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ICTD International Centre for Training and Development

Recent Advances in Reliability and Quality in Design

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Description

This is an intense five day class with special topics included tailored to class interest. The course organization is compact and designed to be able to move at a rapid pace. It includes course material and reliability software that makes learning fast. People are busy so the class is compacted to save downtime and get engineers and managers back in the office to use the tools that they have learned with learning maximized. However, this is not a birds-eye view; the material provides depth and exposure to the industry's reliability and quality science.

We start by providing full explanation of how to grow reliability in a commercial environment and translate that into ROI dollars. Reliability growth starts in the design phase using tools like FMEA, reliability predictions, and reverse engineering. We move into the testing phase with describing how to demonstrate reliability with statistically significant tests. We also detail how to perform reliability growth tests such as HALT. A full or partial overview on HALT is available depending on class interest. Reliability statistical test and analysis

Course Objectives

Upon successful completion of this course, the delegates will be able to:

  • Demonstrate an understanding of the concepts of reliability engineering
  • Measure model times to failure using the appropriate probability distribution
  • Demonstrate an understanding of the relationship between the time to failure distribution, the reliability function, and the hazard rate
  • Determine a life test, estimate reliability values from the test data and set confidence limits on the results
  • Use the design tools necessary to ensure a reliable product including prediction, allocation and FMEA
  • Understand the differences in analyzing the reliability of a repairable and a non-repairable system

Course Outline

Day 1

System Reliability Computing: Central Limit Theorem for a Family of Reliability Measures

  • Introduction
  • Fuzzy Sets Concepts
  • A Central Limit Theorem for Gauge Measures and Related Results
  • Further Examples and an Application
  • An Application
  • Conclusion

Modeling and Reliability Evaluation of Multi-State K-out-of-N Systems

  • Introduction
  • Reliability Evaluation of Multi-State K-out-of-N Systems
  • Conclusions

On Weighted Least Squares Estimation for the Parameters of Weibull Distribution

  • Introduction
  • Basic Concepts in Lifetime Data Analysis
  • Common Estimation Methods for Weibull Distribution
  • Weighted Least Squares Estimation Methods and Related Work
  • An Improved Method for Calculating Weights
  • Discussions
  • Conclusions

Periodic and Sequential Imperfect Preventive Maintenance Policies for Cumulative Damage Models

  • Introduction
  • Periodic PM
  • Sequential PM
  • PM for a Finite Interval
  • Conclusions

Day 2

Some Alternative Approaches to System Reliability Modeling

  • Introduction
  • A New Bivariate Probability Densities Construction
  • Multivariate Extensions of the Bivariat Models
  • A Comparison with Freund, Marshall and Olkin, and some Other Models
  • The Transformation Method for the pdfs Construction
  • Extension of the Random Vector Models to Stochastic Processes
  • Discrete Time Interpretation
  • Stochastic Processes Memory
  • Application of k-Markovian Stochastic Processes
  • Maintenance Models
  • Additional Remarks
  • Some Analytic Examples

The Optimal Burn-in: State of the Art and New Advances for Cost Function Formulation

  • Introduction
  • State-of-art on Optimal Burn-in Research
  • Development of “After Burn-in Failure Treatment” (AFT) Cost Model
  • Conclusions

Reliability Engineering in Design:

Optimum Threshold Level of Degrading Systems Based on Sensor Observation

  • Introduction
  • Gamma Process Degradation Model
  • Imperfect Maintenance Model
  • Sensor Errors and Accuracy
  • Uptime Modeling
  • Threshold Level: System Availability Maximization
  • Threshold Level: Maintenance Cost Minimization
  • Conclusions

Weibull Data Analysis with Few or no Failures

  • Introduction
  • Theory
  • Examples
  • Simulation Study with Only Three Failures
  • Conclusions

Day 3

A Load-weighted Statistical Average Model of Fatigue Reliability

  • Introduction
  • Statistical Average Interpretation of SSI Model
  • A Statistical Load-weighted Average Model of Fatigue Reliability
  • Fatigue Life Distribution Under Constant Amplitude Cyclic Stress and Fatigue Reliability Calculation
  • Examples of Application
  • Conclusions

Markovian Performance Evaluation for Software System Availability with Processing Time Limit

  • Introduction
  • Markovian Software Availability Model
  • Model Analysis
  • Derivation of Software Performance Measures
  • Numerical Examples
  • Concluding Remarks

Failure Probability Estimation of Long Pipeline

  • Introduction
  • Segment Partition and System Strength Distribution
  • Pipeline Failure Probability Estimation and Failure Dependence Analysis
  • Pipeline Failure Probability Estimation
  • Upper Limit of Large-scale Series System Failure Probability
  • Pipeline Reliability Under Randomly Repeated Load
  • Conclusion

Software Reliability and Testing:

Software Fault Imputation in Noisy and Incomplete Measurement Data

  • Introduction
  • Empirical Datasets
  • Imputation Techniques
  • Missing Data Mechanisms
  • Experimental Design
  • Statistical Analysis
  • Conclusion

Day 4

A Linearized Growth Curve Model for Software Reliability Data Analysis

  • Introduction
  • Generalization of Growth Curve Models
  • Examples of Data Analysis and Discussion
  • Concluding Remarks

Software Reliability Model Considering Time-delay Fault Removal

  • Introduction
  • Model Formulation
  • Numerical Examples
  • Concluding Remarks

Heuristic Component Placement for Maximizing Software Reliability

  • Introduction
  • Overview
  • Analysis and Optimization Methodologies
  • Illustrations
  • Related Research
  • Conclusions and Future Research

Day 5

Software Reliability Growth Models Based on Component Characteristics

  • Introduction
  • Module Composition
  • Software Reliability Growth Modeling
  • Numerical Examples for Software Reliability Analysis
  • Concluding Remarks

Quality Engineering in Design:

Statistical Analysis of Appearance Quality for Automotive Rubber Products

  • Introduction
  • Description of Product and Defect Phenomenon
  • Identification of Bloom Phenomenon
  • Orthogonal Arrays
  • Analysis of Swell
  • Analysis of CS
  • Discriminant Analysis for Swell Measures
  • Multiple Regression Analysis for CS Measures
  • Concluding Remarks

Present Worth Design of Engineering Systems with Degrading Components

  • Introduction
  • Modeling of Time-variant Systems
  • Cumulative Distribution Function Modeling
  • Formulation of Economic Design Problems
  • Case Study

## Course Methodology

A variety of methodologies will be used during the course that includes:

  • (30%) Based on Case Studies
  • (30%) Techniques
  • (30%) Role Play
  • (10%) Concepts
  • Pre-test and Post-test
  • Variety of Learning Methods
  • Lectures
  • Case Studies and Self Questionaires
  • Group Work
  • Discussion
  • Presentation

Who should attend

This course is designed for practicing engineers, quality or reliability managers/engineers, production/design engineers and warranty analysts with engineering functions.

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