- Management and Leadership (15
Questions)
- Quality Philosophies and
Foundations
Explain how modern quality has evolved
from quality control through statistical
process control (SPC) to total quality
management and leadership principles
(including Deming’s 14 points), and how
quality has helped form various
continuous improvement tools including
lean, six sigma, theory of constraints,
etc. (Remember)
- The Quality Management
System (QMS)
- Strategic planning
Identify and define top management’s
responsibility for the QMS,
including establishing policies and
objectives, setting
organization-wide goals, supporting
quality initiatives, etc. (Apply)
- Deployment techniques
Define, describe, and use various
deployment tools in support of the
QMS: benchmarking, stakeholder
identification and analysis,
performance measurement tools, and
project management tools such as
PERT charts, Gantt charts, critical
path method (CPM), resource
allocation, etc. (Apply)
- Quality information
system (QIS)
Identify and define the basic
elements of a QIS, including who
will contribute data, the kind of
data to be managed, who will have
access to the data, the level of
flexibility for future information
needs, data analysis, etc.
(Remember)
- ASQ Code of Ethics for
Professional Conduct
Determine appropriate behavior in
situations requiring ethical decisions.
(Evaluate)
- Leadership Principles and
Techniques
Describe and apply various principles
and techniques for developing and
organizing teams and leading quality
initiatives. (Analyze)
- Facilitation Principles and
Techniques
Define and describe the facilitator’s
role and responsibilities on a team.
Define and apply various tools used with
teams, including brainstorming, nominal
group technique, conflict resolution,
force-field analysis, etc. (Analyze)
- Communication Skills
Describe and distinguish between various
communication methods for delivering
information and messages in a variety of
situations across all levels of the
organization. (Analyze)
- Customer Relations
Define, apply, and analyze the results
of customer relation measures such as
quality function deployment (QFD),
customer satisfaction surveys, etc.
(Analyze)
- Supplier Management
Define, select, and apply various
techniques including supplier
qualification, certification,
evaluation, ratings, performance
improvement, etc. (Analyze)
- Barriers to Quality
Improvement
Identify barriers to quality
improvement, their causes and impact,
and describe methods for overcoming
them. (Analyze)
- The Quality System (15
Questions)
- Elements of the Quality
System
Define, describe, and interpret the
basic elements of a quality system,
including planning, control, and
improvement, from product and process
design through quality cost systems,
audit programs, etc. (Evaluate)
- Documentation of the Quality
System
Identify and apply quality system
documentation components, including
quality policies, procedures to support
the system, configuration management and
document control to manage work
instructions, quality records, etc.
(Apply)
- Quality Standards and Other
Guidelines
Define and distinguish between national
and international standards and other
requirements and guidelines, including
the Malcolm Baldrige National Quality
Award (MBNQA), and describe key points
of the ISO 9000 series of standards and
how they are used. [Note:
Industry-specific standards will not be
tested.] (Apply)
- Quality Audits
- Types of audits
Describe and distinguish between
various types of quality audits such
as product, process, management
(system), registration
(certification), compliance
(regulatory), first, second, and
third party, etc. (Apply)
- Roles and
responsibilities in audits
Identify and define roles and
responsibilities for audit
participants such as audit team
(leader and members), client,
auditee, etc. (Understand)
- Audit planning and
implementation
Describe and apply the steps of a
quality audit, from the audit
planning stage through conducting
the audit, from the perspective of
an audit team member. (Apply)
- Audit reporting and
follow up
Identify, describe, and apply the
steps of audit reporting and follow
up, including the need to verify
corrective action. (Apply)
- Cost of Quality (COQ)
Identify and apply COQ concepts,
including cost categories, data
collection methods and classification,
and reporting and interpreting results.
(Analyze)
- Quality Training
Identify and define key elements of a
training program, including conducting a
needs analysis, developing curricula and
materials, and determining the program’s
effectiveness. (Apply)
- Product and Process Design (25
Questions)
- Classification of Quality
Characteristics
Define, interpret, and classify quality
characteristics for new products and
processes. [Note: The classification of
product defects is covered in IV.B.3.]
