Management and Leadership
10.6%of exam
The Quality System
11.3%of exam
Product, Process, Service Design
13.1%of exam
Product and Process Control
14.4%of exam
Continuous Improvement
16.3%of exam
Quantitative Methods and Tools
21.3%of exam
Risk Management
13.1%of exam
Quick Facts
- Exam
- ASQ CQE
- Questions
- 175 CBT, 160 scored
- Unscored
- 15 pretest items
- Exam time
- 5 h 18 min
- Appointment
- 5.5 hours total
- Pass
- Scaled score 550
- Pass rate
- 69% in 2024
- Format
- Open book, bound references
- Delivery
- Prometric testing windows
- Fee
- $550; members $450
- Experience
- 8 years, 3 deciding
- Recertify
- 18 RUs every 3 years
Quality Philosophies
- Deming
- System owns most variation14 points
- Juran
- Fitness for useTrilogy
- Crosby
- Conformance to requirementsZero defects
- Feigenbaum
- Total quality control
- Ishikawa
- Fishbone, quality circles
- Taguchi
- Loss function, robust design
- Shewhart
- Control charts, plan-do-study-act
- Six Sigma
- DMAIC projects, 3.4 DPMO
Teams and Facilitation
- RACI
- Exactly one accountable owner
- Responsible
- Performs the actual work
- Consulted
- Two-way input before deciding
- Informed
- One-way update afterward
- Brainstorming
- Open generation, no ranking
- Nominal group technique
- Silent write, round-robin, rank
- Force-field analysis
- Driving versus restraining forces
- Facilitator
- Owns process, not content
Benchmarking and Metrics
- Internal benchmarking
- Units inside same organization
- Competitive benchmarking
- Direct rival comparison
- Functional benchmarking
- Same function, other industry
- Generic benchmarking
- Similar process anywhere
- Cost-benefit analysis
- Gains weighed against cost
- Gantt chart
- Schedule bars over time
Customer and Supplier
- Stakeholder analysis
- Identify who is affected
- Satisfaction survey
- Direct voice of customer
- Supplier qualification
- Approve before first order
- Supplier certification
- Reduces receiving inspection
- Supplier rating
- Score quality, delivery, cost
- Business continuity
- Plan for major disruption
Cost of Quality Categories
PAF: Prevention, Appraisal, Failure
Prevention: planning, trainingAppraisal: inspection, testInternal failure: before shipmentExternal failure: after shipmentConformance: prevention plus appraisal
Quality System Documents
- Quality manual
- Policy and scopeLevel 1
- Procedures
- Who does what, whenLevel 2
- Work instructions
- How a task runsLevel 3
- Records
- Objective evidence of executionLevel 4
- Document control
- Right version at use
- Configuration management
- Control baseline and changes
- Quality policy
- Top management intent statement
Documentation Levels
Manual, Procedures, Instructions, Records
Level 1: quality manualLevel 2: proceduresLevel 3: work instructionsLevel 4: records
Audit Types and Roles
- First party
- Organization audits itself
- Second party
- Customer audits its supplier
- Third party
- Independent registrar or regulatorCertifies
- Product audit
- Item against its specification
- Process audit
- One process as documented
- System audit
- Whole QMS against standard
- Client
- Requests and commissions audit
- Auditee
- Organization being audited
- Follow-up
- Verify corrective action worked
Cost of Quality
- Prevention
- Stop defects from happening
- Appraisal
- Inspection, test, audit cost
- Internal failure
- Found before shipment
- External failure
- Found by the customerCostliest
- Cost of conformance
- Prevention plus appraisal
- Cost of nonconformance
- Internal plus external failure
- Hidden quality cost
- Unrecorded rework and delay
Standards Map
- ISO 9001
- QMS requirementsCertifiable
- ISO 9000
