Professional Training

Reliability Analysis for Repairable Systems

This course connects reliability data analysis with system modelling and simulation for repairable industrial assets. Participants progress from failure and downtime information to a Reliability Digital Twin that can evaluate availability, production loss and engineering alternatives.

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Target Audience:

Maintenance and reliability professionals, asset managers and engineers responsible for industrial systems

Duration:

4 Days

Learning Objectives

Analyse non-repairable and repairable reliability data using Life Data and Recurring Data methods

Build and examine a Reliability Digital Twin for a repairable industrial system

Interpret simulation results to compare maintenance, redundancy, resource and production-related alternatives

Topics Include

Reliability Data Analysis

  • Statistical concepts in reliability analysis
  • Reliability data types
  • Reliability metrics
  • Life distribution analysis
  • Recurring data analysis
  • Cost-Based Optimum Replacement and Optimum Overhaul

Reliability Digital Twin (Reliability Modelling) and Simulations

  • Basic constructs for Reliability Digital Twin
  • Reliability metric: Availability and Efficiency
  • Equipment production loss contribution and Improvement Allocations
  • Standby system
  • Spare inventory optimization
  • Process flows and storage buffer design optimization

Steps for RAM analysis

  • Functional Diagram and Digital Twin
  • Data Collection
  • Failure and Downtime Distributions
  • Simulation and Results

Course Leadership

Hongan Lin

Founder & Director, AssetStudio

Hongan designed the AeROS simulation engine and has taught repairable-system analysis and RAM modelling across Asia Pacific. The course connects reliability data, modelling assumptions and the interpretation of simulation results.

View Hongan's profile