(Evaluate)
- Design Inputs and Review
Identify sources of design inputs such
as customer needs, regulatory
requirements, etc. and how they
translate into design concepts such as
robust design, QFD, and Design for X (DFX,
where X can mean six sigma (DFSS),
manufacturability (DFM), cost (DFC),
etc.). Identify and apply common
elements of the design review process,
including roles and responsibilities of
participants. (Analyze)
- Technical Drawings and
Specifications
Interpret technical drawings including
characteristics such as views, title
blocks, dimensioning, tolerancing, GD&T
symbols, etc. Interpret specification
requirements in relation to product and
process characteristics. (Evaluate)
- Design Verification
Identify and apply various evaluations
and tests to qualify and validate the
design of new products and processes to
ensure their fitness for use. (Evaluate)
- Reliability and
Maintainability
- Predictive and
preventive maintenance tools
Describe and apply these tools and
techniques to maintain and improve
process and product reliability.
(Analyze)
- Reliability and
maintainability indices
Review and analyze indices such as,
MTTF, MTBF, MTTR, availability,
failure rate, etc. (Analyze)
- Bathtub curve
Identify, define, and distinguish
between the basic elements of the
bathtub curve. (Analyze)
- Reliability / Safety /
Hazard Assessment Tools
Define, construct, and interpret the
results of failure mode and effects
analysis (FMEA), failure mode,
effects, and criticality analysis (FMECA),
and fault tree analysis (FTA).
(Analyze)
- Product and Process Control (32
Questions)
- Tools
Define, identify, and apply product and
process control methods such as
developing control plans, identifying
critical control points, developing and
validating work instructions, etc.
(Analyze)
- Material Control
- Material identification,
status, and traceability
Define and distinguish these
concepts, and describe methods for
applying them in various situations.
[Note: Product recall procedures
will not be tested.] (Analyze)
- Material segregation
Describe material segregation and
its importance, and evaluate
appropriate methods for applying it
in various situations. (Evaluate)
- Classification of
defects
Define, describe, and classify the
seriousness of product and process
defects. (Evaluate)
- Material review board (MRB)
Identify the purpose and function of
an MRB, and make appropriate
disposition decisions in various
situations. (Analyze)
- Acceptance Sampling
- Sampling concepts
Define, describe, and apply the
concepts of producer and consumer
risk and related terms, including
operating characteristic (OC)
curves, acceptable quality limit (AQL),
lot tolerance percent defective (LTPD),
average outgoing quality (AOQ),
average outgoing quality limit (AOQL),
etc. (Analyze)
- Sampling standards and
plans
Interpret and apply ANSI/ASQ Z1.4
and Z1.9 standards for attributes
and variables sampling. Identify and
distinguish between single, double,
multiple, sequential, and continuous
sampling methods. Identify the
characteristics of Dodge-Romig
sampling tables and when they should
be used. (Analyze)
- Sample integrity
Identify the techniques for
establishing and maintaining sample
integrity. (Analyze)
- Measurement and Test
- Measurement tools
Select and describe appropriate uses
of inspection tools such as gage
blocks, calipers, micrometers,
optical comparators, etc. (Analyze)
- Destructive and
nondestructive tests
Distinguish between destructive and
nondestructive measurement test
methods and apply them
appropriately. (Analyze)
- Metrology
Identify, describe, and apply metrology
techniques such as calibration systems,
traceability to calibration standards,
measurement error and its sources, and
control and maintenance of measurement
standards and devices. (Analyze)
- Measurement System Analysis
(MSA)
Calculate, analyze, and interpret
repeatability and reproducibility (Gage
R&R) studies, measurement correlation,
capability, bias, linearity, etc.,
including both conventional and control
chart methods. (Evaluate)
- Continuous Improvement (30
Questions)
- Quality Control Tools
Select, construct, apply, and interpret
tools such as 1) flowcharts, 2) Pareto
charts, 3) cause and effect diagrams, 4)
control charts, 5) check sheets, 6)
scatter diagrams, and 7) histograms.