- Vocabulary and fundamentals
- ISO 9004
- Sustained success guidance
- ISO 19011
- Auditing management systems
- ISO 31000
- Risk management guidance
- Baldrige
- Seven-category excellence frameworkAward, not certificate
- ANSI/ASQ Z1.4
- Attributes sampling standard
- ANSI/ASQ Z1.9
- Variables sampling standard
Weibull Beta Shapes
Beta under one infant, over one wear-out
Beta below 1: decreasing rateBeta = 1: exponential, randomBeta above 1: wear-outBathtub combines all three
Verification vs Validation
Verification
- Built the product right
- Meets written specification
- IQ and OQ
Validation
- Built the right product
- Meets real user needs
- PQ in production
Specification vs intended use
Drawings and Specifications
- Basic dimension
- Boxed, exact, no tolerance
- Feature control frame
- Carries the geometric tolerance
- Datum
- Reference origin for measurement
- Title block
- Scale, units, revision level
- MMC
- Maximum material conditionBonus tolerance
- LMC
- Least material condition
- Bilateral tolerance
- Plus and minus both
- Unilateral tolerance
- One direction only
- Critical to quality
- Customer-driven key characteristic
Verification and Validation
- Verification
- Output meets the specification
- Validation
- Product meets user needs
- IQ
- Installed and configured correctly
- OQ
- Works across operating range
- PQ
- Consistent output, real production
- DFX
- Design for manufacturability, serviceability
- DFSS
- Design for Six Sigma
- Requirements traceability
- Link need to test
- Design review
- Staged cross-functional gate
Reliability Indices
- MTBF
- Repairable, time between failures
- MTTF
- Non-repairable, time to failure
- MTTR
- Mean time to repair
- Failure rate
- Lambda, failures per time
- Availability
- MTBF/(MTBF+MTTR)Inherent
- Exponential model
- Constant rate, MTBF=1/lambda
- Series system
- Multiply component reliabilities
- Active parallel
- One minus product of unreliabilities
- Bathtub curve
- Infant, useful life, wear-out
FMEA and Hazard Tools
- RPN
- Severity x occurrence x detection1 to 1000
- Severity
- Effect on the customer
- Occurrence
- How often cause happens
- Detection
- 10 means controls missInverted scale
- dFMEA
- Design failure modes
- pFMEA
- Process failure modes
- uFMEA
- Use and misuse modes
- FMECA
- FMEA plus criticality analysis
- Hazard analysis
- Safety hazards and controls
Producer's vs Consumer's Risk
Producer's risk
- Good lot rejected
- Alpha, about 0.05
- Read at AQL
Consumer's risk
- Bad lot accepted
- Beta, about 0.10
- Read at LTPD
AQL protects seller, LTPD buyer
Sampling Plan Picker
- Count good or bad→Z1.4 attributes
- Measure one dimension→Z1.9 variables(Assumes normality)
- Protect the producer→AQL point(Alpha near 0.05)
- Protect the consumer→LTPD point(Beta near 0.10)
- Need sharper discrimination→Increase sample size(Not lot size)
- Want a more lenient plan→Raise acceptance number
- Two of five lots rejected→Tightened inspection
- Consistently good history→Reduced inspection
- Five tightened lots rejected→Stop the sampling(Z1.4 rule)
- Costly or destructive test→Special inspection level(S-1 to S-4)
- One isolated lot→Type A curve(Hypergeometric)
Acceptance Sampling
- AQL
- Worst still-acceptable quality levelPa 0.95
- LTPD
- Poor quality, rarely acceptedPa 0.10
- RQL
- Another name for LTPD
- OC curve
- Acceptance probability versus quality
- Producer's risk
- Alpha, good lot rejected
- Consumer's risk
- Beta, bad lot accepted
- AOQ
- Average outgoing quality
- AOQL
- Worst average outgoing qualityCurve maximum
- ATI
- Average total units inspected
- Type A curve
- Isolated lot, hypergeometric
