Certified Reliability Engineer Training: CRE Certification Course

The Certified Reliability Engineer (CRE) is a professional certification provided by the American Society for Quality (ASQ) to individuals who have shown their expertise in the field of reliability engineering. ASQ is a worldwide organization that promotes quality improvement initiatives in different industries.

The CRE certification aims to confirm an individual’s competence in the principles, practices, and methods of reliability engineering. It indicates that the certified engineer has met ASQ’s high standards and possesses a thorough grasp of reliability concepts and how they are applied in practical situations.

What Is Certified Reliability Engineer Training Course Overview?

This course will adhere to the established Body of Knowledge (BOK) for the certified Reliability Engineer (CRE) outlined by the ASQ. However, it will provide additional in-depth coverage of reliability analytics, reliability testing, and reliability statistical modeling. Overall, the Certified Reliability Engineer training course by PetroSync will cover the following aspects:

  1. Probability and Statistics For Reliability
  2. Reliability in Design and Development
  3. Modeling and Predicting Reliability
  4. Testing Reliability
  5. Maintainability and Availability
  6. Collecting and Utilizing Data
  7. Data Collection and Use

What Is the Certified Reliability Engineer Training Course Objective?

The objective of the Certified Reliability Engineer training course is to provide you with the necessary knowledge and skills to become certified professionals in the field of reliability engineering. Read on to know the whole objectives of the training course.

  1. Display a comprehension of the principles encompassed in reliability engineering.
  2. Utilize the suitable probability distribution to measure the duration until failure in models.
  3. Illustrate an understanding of the connection between the distribution of time until failure, the reliability function, and the hazard rate.
  4. Establish a life test, estimate reliability values based on the test data, and determine confidence intervals for the outcomes.
  5. Employ the necessary design tools to guarantee the reliability of a product, including prediction, allocation, and Failure Mode and Effects Analysis (FMEA).
  6. Recognize the distinctions when evaluating the reliability of systems that can be repaired versus those that cannot.

What Is Certified Reliability Engineer Training Course Outline?

The outline regarding Certified Reliability Engineer training course is listed down below. For a more detailed and complete outline, you can refer to PetroSync’s Certified Reliability Engineer training course.

Session 1: Reliability Management

  • Strategic management
  • Benefits of reliability engineering
  • Reliability engineering techniques and methods
  • Reliability in product and process development
  • Reliability engineering techniques integration with other development activities
  • Failure consequence and liability management
  • Warranty management
  • Basic reliability terms (e.g., MTTF, MTBF, MTTR, availability, failure rate, reliability, maintainability)
  • Types of risk
  • Design evaluation
  • Systems engineering and integration
  • Ethics, safety, and liability
  • Roles and responsibilities
  • System Safety
  • Identify safety-related issues by analyzing customer feedback, design data, field data, and other information
  • Case Study/Exercise: Performing FMEA studies as well as RCA (5 methods)

Session 2: Probability and Statistics for Reliability

  • Basic concepts
  • Statistical terms
  • Define and use terms such as population, parameter, statistic, sample, the central limit theorem, etc., and compute their values.
  • Basic probability concepts
  • Use basic probability concepts
  • Discrete and continuous probability distributions
  • Poison process models
  • Define and describe homogeneous and non-homogeneous Poisson process models (HPP and NHPP).
  • Non-parametric statistical methods
  • Apply non-parametric statistical methods, including median, Kaplan-Meier, Mann-Whitney, etc., in various situations.
  • Sample size determination
  • Use various theories, tables, and formulas to determine appropriate sample sizes for statistical and reliability testing.
  • Statistical process control (SPC) and process capability
  • Define and describe SPC and process capability studies (Cp, Cpk, etc.), their control charts, and how they are all related to reliability.
  • Statistical inference
  • Point estimates of parameters
  • Obtain point estimates of model parameters using probability plots, maximum likelihood methods, etc. Analyze the efficiency and bias of the estimators.
  • Statistical interval estimates

Session 3: Reliability in Design and Development

  • Reliability design techniques
  • Environmental and use factors
  • Identify environmental and use factors and stresses to which a product may be subjected.
  • Stress-strength analysis
  • Apply the stress-strength analysis method of computing the probability of failure, and interpret the results.
  • FMEA and FMECA
  • Define and distinguish between failure mode and effects analysis and failure mode, effects, and criticality analysis and apply these techniques in products, processes, and designs.
  • Common mode failure analysis
  • Describe this type of failure (also known as common cause mode failure) and how it affects design for reliability.
  • Fault tree analysis (FTA) and success tree analysis (STA)
  • Apply these techniques to develop models that can be used to evaluate undesirable (FTA) and desirable (STA) events.
  • Tolerance and worst-case analyses
  • Describe how tolerance and worst-case analyses (e.g., the root of sum of squares, extreme value) can be used to characterize variation that affects reliability.
  • Design of experiments
  • Fault tolerance
  • Define and describe fault tolerance and the reliability methods used to maintain system functionality.
  • Reliability optimization

