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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 Reliability 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 Engineer, Reliability
Engineer, Software Quality Engineer, or Quality Manager, experience used to qualify for
certification in these fields often applies to certification as a Reliability 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 persons-ASQ members, members of a foreign affiliate
society, or members of another recognized professional society-verifying 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 Reliability Engineer examination is a one-part, 150-question, four-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 March and mid-October,
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.
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Body of
Knowledge
The following is an outline of the topics that constitute the Body of
Knowledge for Reliability Engineering.
- RELIABILITY MANAGEMENT (19 Questions)
- Strategic management
- Benefits of reliability engineering
Demonstrate how reliability engineering techniques and methods improve programs,
processes, products, and services. (Synthesis)
- Interrelationship of quality and reliability
Define and describe quality and reliability and how they relate to each other.
(Comprehension)
- Role of the reliability function in the organization
Demonstrate how reliability professionals can apply their techniques and interact
effectively with marketing, safety and product liability, engineering, manufacturing,
logistics, etc. (Analysis)
- Reliability in product and process development
Integrate reliability engineering techniques with other development activities (e.g.,
concurrent engineering). (Synthesis)
- Failure consequence and liability management
Use liability and consequence limitation objectives to determine reliability acceptance
criteria, and identify development and test methods that verify and validate these
criteria. (Application)
- Life-cycle cost planning
Determine the impact of failures in terms of service and cost (both tangible and
intangible) throughout a product's life-cycle. (Analysis)
- Customer needs assessment
Describe how various feedback mechanisms (e.g., QFD, prototyping, beta testing) help
determine customer needs and specify product and service requirements. (Comprehension)
- Project management
Interpret basic project management tools and techniques, such as Gantt chart, PERT chart,
critical path, resource planning, etc. (Comprehension)
- Reliability program management
- Terminology
Identify and define basic reliability terms such as MTTF, MTBF, MTTR, availability,
failure rate, dependability, maintainability, etc. (Analysis)
- Elements of a reliability program
Use customer requirements and other inputs to develop a reliability program including
elements such as design for reliability, progress assessment, FRACAS, monitoring and
tracking components, customer satisfaction and other feedback, etc. (Evaluation)
- Product life-cycle and costs
Identify the various life-cycle stages and their relationship to reliability, and analyze
various cost-related issues including product maintenance, life expectation, duty cycle,
software defect phase containment, etc. (Analysis)
- Design evaluation
Plan and implement product and process design evaluations to assess reliability at various
life-cycle stages using validation, verification, or other review techniques. (Evaluation)
- Requirements management
Describe how requirements management methods are used to help prioritize design and
development activities. (Comprehension)
- Reliability training programs
Demonstrate the need for training, develop a training plan, and evaluate training
effectiveness. (Application)
- Product safety and liability
- Roles and responsibilities
Define and describe the roles and responsibilities of a reliability engineer in terms of
safety and product liability. (Application)
- Ethical issues
Identify appropriate ethical behaviors for a reliability engineer in various situations.