- Type B curve
- Continuous stream, binomial
Repeatability vs Reproducibility
Repeatability
- Equipment variation
- One operator, one gage
- Within-appraiser spread
Reproducibility
- Appraiser variation
- Different operators, same part
- Between-appraiser spread
Gage varies vs people vary
Sampling Standards
- Z1.4
- Attributes, indexed by AQL
- Z1.9
- Variables, assumes normal distribution
- General level II
- Default inspection level
- Special levels
- S-1 through S-4Small samples
- Code letter
- Lot size to sample
- Normal inspection
- Standard starting state
- Tightened inspection
- Two of five rejected
- Reduced inspection
- Consistent good history
- Discontinue rule
- Five tightened lots rejected
Rework vs Repair
Rework
- Restores full conformance
- Meets original specification
- No concession needed
Repair
- Usable but nonconforming
- Needs documented concession
- Customer approval typical
Conforming vs merely acceptable
Metrology and Calibration
- Traceability
- Unbroken chain to NIST
- Calibration interval
- Set by risk and drift
- Measurement error
- Bias plus random variation
- Rule of ten
- Gage ten times finer
- Gage blocks
- Length reference standards
- CMM
- Coordinate measuring machine
- Optical comparator
- Projects magnified part profile
- Destructive test
- Part unusable afterward
Z1.4 vs Z1.9
Z1.4
- Attributes sampling
- Count nonconforming units
- Any number of characteristics
Z1.9
- Variables sampling
- Measure one characteristic
- Smaller sample, assumes normal
Count versus measure
Gage R&R Terms
- Repeatability
- Equipment variation, one operator
- Reproducibility
- Appraiser variation between operators
- GRR under 10%
- Generally acceptable systemAccept
- GRR 10 to 30%
- Acceptable depending on application
- GRR over 30%
- Unacceptable, fix systemReject
- Bias
- Average differs from reference
- Linearity
- Bias changes across range
- Stability
- Bias drifts over time
- ndc
- Number of distinct categoriesFive or more
Material Control
- MRB
- Board deciding nonconforming disposition
- Use as is
- Accept with no change
- Rework
- Restores full conformance
- Repair
- Usable but still nonconformingNeeds concession
- Scrap
- Discard, cannot be used
- Return to supplier
- Send back for credit
- Segregation
- Physically separate nonconforming stock
- Lot traceability
- History, location, application record
Eight Lean Wastes
DOWNTIME
DefectsOverproductionWaitingNon-utilized talentTransportationInventoryMotionExtra processing
Correction vs Corrective Action
Correction
- Fixes the affected item
- Rework, repair, scrap
- No cause analysis
Corrective action
- Eliminates the cause
- Prevents recurrence
- Effectiveness verified
Fix the part vs cause
Improvement Method Picker
- Small local incremental change→PDCA(Fast loop)
- Unknown cause, high stakes→DMAIC(Six Sigma project)
- New product or process→DMADV(DFSS)
- Short intense team event→Kaizen event
- Organize causes before data→Fishbone diagram
- Find the vital few→Pareto chart(80/20)
- Organize many verbal ideas→Affinity diagram
- Sequence tasks and deadlines→Activity network diagram
- Anticipate what could fail→PDPC
Seven QC Tools
- Flowchart
- Map the process steps
- Pareto chart
- Separate the vital few80/20
- Cause and effect
- Fishbone organizes hypotheses
- Control chart
- Common versus special cause
- Check sheet
- Structured tally collection
- Scatter diagram
- Two-variable relationship plot
- Histogram
- Distribution shape and spread
Basic Tools Recall
Flow, Pareto, Fish, Chart, Check, Scatter, Histogram
Handles numerical dataFishbone works before dataPareto finds vital fewControl chart tests stability
