📊 Reliability Engineering: Weibull, RBD, Bearing Life & Availability Analysis

Move beyond maintenance strategy into quantitative reliability: model and predict failure with Weibull, size redundancy with block diagrams, calculate bearing life and availability, and optimise critical-spare stocking. The course is organized into 10 modules, ending with a final exam (pass mark 80%). It is independent, free exam-preparation training — not an official or accredited review course.

What you'll learn

• From maintenance types to predicting failure
• The bathtub curve and choosing a distribution
• Weibull analysis: shape, scale and B10 life
• MTBF, MTTR and the two availabilities
• Availability and downtime budgeting against SLA
• System reliability: series, parallel, k-out-of-n
• Rolling-bearing fatigue life (ISO 281, L10)
• Asset criticality ranking
• Spare-parts stocking: EOQ and reliability-based
• Putting it together: a worked reliability case

Learning objectives

• Interpret the bathtub curve and choose the correct failure distribution for infant-mortality, random and wear-out regimes.
• Fit and read a Weibull plot — derive the shape parameter β, scale parameter η and B10 life, and explain what each tells you about failure mode.
• Calculate MTBF and MTTR from field data and distinguish inherent from operational availability.
• Build an availability and downtime budget against an uptime or SLA target and allocate allowable downtime across subsystems.
• Model system reliability with reliability block diagrams for series, parallel and k-out-of-n redundancy.
• Compute rolling-bearing fatigue life using ISO 281 (L10 and L10h) from load and speed.
• Rank assets by criticality to focus reliability effort where it pays.
• Size critical-spare and consumable stock using EOQ and reliability-based (Poisson) inventory methods.