RAM (Reliability, Availability, and Maintainability)

Background & About the Course

The RAM (Reliability, Availability, and Maintainability) study is a method used to assess the capabilities of production systems, both operational and in the design phase. As facilities and plants are utilized over extended periods, RAM studies provide insights into asset lifetime capabilities, enabling businesses to maximize return on investment.RAM is beneficial for evaluating production efficiency and lifetime capabilities of production facilities. Reliability and maintainability depend on the performance of each piece of equipment, helping to identify contributors to unavailability or “bad actor” equipment. Operational time and duration to restore are fundamental data points for determining the availability of production plants.

In the era of digitalization 4.0, RAM is often implemented with the aid of software (e.g., Maximo) to optimize efficiency and achieve key performance indicators (KPIs) set by management. The effectiveness of such software relies heavily on the quality of input data and the utilization of output data to enhance plant efficiency. This training will cover the philosophy and implementation of RAM, from data verification and validation to modeling and data application, with a focus on case studies using Maximo software.

Course Objectives
After the RAM training, participants will be able to:
– Read and process reliability data from Maximo.
– Present RAM KPIs more effectively.
– Enhance long-term maintenance planning through improved LCM (Life Cycle Management) strategies.

Who Should Attend:

This training is recommended for:
– Reliability Engineers
– Mechanical Engineers
– Operation and Maintenance Teams
– Operators
– Anyone interested in asset management and reliability.

Course Outline:

1. Theory and Practice: 40% theory, 60% practice.
2. Philosophy of RAM and ISO 55000: Understanding asset management principles.
3. RAM Theory and Application: Core concepts and their practical applications.
4. RAM Procedures and Reporting: Standard procedures for RAM assessments.
5. Case Study with Reliability Data: Practical application using Maximo.
6. MTBF, MTTF, and MTTR Data: Key metrics for reliability analysis.
7. Data Verification and Validation: Ensuring data accuracy and reliability.
8. Building Generic Reliability Data: Benchmarking against IEEE/DNV standards.
9. Reliability Block Diagram (RBD) Case Study: Analyzing reliability through RBD.
10. Configuration/Modeling of RBD: Creating and configuring RBDs.
11. Building RBD Equipment to Plant: Integrating RBDs into plant operations.
12. Applying Life Cycle Management Strategy to Maintenance Plans: Incorporating LCM into RAM.
13. Useful Remaining Life and Risk: Assessing remaining life and associated risks.
14. Developing Reliability KPIs: Creating effective KPIs for reliability.
15. Additional Case Studies: Exploring further applications and insights.