(Evaluation)
- System safety program
Identify safety-related issues by analyzing customer feedback, design data, field data,
and other information sources. Use risk assessment tools such as hazard analysis, FMEA,
FMECA, PRAT, FTA, etc., to identify and prioritize safety concerns, and identify steps to
idiot-proofing products and processes to minimize risk exposure. (Analysis)
- PROBABILITY AND STATISTICS FOR RELIABILITY (25 Questions)
- Basic concepts
- Statistical terms
Define and use basic terms such as population, parameter, statistic, random sample, the
central limit theorem, etc., and compute expected values. (Application)
- Basic probability concepts
Define and use basic probability concepts such as independence, mutually exclusive,
complementary and conditional probability, joint occurrence of events, etc., and compute
expected values. (Application)
- Discrete and continuous probability distributions
Describe, apply, and distinguish between various distributions (binomial, Poisson,
exponential, Weibull, normal, log-normal, etc.) and their functions (cumulative
distribution functions (CDFs), probability density functions (PDFs), hazard functions,
etc.). Apply these distributions and functions to related concepts such as the bathtub
curve.(Evaluation)
- Statistical process control (SPC)
Define various SPC terms and describe how SPC is related to reliability. (Comprehension)
- Statistical inference
- Point and interval estimates of parameters
Define and interpret these estimates. Obtain them using probability plots, maximum
likelihood methods, etc. Analyze the efficiency and bias of the estimators. (Evaluation)
- Statistical interval estimates
Compute confidence intervals, tolerance intervals, etc., and draw conclusions from the
results. (Analysis)
- Hypothesis testing (parametric and non-parametric)
Apply hypothesis testing for parameters such as means, variance, and proportions. Apply
and interpret significance levels and Type I and Type II errors for accepting/rejecting
the null hypothesis. (Analysis)
- Bayesian technique
Describe the advantages and limitations of this technique. Define elements including
prior, likelihood, and posterior probability distributions, and compute values using the
Bayes formula. (Application)
- RELIABILITY IN DESIGN AND DEVELOPMENT (25 Questions)
- Reliability design techniques
- Use factors
Identify and characterize various use factors (e.g., temperature, humidity, vibration,
corrosives, pollutants) and stresses (e.g., severity of service, electrostatic discharge
(ESD), radio frequency interference (RFI), throughput) to which a product may be
subjected. (Synthesis)
- Stress-strength analysis
Apply this technique and interpret the results. (Evaluation).
- Failure mode effects analysis (FMEA) in design
Apply the techniques and concepts and evaluate the results of FMEA during the design
phase. (Evaluation) [NOTE: Identifying and using this tool for other aspects of
reliability are covered in VII.C.1.]
- Failure mode effects and criticality analysis (FMECA) in design
Apply the techniques and concepts and evaluate the results of FMECA during the design
phase. (Evaluation) [NOTE: Identifying and using this tool for other aspects of
reliability are covered in VII.C.2.]
- Fault tree analysis (FTA) in design
Apply this technique at the design stage to eliminate or minimize undesired events.
(Analysis)
[NOTE: Identifying and using the symbols and rules of FTA are covered in VII.C.3.]
- Tolerance and worst-case analyses
Use various analysis techniques (e.g., root-sum squared, extreme value, statistical
tolerancing) to characterize variation that affects reliability. (Evaluation)
- Robust-design approaches
Define terms such as independent and dependent variables, factors, levels, responses,
treatment, error, replication, etc. Plan and conduct design of experiments
(full-factorial, fractional factorial, etc.) or other methods. Analyze the results and use
them to achieve robustness. (Evaluation)
- Human factors reliability
Describe how human factors influence the use and performance of products and processes.
(Comprehension)
- Design for X (DFX)
Apply tools and techniques to enhance a product's producibility and serviceability,
including design for assembly, service, manufacturability, testability, etc. (Evaluation)
- Parts and systems management
- Parts selection
Apply techniques such as parts standardization, parts reduction, parallel model, software
reuse, etc., to improve reliability in products, systems, and processes. (Application)
- Material selection and control
Apply probabilistic methods for proper selection of materials. (Application)
- Derating methods and principles
Use methods such as S-N diagram, stress-life relationship, etc., to determine the
relationship between applied stress and rated value . (Application)
- Establishing specifications
Identify various terms related to reliability, maintainability, and serviceability (e.g.,
MTBF, MTTF, MTBR, MTBUMA, service interval) as they relate to product specifications.
- RELIABILITY MODELING AND PREDICTIONS (23 Questions)
- Reliability modeling
- Sources of reliability data
Identify and describe various types of data (e.g., public, common, in-house data) and
their advantages and limitations, and use data from various sources (prototype,
development, test, field, etc.) to measure and enhance product reliability. (Analysis)
- Reliability block diagrams and models
Describe, select, and use various types of block diagrams and models (e.g., series,
parallel, partial redundancy, time-dependent modeling) and analyze them for reliability.
