|
|
The following information is provided
by the American Society for Quality (ASQ):
Certification Requirements
Education and/or Experience
You must have eight years of on-the-job experience in one or more of the
areas of the Certified Quality Engineer Body of Knowledge. A minimum of three years of
this experience must be in a decision-making position. Decision-making is
defined as the authority to define, execute, or control projects/processes and to be
responsible for the outcome. This may or may not include management or supervisory
positions.
If you are now or were previously certified by ASQ as a Quality Auditor, Reliability
Engineer, Software Quality Engineer, or Quality Manager, experience used to qualify for
certification in these fields applies to certification as a Quality Engineer.
If you have completed a degree* from a college, university, or technical school with
accreditation accepted by ASQ, part of the eight-year experience requirement will be
waived, as follows (only one of these waivers may be claimed):
- Diploma from a technical or trade schoolone year will be waived
- Associate degreetwo years waived
- Bachelors degreefour years waived
- Masters or doctoratefive years waived
*Degrees/diplomas from foreign educational institutions must be equivalent to degrees
from U.S. educational institutions.
Proof of Professionalism
Proof of professionalism may be demonstrated in one of three ways:
- Membership in ASQ, a foreign affiliate society of ASQ, or another society that is a
member of the American Association of Engineering Societies or the Accreditation Board for
Engineering and Technology
- Registration as a Professional Engineer
- The signatures of two personsASQ members, members of a foreign affiliate society,
or members of another recognized professional societyverifying that you are a
qualified practitioner of the quality sciences
Examination
Each certification candidate is required to pass a written examination that consists of
multiple choice questions that measure comprehension of the Body of Knowledge. The Quality
Engineer examination is a one-part, 160-question, five-hour exam and is offered in the
English language only.
Sample examination questions are included in the study guide.
Examinations are conducted twice a year, in early June and early December, by local ASQ
sections and foreign international organizations. All examinations are open-book. Each
participant must bring his or her own reference materials. Use of reference materials and
calculators is explained in the seating letter provided to applicants.
Please Note: The Body of Knowledge for certification is affected by
new technologies, policies, and the changing dynamics of manufacturing and service
industries. Changed versions of the examination based on the current Body of Knowledge are
used at each offering.
Back to Top
2006 Body of
Knowledge
The topics in this Body of Knowledge include subtext explanations and the cognitive
level at which the questions will be written. This information will provide useful
guidance for both the Exam Development Committee and the candidate preparing to take the
exam. The subtext is not intended to limit the subject matter or be all-inclusive of that
material that will be covered in the exam. It is meant to clarify the type of content that
will be included on the exam. The descriptor in parentheses at the end of each entry
refers to the maximum cognitive level at which the topic will be tested. A complete
description of cognitive levels is provided at the end of this document.
- 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
Demings 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 managements 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 facilitators 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 programs
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, Students 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 Blooms 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
Blooms 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.
Back to Top
Sample
Questions
Perfectionism in project management is LEAST likely to result in excess
- appraisal costs
- prevention costs
- internal failure costs
- external failure costs
Which three of the following are considered key elements of Demings quality
improvement strategy?
| I. |
An organizations overall quality is in the hands of the
organizations management. |
| II. |
The establishment of clear performance goals is required for effective
improvement efforts. |
| III. |
Quality problems are almost always a result of suboptimal systems, not
the people operating in them. |
| IV. |
Understanding variation and the use of statistical quality control
methods is the primary tool to improve processes and systems. |
- I, II, and III
- I, II, and IV
- I, III, and IV
- II, III, and IV
Which of the following tools are appropriate for quality engineer to use in
qualifying a process that has variable data?
| I. |
and R control chart |
| II. |
Histogram |
| III. |
c chart |
| IV. |
p chart |
- I and II only
- II and III only
- III and IV only
- I, II, and IV only
A process is stable at a 1.5 percent nonconformity rate where the plant produces
200,000 units per month. The final inspection captures 1 out of every 10 nonconformities
with only 1 out of every 25 noncomformities returned for warranty response. If the average
cost for each detected nonconformity is $50/unit, what is the cost of quality?
- $20,400
- $21,000
- $150,500
- $204,000
Which of the following costs decreases most dramatically as nonconformities approach
zero?
- Prevention
- Appraisal
- Manufacturing
- External failure
Design reviews are used to analyze all of the following EXCEPT
- cost of manufacturing
- cost of field maintenance
- performance at acceptable levels
- customer demand for the product
A major drawback of using histograms in process control is that they
- do not readily account for the factor of time
- are relatively difficult to construct and interpret
- require too many data points
- require too many intervals
A sequential operation can best be depicted graphically by means of
- a histogram
- a scatter diagram
- a flow diagram
- an interrelationship digraph
Two variables, x and y, are related in that x increases or decreases with y. Which of
the following could best be used to depict this relationship?
