Last Updated S022021

MSR508

Unit Name DATA ANALYSIS AND STATISTICS
Unit Code MSR508
Unit Duration 1 Term (online) or 1 Semester (on-campus)
Award

Graduate Diploma of Engineering (Safety, Risk and Reliability)

Duration: 1 year

Master of Engineering (Safety, Risk and Reliability)

Duration: 2 years   

Year Level One
Unit Creator / Reviewer Keerthy Mysore | Arti Siddhpura | Kecheng Shen
Core/Elective: Core
Pre/Co-requisites Nil
Credit Points

3

Grad Dip total course credit points = 24

(3 credits x 8 (units))

Masters total course credit points = 48

(12 credits (Thesis) + 3 credits x 12 (units))

Mode of Delivery

Online or on-campus.

Combination of modes: Online synchronous lectures; asynchronous discussion groups, videos, remote and cloud-based labs (simulations); web and video conferencing tutorials. High emphasis on personal and group self-study.  

Unit Workload

Total student workload including “contact hours” = 10 hours per week:

Lecture – 1 hour

Tutorial Lecture - 1 hour

Practical / Lab - 1 hour (if applicable)

Personal Study recommended - 7 hours

Unit Description and General Aims

This unit focusses on Interpretation of Failure rates. Starting with a discussion on the differences between success and failure domains, the unit meanders through various topics such as sources of failure data, accuracy, confidence levels, Cumulative Poisson curves, Chi-square tests, and the bath-tub curve for constant failure rates and the Weibull distribution for variable failure rates. The unit concludes that the extremely wide variability of failure rates of identical components under identical conditions obviates the need for complex reliability prediction models.

Learning Outcomes

On successful completion of this Unit, students are expected to be able to:

1. Compare and contrast failure data from various sources in terms of reliability, accuracy and confidence levels.

2. Apply correction factors to failure data to make it “fit for purpose”

3. Apply appropriate failure data to real-life situations

4. Employ appropriate statistical methods for data analysis and deductions

5. Interpret system failure rates and appreciate their limitations

6. Discuss Field data collection and Reliability Growth Modelling

Student assessment

Assessment Type

When assessed

 

Weighting (% of total unit marks) Learning Outcomes Assessed

Assessment 1

Type: Multi-choice test (Proctored)

Word length: n/a

Topic: All material covered in the syllabus to date. Assessing terms and jargon, Data accuracy and measurement system

After Topic 3 15% Topic 1, 2, 3 (1, 2)

 

Assessment 2

Type: Mid-semester test (Proctored)

Example Questions: “Explain contingency table. Calculate binomial distribution.”

 

After

Topic 6

 25% Topic 4, 5, 6 (3, 4)

 

Assessment 3

Type: Group Case Study on Safety Instrumented Systems and presentation

Allocation of weighting:

15% - Report

5% - Presentation (Presentations to take place during Topic 12 tutorial)

 

Word length for Report: 1500

Develop, assemble and synthesise appropriate engineering and management elements within a major case study of statistical data analysis.

After

Topic 9

20% Topic 6, 7, 8, 9 (4, 5)

 

Assessment 4

Type: Safety and Risk Management Related Report (Final Project)

Word length: 2500

Example:

Report on statistical techniques used in Failure data analysis and the practical aspects of Reliability Growth Modelling.

A comparative study on failure data from various sources e.g., field failures, manufacturer’s data and cycle testing, with an attempt to account for the differences noticed. 

 

Word length: 2500

After Topic 12 35%

All Topics

(1 - 6)

Attendance

Continuous 5% 1-6

 

Prescribed and Recommended readings

Required textbook(s)

  1. D.J. Smith and K.G.L. Simpson, Safety critical systems handbook: a straightforward guide to functional safety: IEC 61508 (2010 edition) and related standards, 2010. (used in MSR507)

OR

  1. D. J. Smith, Reliability, Maintainability and Risk, 2005.
  2. Kubiak, T. M. Benbow, Donald W.. (2017). Certified Six Sigma Black Belt Handbook (3rd Edition). American Society for Quality (ASQ). Retrieved from https://app.knovel.com/hotlink/toc/id:kpCSSBBH02/certified-six-sigma-black/certified-six-sigma-black
  3. Ebeling, C. E. (2004). An introduction to reliability and maintainability engineering. Tata McGraw-Hill Education.
  4. Ayyub, B. M., & McCuen, R. H. (2016). Probability, statistics, and reliability for engineers and scientists. CRC press

 

Reference Materials

A number of peer-reviewed journals and websites (advised during lectures). Some examples are listed below.