Seven Management Tools
- Affinity diagram
- Group ideas into themes
- Tree diagram
- Break goal into tasks
- PDPC
- Anticipate what could fail
- Matrix diagram
- Relate two or more lists
- Interrelationship digraph
- Find drivers and outcomes
- Prioritization matrix
- Weighted option ranking
- Activity network diagram
- Sequence and critical path
Lean Tools
- 5S
- Sort, set, shine, standardize, sustain
- Value stream mapping
- Material and information flow
- Kanban
- Pull signal for replenishment
- Visual control
- Status obvious at glance
- Standardized work
- Best known method documented
- Takt time
- Available time / demandCustomer pace
- Cycle time
- Actual time per unit
- SMED
- Single minute exchange die
- OEE
- Availability x performance x qualityThree rates multiply
Corrective and Preventive Action
- Correction
- Fixes this item only
- Corrective action
- Removes cause of nonconformity
- Preventive action
- Removes cause of potential
- 5 Whys
- Ask why until cause
- Root cause analysis
- Find the true origin
- Recurrence control
- Stop it happening again
- Verification of effectiveness
- Prove the fix held
- Prevention poka-yoke
- Error physically impossiblePreferred
- Detection poka-yoke
- Signals the error immediately
Chart Selection
Variables: Xbar-R, ImR. Attributes: p, np, c, u
Xbar-R: subgroups 2-9ImR: single readingsp, np: nonconforming unitsc, u: nonconformities
Cp vs Cpk
Cp
- Potential capability
- Ignores centering
- (USL-LSL)/6 sigma
Cpk
- Actual capability
- Penalizes off-center mean
- Minimum of Cpu, Cpl
Cpk never exceeds Cp
Control Chart Picker
- Variables, subgroup 2-9→Xbar-R(Range estimates spread)
- Variables, subgroup 10+→Xbar-s(Std dev better)
- Variables, one reading→ImR chart(Needs normality)
- Slow process, smoothing wanted→MAmR chart
- Nonconforming units, varying n→p chart(Proportion)
- Nonconforming units, constant n→np chart(Count)
- Nonconformities, constant unit→c chart(Poisson)
- Nonconformities, varying unit→u chart(Per unit)
- Short production runs→Short-run SPC(Code to target)
Distributions
- Normal
- Symmetric continuous bell shape
- Uniform
- Equal probability across range
- Exponential
- Constant failure rate life
- Lognormal
- Right-skewed, repair times
- Weibull
- Shape parameter fits anything
- Student's t
- Small samples, unknown sigma
- F
- Ratio of two variances
- Chi-square
- Variance and goodness-of-fit
- Binomial
- Fixed trials, constant probability
- Poisson
- Counts per constant interval
- Hypergeometric
- Finite lot, no replacement
- Multinomial
- More than two outcomes
Cpk vs Ppk
Cpk
- Within-subgroup sigma
- Rbar/d2 estimate
- Short-term capability
Ppk
- Overall sample sigma
- Includes between-subgroup drift
- Long-term performance
Wide gap signals instability
Hypothesis Test Picker
- One mean, sigma known→Z test
- One mean, sigma unknown→t test(n-1 degrees freedom)
- Two independent means→Two-sample t test
- Before and after, same units→Paired t test
- Three or more means→ANOVA F test(Then post-hoc)
- Compare two variances→F test
- One variance versus target→Chi-square test
- Does data fit distribution→Goodness-of-fit test
- Two categorical variables→Contingency table(Chi-square)
- Compare two proportions→Two-proportion Z test
Inference Terms
- Population
- Whole group of interest
- Sample
- Subset actually measured
- Parameter
- True population value
- Statistic
- Value computed from sample
- Standard error
- Sigma over root n
- Central limit theorem
- Sample means approach normal
- Confidence interval
- Range for a parameter
- Tolerance interval
- Range for individual values
- Alpha
- Type I error probability
- Beta