(Analyze)
- Quality Management and
Planning Tools
Select, construct, apply, and interpret
tools such as 1) affinity diagrams, 2)
tree diagrams, 3) process decision
program charts (PDPC), 4) matrix
diagrams, 5) interrelationship digraphs,
6) prioritization matrices, and 7)
activity network diagrams. (Analyze)
- Continuous Improvement
Techniques
Define, describe, and distinguish
between various continuous improvement
models: total quality management (TQM),
kaizen, plan-do-check-act (PDCA), six
sigma, theory of constraints (TOC),
lean, etc. (Analyze)
- Corrective Action
Identify, describe, and apply elements
of the corrective action process
including problem identification,
failure analysis, root cause analysis,
problem correction, recurrence control,
verification of effectiveness, etc.
(Evaluate)
- Preventive Action
Identify, describe, and apply various
preventive action tools such as
error-proofing/poka-yoke, robust design,
etc., and analyze their effectiveness.
(Evaluate)
- Quantitative Methods and Tools
(43 Questions)
- Collecting and Summarizing
Data
- Types of data
Define, classify, and compare
discrete (attributes) and continuous
(variables) data. (Apply)
- Measurement scales
Define, describe, and use nominal,
ordinal, interval, and ratio scales.
(Apply)
- Data collection methods
Describe various methods for
collecting data, including tally or
check sheets, data coding, automatic
gaging, etc., and identify their
strengths and weaknesses. (Apply)
- Data accuracy
Describe the characteristics or
properties of data (e.g.,
source/resource issues, flexibility,
versatility, etc.) and various types
of data errors or poor quality such
as low accuracy, inconsistency,
interpretation of data values, and
redundancy. Identify factors that
can influence data accuracy, and
apply techniques for error detection
and correction. (Apply)
- Descriptive statistics
Describe, calculate, and interpret
measures of central tendency and
dispersion (central limit theorem),
and construct and interpret
frequency distributions including
simple, categorical, grouped,
ungrouped, and cumulative.
(Evaluate)
- Graphical methods for
depicting relationships
Construct, apply, and interpret
diagrams and charts such as
stem-and-leaf plots, box-and-whisker
plots, etc. [Note: Run charts and
scatter diagrams are covered in V.A.]
(Analyze)
- Graphical methods for
depicting distributions
Construct, apply, and interpret
diagrams such as normal probability
plots, Weibull plots, etc. [Note:
Histograms are covered in V.A.]
(Analyze)
- Quantitative Concepts
- Terminology
Define and apply quantitative terms,
including population, parameter,
sample, statistic, random sampling,
expected value, etc. (Analyze)
- Drawing statistical
conclusions
Distinguish between numeric and
analytical studies. Assess the
validity of statistical conclusions
by analyzing the assumptions used
and the robustness of the technique
used. (Evaluate)
- Probability terms and
concepts
Describe and apply concepts such as
independence, mutually exclusive,
multiplication rules, complementary
probability, joint occurrence of
events, etc. (Apply)
- Probability Distributions
- Continuous distributions
Define and distinguish between these
distributions: normal, uniform,
bivariate normal, exponential,
lognormal, Weibull, chi square,
Student’s t, F, etc. (Analyze)
- Discrete distributions
Define and distinguish between these
distributions: binomial, Poisson,
hypergeometric, multinomial, etc.
(Analyze)
- Statistical Decision-Making
- Point estimates and
confidence intervals
Define, describe, and assess the
efficiency and bias of estimators.
Calculate and interpret standard
error, tolerance intervals, and
confidence intervals. (Evaluate)
- Hypothesis testing
Define, interpret, and apply
hypothesis tests for means,
variances, and proportions. Apply
and interpret the concepts of
significance level, power, type I
and type II errors. Define and
distinguish between statistical and
practical significance. (Evaluate)
- Paired-comparison tests
Define and use paired-comparison
(parametric) hypothesis tests, and
interpret the results. (Apply)
- Goodness-of-fit tests
Define and use chi square and other
goodness-of-fit tests, and interpret
the results. (Apply)
- Analysis of variance
(ANOVA)
Define and use ANOVAs and interpret
the results. (Analyze)
- Contingency tables
Define, construct, and use
contingency tables to evaluate
statistical significance. (Analyze)
- Relationships Between
Variables
- Linear regression
Calculate the regression equation
for simple regressions and least
squares estimates. Construct and
interpret hypothesis tests for
regression statistics. Use
regression models for estimation and
prediction, and analyze the
uncertainty in the estimate. [Note:
Non-linear models and parameters
will not be tested.] (Analyze)
- Simple linear
correlation
Calculate the correlation
coefficient and its confidence
interval, and construct and
interpret a hypothesis test for
correlation statistics. [Note:
Serial correlation will not be
tested.] (Analyze)
- Time-series analysis
Define, describe, and use
time-series analysis including
moving average, and interpret
time-series graphs to identify
trends and seasonal or cyclical
variation. (Analyze)
- Statistical Process Control
(SPC)
- Objectives and benefits
Identify and explain objectives and
benefits of SPC such as assessing
process performance. (Understand)
- Common and special
causes
Describe, identify, and distinguish
between these types of causes.