- A control chart
- A pareto chart
- A scatter diagram
- An interrelationship digraph
A quality information system is best defined as a
- historical collection of process and product data used to produce customer- or
government-required reports on quality
- set of systematic management reports that cover product and process functions and
usually include summary information on warranty frequency and the cost of quality
- method of collecting, storing, analyzing, and summarizing quality data to assist in
decision-making
- data collection and reporting system that tracks key product and process indicators of
quality
The correlation coefficient for the length and weight of units made by a process is
determined to be 0.27. If the process were adjusted to reduce the weight of each unit by
0.5 ounce, the correlation coefficient of the length and weight of the units made by the
new process would be equal to
- 0.50
- 0.27
- 0.23
- -0.23
A manufacturer of air conditioners wants to estimate the mean life (years from
installation to replacement) of its units. The error level is set at 0.5 year, a desired
probability (1 - ) of 95 percent is selected, and the standard
deviation of unit life is given as 6.0 years. If unit life is normally distributed, then
the required sample size for the desired estimate is equal to
- 283
- 291
- 554
- 585
| Alternative |
| Result |
A |
B |
Total |
| X |
I |
II |
80 |
| Y |
III |
IV |
120 |
| Total |
130 |
70 |
200 |
The correct value for the expected frequency of cell I in the contingency table
shown above is
- 28
- 42
- 52
- 78
For questions 14-16 refer to the following information.
Management has asked a team of quality engineers to evaluate a sister companys
quality system in order to qualify the sister company to manufacture a critical component
that has three characteristics that must be controlled. The characteristics are process
temperature, 195 ± 5°F; component mass, 100 grams ± 7 grams; and chemical component, 3
percent or less.
A technical report submitted by the sister company stated that all of the
characteristics complied with the companys specifications. During review of the
quality system, it was determined that the sister company does not have calibration
procedures, only one mass measurement per component is performed per shift, and the
analytical equipment for testing chemical accuracy does not work.
The team decided to measure 30 random samples from multiple shifts and to compare those
measurements with 30 random samples taken from the sister companys historical files.
The data are summarized in the table below. Based on this evaluation, the quality
engineers concluded that the sister company should not be used.
| |
Temperature (°F) |
Mass (grams) |
Chemical Analysis |
| |
New |
Historical |
New |
Historical |
New |
Historical |
| Mean |
194.4 |
195.0 |
98.3 |
100.0 |
2.62% |
None |
| Standard Deviation (n-1) |
3.58 |
0.9 |
4.13 |
2.37 |
0.29% |
None |
| Range |
188-202 |
193-197 |
91-107 |
95-105 |
2.0%-3.0% |
None |
| n |
30 |
30 |
30 |
30 |
30 |
|
Equality of the new and historical mean values can be tested most appropriately by
using which of the following tests?
- Grubbs
- t-test
- Chi-square
- Dixon
Based on the assumption that the temperature samples were taken from the same
population, the null hypothesis that there is no significant difference between means is
tested at the 5 percent level of significance. Which of the following gives the calculated
z-statistic and the appropriate decision regarding acceptance or rejection of the null
hypothesis?
- -0.89; accept
- -0.89; reject
- 0.67; accept
- 0.67; reject
A sample size of 30 individual values for each of the three characteristics
(temperature, mass, and chemical analysis) allows the
- use of the Dodge-Roming sampling plans
- use of an approximation to a Gaussian distribution
- use of the Bernoulli Process Theorem
- calculation of Pearsons coefficient of skewness
and have been computed for a series
of control chart sample subgroups. Which of the following expressions would be used to
calculate the spread of the individual units drawn from the production stream?
Of the following, the best way to prevent batches of material from becoming mixed or
misplaced is to establish
- operator check sheets
- a material review board
- statistical process control
- material and status control
The formal, documented, comprehensive, and systematic examination of a design that
ensures requirements are met, identifies problems, and proposes solutions is known as a
- quality review
- design review
- design examination
- failure mode, effect, and criticality analysis
A manufacturing control characteristic has a tighter tolerance than the product
requirement. Such a tolerance would be classified as
- nonfunctional
- end-use
- critical
- major
To determine the average number of nonconforming parts over time, which of the
following attribute control charts would be most appropriate?
- c chart
- u chart
- p chart
- np chart
A reference measurement is required to determine gage
- accuracy
- linearity
- stability
- repeatability
The variation in the average of the measurements made by different operators using
the same gage when measuring a characteristic on one part is known as gage
- linearity
- accuracy
- repeatability
- reproducibility
Which of the following analyses is most often used to study the potential failures in
a system?
- Failure analysis
- Fault tree analysis
- Reliability allocation analysis
- Pareto analysis
Answers: |
| 1. d |
7. a |
13. c |
19. b |
| 2. c |
8. c |
14. b |
20. a |
| 3. a |
9. c |
15. a |
21. d |
| 4. a |
10. c |
16. b |
22. a |
| 5. d |
11. b |
17. c |
23. d |
| 6. d |
12. c |
18. d |
24. b |
Back to Top |