  • Reliability growth – Statistical test and estimation methods, Australian standard AS IEC 61164-2008.
  • Equipment reliability – Reliability assessment methods, Australian standard AS IEC 62308– 2008.
  • IDC /EIT notes and Reference texts as advised.
  • Other material advised during the lectures

Unit Content

One topic is delivered per contact week.

 

Topic 1

Probability

  1. Basic Concepts
    1. Complementary Rule of Probability
    2. Addition Rule of Probability
    3. Contingency Tables
    4. Conditional Probability
    5. Independent and Dependent Events
    6. Mutually Exclusive Events
    7. Multiplication Rule of Probabilities
  2. Distributions
    1. Normal Distribution
    2. Poisson Distribution
    3. Binomial Distribution
    4. t-Distribution (also known as Student's t-Distribution)
    5. Exponential Distribution
    6. Lognormal Distribution
    7. Weibull Distribution

Topic 2

Basic Statistics

  1. Basic Statistical Terms
  2. Central Limit Theorem
  3. Descriptive Statistics
    1. Measures of Central Tendency
    2. Measures of Dispersion
    3. Other Useful Descriptive Statistics
    4.  Determining Quartiles
  4.  Graphical Methods
    1. Frequency Distribution
    2. Histogram
    3. Scatter Diagrams
    4. Normal Probability Plot

Topic 3

Measuring and Modelling Relationships between Variables

  1. Simple Linear Regression
  2. Value of the prediction equation
  3. Assumptions
  4. Checking assumptions through the residual plot
  5. Confidence Interval for the Regression Line

Topic 4

Field Data Collection and Feedback

  1. Reasons for Data Collection
  2. Information and Difficulties
  3. Spreadsheets and Databases
  4. Best Practice and Recommendations
  5. Analysis and Presentation of Results
  6. Examples of Failure Report Forms

Topic 5

Data accuracy, databases and confidence limits

  1. Data Accuracy
  2. Sources of Data
  3. Manufacturers' Data
  4. Anecdotal Data
  5. No-Fault-Found (NFF)
  6. Data Ranges
  7. Manufacturers' Data (Warranty Claims)
  8. Overall Conclusion

Topic 6

Basic concepts of reliability - I

  1. The study of Reliability and Maintainability
  2. Concepts, terms and definitions
  3. Applications
  4. A brief history
  5. Reliability Engineering as a Profession

Topic 7

Basic concepts of reliability - II

  1. Defining Failure and Failure Modes
  2. Failure Rate Function
  3. Time to failure  and Time between failures
  4. Interrelationships of Terms
  5. Bathtub Curve
  6. Conditional Reliability
  7. Times to Failure
  8. Down Time and Repair Time
  9. Availability, Unavailability and Probability of Failure on Demand
  10. Hazard and Risk-Related Terms
  11. Choosing the Appropriate Parameter

Topic  8

Distribution analysis/Weibull analysis

  1. Ranking of times to failure
  2. Probability plotting
  3. Estimate of the distribution parameters
  4. Goodness of fit test
  5. 3-parameter Weibull probability plot

Topic  9

Reliability Growth Modelling

 

  1. The CUSUM ((Cumulative Sum Chart) technique
  2. AMSAA (U.S. Army Materiel Systems Analysis Activity) model
  3. Duane Plots

Topic 10

Data accuracy, databases and confidence limits

  1. General procedure
  2. Confidence intervals on sample statistics
  3. Confidence interval for the mean
  4. Factors affecting confidence interval and sampling variation
  5. Sample size determination
  6. Relationship between decision parameters and type I and II errors

 

Topic 11

Interpreting data

  1. The four cases
  2. Inference and confidence levels
  3. The Chi-Square distribution and test
  4. Confidence interval of MTBF/MTTR with time termination
  5. Confidence interval of MTTR/MTTR with failure termination

Topic 12

Presentations and Unit Review

In the final week, students will prepare and present the main findings of their case study as part of Assessment 3. They will also have an opportunity to review the contents covered so far. Opportunities will be provided for a review of student work and to clarify any outstanding issues.  Instructors/facilitators may choose to cover a specialized topic if applicable to that cohort.

Software/Hardware Used

Software

  • Software: N/A

  • Version: N/A

  • Instructions:  N/A

  • Additional resources or files: N/A

Hardware

  • N/A