(Analyze)
- Selection of variable
Identify and select characteristics
for monitoring by control chart.
(Analyze)
- Rational subgrouping
Define and apply the principles of
rational subgrouping. (Apply)
- Control charts
Identify, select, construct, and use
various control charts, including
-R, -s, individuals and moving range
(ImR or XmR), moving average and
moving range (MamR), p, np, c, u,
and CUSUM charts. (Analyze)
- Control chart analysis
Read and interpret control charts,
use rules for determining
statistical control. (Evaluate)
- PRE-control charts
Define and describe how these charts
differ from other control charts and
how they should be used. (Apply)
- Short-run SPC
Identify, define, and use short-run
SPC rules. (Apply)
- Process and Performance
Capability
- Process capability
studies
Define, describe, calculate, and use
process capability studies,
including identifying
characteristics, specifications, and
tolerances, developing sampling
plans for such studies, establishing
statistical control, etc. (Analyze)
- Process performance vs.
specifications
Distinguish between natural process
limits and specification limits, and
calculate percent defective.
(Analyze)
- Process capability
indices
Define, select, and calculate Cp,
Cpk, Cpm, and Cr, and evaluate
process capability. (Evaluate)
- Process performance
indices
Define, select, and calculate Pp and
Ppk and evaluate process
performance. (Evaluate)
- Design and Analysis of
Experiments
- Terminology
Define terms such as dependent and
independent variables, factors,
levels, response, treatment, error,
and replication. (Understand)
- Planning and organizing
experiments
Define, describe, and apply the
basic elements of designed
experiments, including determining
the experiment objective, selecting
factors, responses, and measurement
methods, choosing the appropriate
design, etc. (Analyze)
- Design principles
Define and apply the principles of
power and sample size, balance,
replication, order, efficiency,
randomization, blocking,
interaction, and confounding.
(Apply)
- One-factor experiments
Construct one-factor experiments
such as completely randomized,
randomized block, and Latin square
designs, and use computational and
graphical methods to analyze the
significance of results. (Analyze)
- Full-factorial
experiments
Construct full-factorial designs and
use computational and graphical
methods to analyze the significance
of results. (Analyze)
- Two-level fractional
factorial experiments
Construct two-level fractional
factorial designs (including Taguchi
designs) and apply computational and
graphical methods to analyze the
significance of results. (Analyze)
Levels of Cognition
based on Bloom’s Taxonomy – Revised (2001)
In addition to content
specifics, the subtext for each topic in this
BOK also indicates the intended
complexity level of the test questions
for that topic. These levels are based on
“Levels of Cognition” (from Bloom’s Taxonomy –
Revised, 2001) and are presented below in rank
order, from least complex to most complex.
Remember
Recall or recognize terms, definitions, facts,
ideas, materials, patterns, sequences, methods,
principles, etc.
Understand
Read and understand descriptions,
communications, reports, tables, diagrams,
directions, regulations, etc.
Apply
Know when and how to use ideas, procedures,
methods, formulas, principles, theories, etc.
Analyze
Break down information into its constituent
parts and recognize their relationship to one
another and how they are organized; identify
sublevel factors or salient data from a complex
scenario.
Evaluate
Make judgments about the value of proposed
ideas, solutions, etc., by comparing the
proposal to specific criteria or standards.
Create
Put parts or elements together in such a way as
to reveal a pattern or structure not clearly
there before; identify which data or information
from a complex set is appropriate to examine
further or from which supported conclusions can
be drawn.
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