1. V. Reliability Testing (24 Questions)
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2. VI. Maintainability and Availability (15 Questions)
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3. VII. Data Collection and Use (18 Questions)
   1. A. Data collection 1. Types of data Identify and distinguish between various types of data (e.g., attributes vs. variable, discrete vs. continuous, censored vs. complete, univariate vs. multivariate). Select appropriate data types to meet various analysis objectives. (Evaluate) 2. Collection methods Identify appropriate methods and evaluate the results from surveys, automated tests, automated monitoring and reporting tools, etc., that are used to meet various data analysis objectives. (Evaluate)
      1. 3. Data management Describe key characteristics of a database (e.g., accuracy, completeness, update frequency). Specify the requirements for reliability-driven measurement systems and database plans, including consideration of the data collectors and users, and their functional responsibilities. (Evaluate)
   2. B. Data use 1. Data summary and reporting Examine collected data for accuracy and usefulness. Analyze, interpret, and summarize data for presentation using techniques such as trend analysis, Weibull, graphic representation, etc., based on data types, sources, and required output. (Create) 2. Preventive and corrective action Select and use various root cause and failure analysis tools to determine the causes of degradation or failure, and identify appropriate preventive or corrective actions to take in specific situations. (Evaluate) 3. Measures of effectiveness Use various data analysis tools to evaluate the effectiveness of preventive and corrective actions in improving reliability. (Evaluate) C. Failure analysis and correction 1. Failure analysis methods Describe methods such as mechanical, materials, and physical analysis, scanning electron microscopy (SEM), etc., that are used to identify failure mechanisms. (Understand) 2. Failure reporting, analysis, and corrective action system (FRACAS) Identify the elements necessary for a FRACAS to be effective, and demonstrate the importance of a closed-loop process that includes root cause investigation and follow up. (Apply)
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      4. 4. Reliability in product and process development Integrate reliability engineering techniques with other development activities, concurrent engineering, corporate improvement initiatives such as lean and six sigma methodologies, and emerging technologies. (Apply)
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      4. 4. Product lifecycle engineering Describe the impact various lifecycle stages (concept/design, introduction, growth, maturity, decline) have on reliability, and the cost issues (product maintenance, life expectation, software defect phase containment, etc.) associated with those stages. (Understand)
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      6. 6. Systems engineering and integration Describe how these processes are used to create requirements and prioritize design and development activities. (Understand)
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      3. 3. System safety Identify safety-related issues by analyzing customer feedback, design data, field data, and other information. Use risk management tools (e.g., hazard analysis, FMEA, FTA, risk matrix) to identify and prioritize safety concerns, and identify steps that will minimize the misuse of products and processes. (Analyze)
5. II. Probability and Statistics for Reliability (27 Questions)
   1. A. Basic concepts
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      5. 5. Non-parametric statistical methods Apply non-parametric statistical methods, including median, Kaplan-Meier, Mann- Whitney, etc., in various situations. (Apply)
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      7. 7. 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. (Understand)
   2. B. Statistical Inference
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6. III. Reliability in Design and Development (26 Questions)
   1. A. Reliability design techniques
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   2. B. Parts and Systems Management
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7. IV. Reliability Modeling and Predictions (22 Questions)
   1. A. Reliability Modeling
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   2. B. Reliability Predictions
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