- Type II error probability
- Power
- One minus betaRaise with n
- p-value
- Evidence against the null
Type I vs Type II
Type I error
- Reject a true null
- Probability alpha
- Producer's risk
Type II error
- Keep a false null
- Probability beta
- Consumer's risk
False alarm vs missed signal
Capability Index Picker
- Process not in control→Fix stability first(Capability invalid)
- Short-term, within subgroup→Cp and Cpk
- Long-term, all data→Pp and Ppk
- Centering does not matter→Cp(Potential only)
- Centering matters→Cpk(Min Cpu, Cpl)
- Target value matters→Cpm(Taguchi index)
- One-sided specification only→Cpu or Cpl
Relationships Between Variables
- r
- Direction and strength, -1 to 1
- r-squared
- Proportion of variation explained
- Linear regression
- Fit line, predict response
- ANOVA F
- MSB divided by MSW
- Contingency table
- Two categorical variables, independence
- Moving average
- Smooths time series trend
Control vs Specification Limits
Control limits
- Calculated from process
- Three sigma of statistic
- Voice of process
Specification limits
- Set by customer
- Apply to individual parts
- Voice of customer
Never plot specs on Xbar
Control Charts
- Xbar-R
- Variables, subgroup two to nine
- Xbar-s
- Variables, subgroup ten plus
- ImR
- Individuals and moving range
- MAmR
- Moving average, moving range
- p chart
- Proportion nonconforming, varying n
- np chart
- Number nonconforming, constant n
- c chart
- Nonconformities, constant inspection unit
- u chart
- Nonconformities per unit, varying
- Rational subgrouping
- Common cause within subgroup
- Short-run SPC
- Coded deviation from target
Common vs Special Cause
Common cause
- Inherent random variation
- Process is stable
- Management changes system
Special cause
- Assignable, outside system
- Signals on chart
- Local investigation first
System noise vs assignable event
Control Chart Constants
- A2
- Xbar-R limit factor
- A3
- Xbar-s limit factor
- d2
- Converts Rbar to sigma
- D3
- Lower R limit factor0 below n=7
- D4
- Upper R limit factor
- E2
- Individuals chart limit factor
- n=2
- d2=1.128, D4=3.267, E2=2.660
- n=5
- d2=2.326, A2=0.577, D4=2.114
Out-of-Control Rules
- 1 beyond 3 sigma
- Classic out-of-control signalWestern Electric
- 2 of 3 beyond 2 sigma
- Same side of centerWestern Electric
- 4 of 5 beyond 1 sigma
- Same side of centerWestern Electric
- 8 in a row
- One side of centerlineWestern Electric
- Points hug centerline
- Suspect stratification or mixing
- Cycles or trends
- Nonrandom systematic pattern
Capability Indices
- Cp
- (USL-LSL)/6 sigmaPotential
- Cpk
- Minimum of Cpu, CplActual
- Cpu
- (USL-xbar)/3 sigma
- Cpl
- (xbar-LSL)/3 sigma
- Cpm
- Penalizes deviation from targetTaguchi
- Cr
- Inverse of CpLower is better
- Pp
- Overall sigma, ignores centering
- Ppk
- Overall sigma, includes centering
- Sigma within
- Rbar/d2 from chart
- Sigma overall
- Standard deviation, all data
- DPMO
- Defects per million opportunities
- PPM
- Parts per million defective
- Natural process limits
- Mean plus minus 3 sigma
DOE Terms
- Factor
- Input variable being changed
- Level
- Setting of a factor
- Response
- Measured output variable
- Treatment
- One factor level combination
- Replication
- Repeat runs estimate error
- Randomization
- Protects against lurking variables
- Blocking
- Removes known nuisance variation
- Interaction
- Effect depends on another
- Confounding
- Effects cannot be separated
- Full factorial
- 2^k runs, all effects
- Fractional factorial
- 2^(k-p) runs, aliased effects
- Resolution III
- Main effects alias two-factor
- Resolution IV
- Main effects clear, two-factor aliased
- Resolution V
