Curriculum
- 6 Sections
- 49 Lessons
- 1 Day
Expand all sectionsCollapse all sections
- Foundations of Reliability Engineering10
- 1.1What is Reliability? (MTBF, MTTR, failure probability, bathtub curve)
- 1.2Failure rate behaviour & life cycle reliability
- 1.3Key reliability metrics: MTTF, reliability function, hazard rate
- 1.4Why reliability matters: warranties, safety, brand trust, competitive advantage
- 1.5Common failure modes in automotive, manufacturing, aerospace, electronics
- 1.6Cost of unreliability: recalls, downtime, customer dissatisfaction
- 1.7Reliability vs maintainability vs availability
- 1.8Industry examples of design failures due to reliability gaps
- 1.9Warranty failures & prediction errors from real OEM cases
- 1.10Exercise: Identify critical components in your product/process and estimate potential failure modes
- Reliability Statistics & Distributions8
- 2.1Failure distributions: Weibull, Exponential, Lognormal, Normal
- 2.2Statistical parameters: scale, shape, characteristic life
- 2.3Probability plots & interpretation
- 2.4Situational Awareness: Selecting the right distribution for real-world behaviour
- 2.5Common mistakes: poor data, incorrect model, sample size issues
- 2.6Example: Defect prediction from field return data
- 2.7Example: Reliability trends from warranty databases
- 2.8Exercise: Manually fit a Weibull distribution using provided sample data
- Life Data Analysis & Warranty Analytics9
- 3.1Life Data Analysis using Minitab-style workflow
- 3.2Right/left-censored data
- 3.3Reliability estimation from field returns
- 3.4Warranty curve fitting
- 3.5Situational Awareness: How companies misuse or misinterpret warranty data
- 3.6Detecting early-life failures vs wear-out failures
- 3.7Example: OEM case study: warranty spikes due to supplier variation
- 3.8Example: Cost-saving achieved by proactive reliability screening
- 3.9Exercise: Build a basic failure prediction curve using provided warranty dataset
- Reliability Block Diagrams (RBD) & System Reliability9
- 4.1Block diagram modelling (series, parallel, k-out-of-n, standby redundancy)
- 4.2Calculating overall system reliability
- 4.3How architecture impacts reliability
- 4.4Situational Awareness: Trade-offs in system design
- 4.5Cost vs reliability: optimal engineering decisions
- 4.6Design-for-reliability principles
- 4.7Example: Automotive subsystem reliability
- 4.8Example: Electronics system reliability improvement using redundancy
- 4.9Exercise: Create an RBD for your own subsystem & calculate system reliability
- Reliability Testing Methods & Sample Size Determination8
- 5.1ALT, HALT, HASS, ESS testing
- 5.2Stress screening & accelerated failure modelling
- 5.3Reliability test planning & acceptable quality levels
- 5.4Situational Awareness: How poor test planning leads to costly field failures
- 5.5Understanding test trade-offs: time, cost, confidence
- 5.6Example: Case: Accelerated life testing revealing design flaw
- 5.7Example: Case: Early-life failure detection via HALT
- 5.8Exercise: Determine required test sample size for 90% reliability at 95% confidence
- Applications, Case Studies & Final Simulation5
- 6.1Case Study: Warranty spike root-cause analysis
- 6.2Reliability improvement roadmap from a manufacturing plant
- 6.3Component failure due to incorrect distribution modelling
- 6.4Exercise: Use all concepts from the day to solve a real-world reliability challenge
- 6.5Interpret failure data, select distribution, estimate system reliability, recommend design/testing improvements, Present findings as an engineering recommendation report
Exercise: Use all concepts from the day to solve a real-world reliability challenge
Prev