(Evaluation)
- Simulation techniques
Identify, select, and apply various simulation methods (e.g., Monte Carlo, Markov) and
describe their advantages and limitations. (Analysis)
- Reliability predictions
- Part count predictions and part stress analysis
Use parts failure rate data to estimate system- and subsystem-level reliability.
(Analysis)
- Advantages and limitations of reliability predictions
Demonstrate the advantages and limitations of reliability predictions, how they can be
used to maintain or improve reliability, and how they relate to and can be used with field
reliability data. (Application)
- Reliability prediction methods for repairable and non-repairable devices
Identify and use appropriate prediction methods for these types of devices and systems.
(Application)
- Reliability apportionment/allocation
Describe the purpose of reliability apportionment/allocation and its relationship to
subsystem requirements, and identify when to use equal apportionment or other techniques.
(Analysis)
- RELIABILITY TESTING (23 Questions)
- Reliability test planning
- Elements of a reliability test plan
Determine the appropriate elements and reliability test strategies for various development
phases. (Analysis)
- Types and applications of reliability testing
Identify and evaluate the appropriateness and limitations of various reliability test
strategies within available resource constraints. (Evaluation)
- Test environment considerations
Evaluate the application environment (including combinations of stresses) to determine the
appropriate reliability test environment. (Evaluation)
- Development testing
Assess the purpose, advantages, and limitations of each of the following types of tests,
and use common models to develop test plans, evaluate risks, and interpret test results.
(Evaluation)
- Accelerated life tests (e.g., single-stress, multiple-stress, sequential stress)
- Step-stress testing (e.g., HALT)
- Reliability growth testing (e.g., Duane, AMSAA, TAAF)
- Software testing (e.g., white-box, fault-injection)
- Product testing
Assess the purpose, advantages, and limitations of each of the following types of tests,
and use common models to develop test plans, evaluate risks, and interpret test results.
(Evaluation)
- Qualification/demonstration testing (e.g., sequential tests, fixed-length tests)
- Product reliability acceptance testing (PRAT)
- Stress screening (e.g., ESS, HASS, burn-in tests)
- Attribute testing (e.g., binomial, hypergeometric)
- Degradation testing (e.g., Arrhenius)
- Software testing (e.g., black-box, operational profile)
- MAINTAINABILITY AND AVAILABILITY (17 Questions)
- Management strategies
- Maintainability and availability planning
Develop maintainability and availability plans that support reliability goals and
objectives. (Application)
- Maintenance strategies
Identify the advantages and limitations of various maintenance strategies (e.g.,
reliability-centered maintenance (RCM), predictive maintenance, condition-based
maintenance), and determine which strategy to use in specific situations. (Analysis).
- Maintainability apportionment/allocation
Describe the purpose of maintainability apportionment/allocation and its relationship to
system and subsystem requirements, and determine when to modify the maintainability
strategy to achieve maintainability goals. (Synthesis)
- Availability tradeoffs
Identify various types of availability (e.g., inherent availability, operational
availability), and evaluate the reliability/maintainability tradeoffs associated with
achieving availability goals. (Evaluation)
- Analyses
- Maintenance time distributions
Determine the applicable distributions (e.g., log-normal, Weibull) for maintenance times.
(Analysis)
- Preventive maintenance (PM) analysis
Identify the elements of PM analysis (e.g., types of PM tasks, optimum PM intervals, items
for which PM is not applicable) and apply them in specific situations. (Analysis)
- Corrective maintenance analysis
Identify the elements of corrective maintenance analysis (e.g., fault-isolation time,
repair/replace time, skill level, crew hours) and apply them in specific situations.