- Two-factor interactions stay clear
Risk Treatment Choices
Avoid, Mitigate, Transfer, Accept
Avoid: drop the activityMitigate: add controlsTransfer: insure or contractAccept: retain residual risk
Risk Terminology
- Risk
- Effect of uncertainty
- Severity
- Consequence if it happens
- Occurrence
- Likelihood it happens
- Detection
- Chance controls catch it
- Inherent risk
- Before any control applied
- Residual risk
- After treatment and controlsSign off here
- Risk appetite
- Exposure willingly accepted
- Risk-based thinking
- Prioritize effort by risk
Risk Types
- Enterprise risk
- Strategic, regulatory, business-wide
- Operational risk
- Supplier, project, quality system
- Product risk
- Design, process, use, safety
- Supply chain risk
- Disruption across supplier tiers
- Regulatory risk
- Compliance and approval exposure
- Safety risk
- Harm to people
Risk Treatment and Register
- Avoid
- Do not do it
- Mitigate
- Reduce severity or likelihood
- Transfer
- Insurance or contract termsCost moves only
- Accept
- Consciously retain residual risk
- Risk register
- Living log of risks
- Risk owner
- Named accountable person
- Risk matrix
- Severity against likelihood gridIgnores detection
- Acceptability criteria
- Threshold for treating risk
- Mitigation plan
- Actions, owners, due dates
Risk Monitoring
- Complaint tracking
- Customer signals after release
- Trending
- Field and warranty data
- Post-market surveillance
- Ongoing real-use monitoring
- Control testing
- Audit whether controls work
- Reopen the FMEA
- Rising trend triggers revision
- Gap analysis
- Missing or weak controls
Common Traps
Verification vs validation
Verification checks the specification ≠ Validation checks intended use
Cp vs Cpk
Cp ignores centering ≠ Cpk penalizes off-center mean
Control vs specification limits
Control limits from process ≠ Spec limits from customer
Alpha vs beta
Alpha rejects good lots ≠ Beta accepts bad lots
Rework vs repair
Rework restores full conformance ≠ Repair needs documented concession
Repeatability vs reproducibility
Repeatability is the equipment ≠ Reproducibility is the appraisers
Correction vs corrective action
Correction fixes the item ≠ Corrective action removes cause
Detection rating direction
Detection 10 means missed ≠ Detection 1 means caught
Sample size vs lot size
Sample size drives discrimination ≠ Lot size barely matters
Inherent vs residual risk
Inherent is before controls ≠ Residual is after treatment
MTBF vs MTTF
MTBF for repairable items ≠ MTTF for discarded items
Calibration vs traceability
Sticker shows calibration date ≠ Traceability needs unbroken chain
Last Minute
- 1.160 scored questions, 15 unscored
- 2.Quantitative Methods is largest, 34 questions
- 3.Cp = potential; Cpk = centered
- 4.Cpk uses within-subgroup sigma; Ppk overall
- 5.Alpha = producer risk; beta = consumer
- 6.AQL sits near 0.95 acceptance
- 7.LTPD sits near 0.10 acceptance
- 8.GRR under 10% is acceptable
- 9.GRR over 30% is unacceptable
- 10.MTBF = 1/lambda when rate constant
- 11.Series multiplies R; parallel multiplies unreliability
- 12.Availability = MTBF/(MTBF+MTTR)
- 13.RPN = severity x occurrence x detection
- 14.Detection 10 means controls miss it
- 15.Z1.4 counts; Z1.9 measures
- 16.Never plot specs on Xbar chart
- 17.Correction fixes item; corrective removes cause
- 18.Takt = available time / demand
- 19.OEE = availability x performance x quality
- 20.Residual risk drives acceptance decisions
- 21.Exam is open book, bound references
- 22.No alphabetic-keyboard calculators; clear memory
- 23.Passing scaled score is 550
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