Last Updated S012019


Unit Code MSR508
Unit Duration 1 Term (online) or 1 Semester (on-campus)

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
Core/Elective: Core
Pre/Co-requisites Nil
Credit Points


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

(e.g. Assignment - 2000 word essay (specify topic) Examination (specify length and format))

When assessed

(eg Week 5)

Weighting (% of total unit marks) Learning Outcomes Assessed

Assessment 1

Type: Quiz

Word length: n/a

Topic: Fundamental concepts of Failure and Reliability data and statistical methods overview  

Week 4 20% 1, 2

Assessment 2 - mid-semester test

Type: Report (Midterm Project)

[This will include a progress report; literature review, hypothesis, and methodology / conclusions]

Word length: 1000

Topic: 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.  

Week 7  25% 1, 2, 3, 4

Assessment 3

Type: Report (Final Project)

[If a continuation of the midterm, this should complete the report by adding sections on: methodology, implementation / evaluation, verification / validation, conclusion / challenges and recommendations / future work. If this is a new report, all headings from the midterm and the final reports must be included.]

Word length: 2000

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

Week 12 35% 5, 6

Practical Participation

Students will be presented curves and plots and will be quizzed on interpretation.

Continuous 15% 4, 5

 Class Participation

Continuous 5% 1-6


Prescribed and Recommended readings

Required Textbook(s)

D. J. Smith, K. G. L. Simpson, Safety Critical Systems Handbook (4th Edition) - A Straightforward Guide to Functional Safety, IEC 61508 (2010 Edition), IEC 61511 (2016 Edition) and Related Guidance - Including Machinery and other Industrial Sectors


D. J. Smith, Reliability, Maintainability and Risk, 9th Edition. Elsevier, 2017 - ISBN: 978-0081020104


Reference Materials

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, with the exception of part-time 24-week units, where one topic is delivered every two weeks.


Topic 1 and 2


1. Success and failure – domains and interpretation

2. Terms and jargon

3. Data accuracy, databases and confidence limits

Topic 3,4,5 and 6

Methods and mathematics

1. Statistical methods - Overview

2. Cumulative Poisson curves

3. Chi-square Distribution

4. Probability mathematics

Topic 7 and 8

Failure rates and methodologies

1. System failure rates

2. Methods - Overview

Topic 9 and 10

Failure and reliability modelling

1. Field failure data collection

2. Reliability Growth Modelling

Topic 11 and 12

Project and Unit Review

In the final weeks students will have an opportunity to review the contents covered so far. Opportunity 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.

Project – due at end of term


Software/Hardware Used


  • Software: N/A

  • Version: N/A

  • Instructions:  N/A

  • Additional resources or files: N/A


  • N/A