
1087654321010876543210108765432101087654321010876543210
1.53
1.48
1.43
1.38
Part
A
1
2
Multi-Vari Chart for A by Trial - PartOper
Trial
Multi-Vari Study Example
Range of measurement – all inspectors – single part
Master Inspector measurement
77
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
SPC Checklist Activity
Team Activity
• Form Teams of 4-5
• Using current SPC Procedure & Process Specs
• Create a Checklist for daily/weekly review of SPC
• Activity: 30 minutes to complete
• Report-Out – 5 minutes per team of line items
• Debrief: collective sharing of team Checklists
• Similarities & Differences
• Value of SPC Checklist ?
78
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
1. _____________________________________________
2. _____________________________________________
3. _____________________________________________
4. _____________________________________________
5. _____________________________________________
Key Learnings79
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Overall Feedback – Key Learnings• Cpk based individual; SPC on X-bar chart
• Datainterpretationaction
• Stable chart as the foundation for predictable future
• Clear steps to set up SPC
• Interpretation of WE rules
• Fully understand the key parameters then create specific chart tomonitor
• OCAP design review to come up with good procedure
• Daily review and in some cases to reset SPC limits
• Charting SPC on a paper a good exercise
• Multi-variable correlation to generate actions to improve SPC
• Customer always sees individual not average of the sample; thisreminds us to look at and address SPC more carefully
• Interpretation immediately; looking at SPC chart real-time
• Process capability, stability, normality review before SPC setup
• Daily review checklist item exercise/OCAP for continuousimprovement
80
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
Overall Feedback – Key Learnings
81
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
For your attention and active participation!
John
SPC - Jireh Semiconductor - 2018ualityQJohn Breckline – Key Quality
John Breckline
83