(Analysis)
- Testability
Identify testability requirements and use various methods (e.g., built in tests (BITs), no
fault found, retest okay, false-alarm rates, software testability) to achieve reliability
goals. (Analysis)
- Spare parts strategy
Evaluate the relationship between spare parts requirements and maintainability and
availability. (Evaluation)
- DATA COLLECTION AND USE (18 Questions)
- Data collection
- Types of data
Identify, define, classify, and compare various data types (e.g., variables vs.
attributes, censored vs. uncensored). (Evaluation)
- Data sources
Evaluate the appropriateness of various data sources such as field, in-house, environment,
location, test specification, failure modes, failure mechanisms, time at failure, etc.
(Evaluation)
- Collection methods
Identify elements of data collection methods such as surveys, automated tests, automated
monitoring and reporting, etc. (Application)
- Data management
Identify the requirements for an organization-wide product-failure database, including
which user groups (e.g., production, research, field service, supplier relations,
purchasing, business management/accounting) will use the database and how the information
interests and needs of those groups can conflict. Identify and distinguish between the
level of detail each user group requires, and explain how reporting formats, coding
schemes, and other structural components of the database system can influence the
usefulness of the data over time and throughout the organization. (Evaluation)
- Data use
- Data summarization
Analyze, evaluate, and summarize data using techniques such as trend analysis, Weibull,
graphic representation, etc., based on data types, sources, and required output.
(Evaluation)
- Preventive and corrective action
Select and use various root cause and data (failure) analysis tools to determine
degradation or failure causes, and identify various preventive or corrective actions to
take in specific situations. (Evaluation)
- Measures of effectiveness
Select and use various data analysis tools to evaluate the effectiveness of preventive and
corrective actions. (Synthesis)
- Data and failure analysis tools
- Failure mode and effects analysis (FMEA)
Identify the components and steps used to develop a FMEA, and use this tool to analyze
problems found in various situations. (Evaluation)
- Failure mode, effects, and criticality analysis (FMECA)
Distinguish this analysis tool from FMEA, and use it to evaluate the likelihood of certain
effects and their criticality (including identifying and applying various levels of
severity) in specific situations. (Evaluation)
- Fault tree analysis (FTA) and Success tree analysis (STA)
Identify and use the event and logic symbols and rules of these tools to determine the
root cause of product failures or the steps necessary to ensure product success.
(Evaluation)
- Failure reporting, analysis, and corrective action system (FRACAS)
Identify the elements necessary for a FRACAS to be effective. (Application)
NOTE: Approximately 20% of the CRE exam will require candidates to perform
mathematical functions.
Six Levels of Cognition based on Blooms
Taxonomy (1956)
In addition to content specifics, the subtext detail also indicates the intended
complexity level of the test questions for that topic. These levels are based on
Levels of Cognition (from Blooms Taxonomy, 1956) and are presented below
in rank order, from least complex to most complex.
Knowledge Level
(Also commonly referred to as recognition, recall, or rote knowledge.) Being able to
remember or recognize terminology, definitions, facts, ideas, materials, patterns,
sequences, methodologies, principles, etc.
Comprehension Level
Being able to read and understand descriptions, communications, reports, tables, diagrams,
directions, regulations, etc.
Application Level
Being able to apply ideas, procedures, methods, formulas, principles, theories, etc., in
job-related situations
Analysis
Being able to break down information into its constituent parts and recognize the
parts relationship to one another and how they are organized; identify sublevel
factors or salient data from a complex scenario
Synthesis
Being able to put parts or elements together in such a way as to show 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
Evaluation
Being able to make judgments regarding the value of proposed ideas, solutions,
methodologies, etc., by using appropriate criteria or standards to estimate accuracy,
effectiveness, economic benefits, etc.
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Sample
Questions
- Which of the following is best defined as the practice of using
parallel components and subsystems?