Session 3: Reliability Modeling and Predictions

  • Reliability modeling
  • Sources and uses of reliability data
  • Describe sources of reliability data (prototype, development, test, field, warranty, published, etc.), their advantages and limitations, and how the data can be used to measure and enhance product reliability.
  • Reliability block diagrams and models
  • Generate and analyze various types of block diagrams and models, including series, parallel, partial redundancy, time-dependent, etc.
  • Physics of failure models
  • Identify various failure mechanisms (e.g., fracture, corrosion, memory corruption) and select appropriate theoretical models (e.g., Arrhenius, S-N curve) to assess their impact.
  • Simulation techniques
  • Describe the advantages and limitations of the Monte Carlo and Markov models.
  • Dynamic reliability
  • Describe dynamic reliability as it relates to failure criteria that change over time or under different conditions.
  • Reliability predictions
  • Part count predictions and part stress analysis
  • Use parts failure rate data to estimate system- and subsystem-level reliability.
  • Reliability prediction methods
  • Use various reliability prediction methods for both repairable and non-repairable components and systems, incorporating test and field reliability data when available
  • Case Study/Exercise: Data analytics and advanced topics (Markov chains and Monte Carlo simulation)

Session 4: Reliability Testing

  • Reliability test planning
  • Reliability test strategies
  • Create and apply the appropriate test strategies (e.g., truncation, test–to-failure, degradation) for various product development phases.
  • Test environment
  • Evaluate the environment in terms of system location and operational conditions to determine the most appropriate reliability test.
  • Testing during development
  • Describe 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.
  • Accelerated life tests (e.g., single-stress, multiple-stress, sequential stress, step-stress)
  • Discovery testing (e.g., HALT, margin tests, a sample size of 1),
  • Reliability growth testing (e.g., test, analyze, and fix (TAAF), Duane)
  • Software testing (e.g., white-box, black-box, operational profile, and fault-injection)
  • Product testing
  • Describe the purpose, advantages, and limitations of each of the following types of tests, and use common models to develop product test plans, evaluate risks, and interpret test results.
  • Qualification/demonstration testing (e.g., sequential tests, fixed-length tests)
  • Product reliability acceptance testing (PRAT)

Session 5: Maintainability and Availability

  • Management strategies
  • Planning
  • Develop plans for maintainability and availability that support reliability goals and objectives.
  • Maintenance strategies
  • Identify the advantages and limitations of various maintenance strategies (e.g., reliability-centered maintenance (RCM), predictive maintenance, repair or replace decision making), and determine which strategy to use in specific situations.
  • Availability tradeoffs
  • Describe various types of availability (e.g., inherent, operational), and the tradeoffs in reliability and maintainability that might be required to achieve availability goals.
  • Maintenance and testing analysis
  • Preventive maintenance (PM) analysis
  • Define and use PM tasks, optimum PM intervals, and other elements of this analysis, and identify situations in which PM analysis is not appropriate.
  • Corrective maintenance analysis
  • Describe the elements of corrective maintenance analysis (e.g., fault-isolation time, repair/replace time, skill level, crew hours) and apply them in specific situations.
  • Non-destructive evaluation

Data Collection and Use

  • Data collection
  • Types of data
  • Identify and distinguish between various types of data.
  • Collection methods
  • Data management
  • Describe key characteristics of a database
  • Data use
  • Data summary and reporting

Who Should Attend Certified Reliability Engineer Training Course?

The certified reliability engineer training course specifically benefit for but not limited to:

  • Maintenance and reliability professionals
  • Operations managers
  • Engineering managers

The PetroSync training course covers the established Body of Knowledge (BOK) outlined by the American Society for Quality (ASQ) for the CRE certification. You can receive in-depth coverage of reliability analytics, testing, and statistical modeling, equipping you with a comprehensive understanding of reliability engineering principles for certification preparation.

Aside from obtaining ASQ certification, PetroSync’s Certified Reliability Engineer (CRE) training course focuses on practical application by addressing reliability engineering techniques, methods, and tools used in product and process development. Participants learn how to perform failure mode and effects analysis (FMEA), conduct reliability testing, and optimize reliability through the design of experiments. Enroll in the Certified Reliability Engineer training course and excel in the field of reliability engineering with PetroSync!

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