Reliability Analysis for Repairable Systems
Registration details...
Target Audience:
Maintenance, Reliability Professionals, Asset Management
Duration:
4 Days
Course Description:
This course covers basic statistical concepts of Reliability Digital Twin for both non-repairable and repairable components or equipment. Emphasis is placed on creating Reliability Digital Twins and performing simulations to improve productivity and enhance the company's financial bottom line.
Learning Objectives
- Apply statistical tools to characterize the reliability of non-repairable and repairable components or equipment
- To understand System Reliability Modelling concept for repairable system: Reliability Digital Twin
- Learn how to construct Reliability Digital Twin using software tools
- Derive and interpret simulation results for making the most optimized asset management decisions
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
Customer Base
Throughout the years, we have collaborated with numerous prominent companies, assisting them with their ongoing reliability analysis and CAPEX projects. Our enhanced comprehension of our customers has empowered us to swiftly transform industry challenges into improved software features. Furthermore, our extensive years of project experience have positioned us comfortably to tackle intricate technical issues with practical solutions.