- Maintainability
- Reliability
- Optimization
- Redundancy
- Balancing a reliability requirement against other design parameters
such as performance, cost, or schedule, and then analyzing the consequences of placing
special emphasis on one of these factors is called
- reliability allocation
- reliability predictions
- trade-off decisions
- system modeling
- Software reliability planning includes all of the following EXCEPT
- selecting models for data analysis and prediction
- modeling acquisition of computer software systems
- trade-offs of general purpose programs vs. commercially available
programs
- trade-offs involving cost, schedule, and failure intensity of software
products
- The lifetime of a mechanical lifter is normally distributed with a
mean of 100 hours and a standard deviation of 3 hours. What is the reliability of the
lifter at 106 hours?
- 0.0228
- 0.0570
- 0.9430
- 0.9772
- In an analysis of variance, which of the following distributions is
the basis for determining whether the variance estimates are all from the same population?
- Chi square
- Student's t
- Normal
- F
- A full factorial design of experiments has four factors. The first
factor has two levels, the second factor has three levels, the third factor has two
levels, and the final factor has four levels. How many runs are are required for this
analysis?
- 16
- 48
- 192
- 256
- In a certain application, two identical transducers are used to
measure the vacuum in a system. The system is considered to have failed if either of the
vacuums read by the transducers varies from the standard by more than 10 mm Hg. Which of
the following is the correct reliability logic block diagram for the transducer assembly?

- On the basis of the fault tree below, what is the likelihood of the
top event occurring?
- 0.0044
- 0.2600
- 0.3000
- 0.5200
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- Assuming perfect switching and perfect starting, which of the
following systems has the longest mean life if each system consisits of n units
with identical reliability?
- A series system
- A parallel system
- A k out of n system
- A cold standby system
Questions 10-12 refer to the following situation:
A high incidence of failures has developed during aircraft acceptance
testing over the last several months. The identified failure is that an instrument panel
light has malfunctioned on 6 of the last 10 aircraft tested. This problem needs to be
investigated and a Failure Reporting and Corrective Action System (FRACAS) needs to be
completed without stopping aircraft production.
- The first step of the investigation should be to
- collect additional data on similar events over the last two years
- conduct failure analysis to determine the failure mode and mechanism
- conduct surveillance testing on suspect components
- establish a cross-functional team to brainstorm on the cause and effect
- If the cause of the failure is determined to be a faulty
subassembly manufactured only by a single supplier, and this situation is threatening to
shut down aircraft production, the next step should be to
- visit the supplier to assist in determining the root cause of the problem
- initiate a supplier corrective action and return all of the unsorted
inventory
- issue a Government and Industry Data Exchange Program (GIDEP) alert
- update the inspection instruction and retrain receiving inspection
- If a corrective action notice was sent to the supplier of a
faulty subassembly, and the supplier's response states that the root cause is simply an
operation error, the next step should be to
- accept the response and close the FRACAS
- visit the supplier to develop a better understanding of the root cause
- issue a Government and Industry Data Exchange Program (GIDEP) alert
- being looking for a new supplier
- Which of the following is an appropriate use for experimental design?
- Establishing product requirements
- Developing a fault-tree analysis
- Ensuring the robust design of a product
- Analyzing customer complaint reports
- Which of the following is NOT considered good practice in reliability
design?
- Using proven parts
- Using series design
- Using failure mode and effects analysis (FMEA)
- Simplifying item configuration
- According to Taguchi, robustly designed experiments should employ all
of the following techniques EXCEPT
- inner and outer arrays
- signal-to-noise ratios
- linear graphs
- fold-over capabilities
- Which of the following measures can be used to find a quick
approximation of the availability of a system?
- Mean time to failure (MTTF) and mean time to repair (MTTR)
- Failure rate and failure mode
- Mission time and failure rate
- Downtime and time to repair
- The investment in automated test equipment is often justified under
which of the following circumstances
- Numerous tests must be performed.
- Repair times must be short.
- Conformance records are required.
- Traceable records are required.
- For a company operating multiple units of production equipment, the
observed failure rate is 42 x 10-6 failures per operating hour, and the
preventive maintenance rate is 320 x 10-6 actions per hour. What is the mean
time between corrective and preventive maintenance (MTBM)?
- 2,688.2 hr
- 2,762.4 hr
- 2,840.9 hr
- 26,935.0 hr
- All of the following are purposes of a production reliability
assurance test (PRAT) EXCEPT
- detect significant shifts between the as-built reliability requirements
and the as-assigned reliability requirements
- assess performance against reliability requirements
- assess actual product reliability against reliability requirements
- minimize the need for specific process controls
- The primary aim of sequential-life testing is to determine
- the probability density function of failures
- the mean time between failures (MTBF)
- whether a lot meets the reliability goal
- whether the stress-level variation is significant
- A small sample from a product population is subjected to multiple
levels of elevated stress. Which of the following could be used to model the life of the
product?
- Poisson process
- Pascal expansion
- Pareto rule
- Inverse power law
- Which of the following are important elements of the concept of risk?
- Frequency
- Schedule
- Damage
- I and II only
- I and III only
- II and III only
- I, II, and III
- Which of the following tools is used to analyze the safety of a
system?
- Fault-tree analysis
- Failure reporting and corrective action system
- Reliability allocation
- Environmental stress screening
- System-safety analytical techniques included all EXCEPT
- hazards analyses
- fault tree analyses
- logic diagram analyses
- design readiness reviews
- A component fails on the average of once every 4 years with 75% of the
failures observed to occur during stormy weather. If there are 12 hours of stormy weather
to every 240 hours of good weather, what are the failure rates for stormy and good weather
respectively?

- A go/no-go device is tested until it fails. If X is the number of
tests to first failure with no wear out present, and the probability of success on each
test is .99, then the probability that X is greater than 5 is:
- .9310
- .9410
- .9510
- .9610
- The best way to set an overall reliability goal is to
- write a specification calling for a product to have high realiability and
incorporate it into a contract
- put down specific numerical requirements for reliability, statements of
operating environments, and a definition of successful product performance
- insist that the goal be expressed in terms of mean-time-between-failures
for all components and assemblies
- indicate who would be at fault if the desired reliability is not obtained
during the warranty
- Weibull analysis is a way to quickly and easily analyze field data or
interval test data. The limits of the use of this technique include having a good estimate
for the:
- MTBF
- expected life
- shape parameter
- average quality of the production lots
- A system consists of 4 parallel units each having a reliability of
0.80. The system can still complete its mission with only 2 units functioning. If the
failure rate is constant and failures are independent then the system reliability will be:
- 0.4096
- 0.5376
- 0.8192
- 0.9728
- Given a reliability growth test in progress having accumulated 4
failures during 5000 test hours. Assume a growth rate of 0.3, what is the expected MTBF at
25,000 hours?
- 1250 hrs
- 1895 hrs
- 2026 hrs
- 3856 hrs
- Successful operation of System S, illustrated below, requires that at
least 1 out of 3 through paths be good. The 3 paths are ABC, AEF, and DEF.

If A and D have predicted reliability of .95, and B, C, E, and F each have a predicted
reliability of .99, find the predicted reliability (Rs) of the system.
- .996
- .997
- .998
- .999
- A Weibull distribution has been found to describe the reliability
distribution with characteristic life= 12,000 hrs., and shape parameter
If these are good parameters, at what time will
reliability decrease to .85?
- 2204 hrs
- 3503 hrs
- 4838 hrs
- 5254 hrs
Answers: |
| 1. d |
6. b |
11. a |
16. a |
21. d |
26. c |
31. a |
| 2. c |
7. a |
12. b |
17. a |
22. b |
27. b |
32. d |
| 3. b |
8. a |
13. c |
18. b |
23. a |
28. c |
|
| 4. a |
9. d |
14. b |
19. d |
24. d |
29. c |
| 5. d |
10. b |
15. d |
20. c |
25. a |
30. c |
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