RAM Modelling in the Project Design Phase

1. Asset Management Council – WA Chapter & Maintenance Engineering Society of Australia Reliability Modelling for Business Decisions RAM Modelling in the Project Design Phase Friday 30th April, 2010 Paul Websdane

2. RAM Modelling for Business Decisions • Project Design and Execute Phases • Steps in Process. • Examples & Learnings. • Benefits. • RAM in Operations phase • Barriers & Benefits.

3. Introduction • Snr Reliability Engineer – K2 Technology. • Experience in Oil and Gas, Alumina, Mining, Condition Monitoring, Pumping. • RAM Tools & Packages; • Many different packages are available. • Each have strengths and weaknesses. • Used RAM for analysis of large new projects, small design changes, tank overhaul scenarios, decisions on redundancy.

4. RAM Modelling Overview • Tool to analyse and predict the availability / reliability of an asset or facility. • Reliability Block Diagrams (RBD) used. • Use Equipment Capability & Reliability data. • Maintenance Strategies & Schedules (optimise). • Overall production impact - $$$$. • Improved business decisions.

5. RAM models in the Design Phase • Evaluate, Validate and Optimize design • Availability & Reliability targets. • Production capability. • Bottlenecks & Big hitters – Critical Equipment. • Redundancy levels. • Sparing. • Can “Design In” Reliability • Focus improvement efforts early in design.

6. Model Basic Steps • Understand system operating context, production impact and cost of downtime. • Document assumptions. • Build the RBD and Reliability Data Register. • Populate with Reliability Data and details of Maintenance Strategy / Shutdowns. • Analyse the System. • Update and refine over time. • Conduct Sensitivity analyses.

7. Reliability Block Diagrams • Build Reliability Block Diagram from P&ID, system drawings, PFDs; • RBD’s represent the connections between system components from a reliability perspective. • Does not show process flow.

8. Reliability Block Diagrams 2 x 100% 3 x 50%

9. RBD’s – Examples

10. Operating Context – what we need • Design Capacity of each block. • Redundancy. • Impact on production • No impact – why in the model? • Single Point Vulnerabilities! • Very important – do not miss these. • Bypass capacity on failure • Inbuilt work arounds that protect production.

11. Production Impact Full Production 32 kT/d Each Turbine 8 kT/d For full production system requires 4 turbines online at all times (32kT/d)

12. Production Impact Full Production 30 kT/d Each Pump 15 kT/d For full production system requires 2 pumps online at all times (15kT/d)

13. Production Impact • Bypass capacity – refines model with actual production impact – also helps with buy in from operations. • Must understand the linkages between key elements in the model.

14. Failure Modes / Reliability Data • Understand dominant functional failures. • Reliability data sourced from • CMMS & Facility Operating History. • Experienced operators. • OREDA. • Vendor.

15. Reliability Data • CMMS • Maintenance and failure history. • Data accuracy? Job recording? • How accurate is this across industry? • Be careful – garbage in , garbage out. • Facility Operating / Trip history • Often stored outside CMMS. • See your friendly Reliability Engineer.

16. Reliability Data • Operators & Maintenance Resources • Very valuable information resource. • BUT – difficult to quantify losses without data. • Useful information on Bypass capacity. • Engage operations and maintenance where possible.

17. Reliability Data • Vendors and OREDA • Some vendors have good history – check operating context and environment. • OREDA is of use – ensure a reasonable population of equipment is available. • Useful Reliability Data is available – understand limitations and use with care.

18. Reliability Data Register • Capture key data & references. • Hold workshop with operations & maintenance to validate / review data & assumptions.

19. Analyse the Model Outputs • Model outputs – typical.

20. Model Outputs - time

21. Model Outputs

22. Unit Interventions

23. Unit Interventions

24. Update and Refining the Model • Assess Design Changes • Latest updates. • Quantify improvements . • Incorporate maintenance (RCM). • Shutdown analysis. • Sensitivity Studies. • Production Profiles.

25. Design Changes • Add newer component (high reliability) • System availability before – 98.0% • System availability after - 99.2% • Improvement of 1.2% or 4.4 days production @ $1million per day = $4.4m savings

26. Design Changes • Redesign to save cost! • Reduction in availability 0.5% or 1.8 days production @ $1million per day = $1.8m COST to business. • Can demonstrate impact of changes on facility performance – better decisions are made.

27. Sensitivity Studies • Critical Equipment improvement options; • water washing frequencies. • more reliable equipment. • maint strategy changes. • Redundancy installed. • Show me the money $$$$! • Shutdown analysis – modify frequency and durations – optimise.

28. Sensitivity Studies – Savings $$

29. Sensitivity Studies – Savings $$

30. Production Profiles - Refining • Highlights system deficiencies over time. • Applications • well deterioration over time. • Tank volume decrease (scaling) over time.

31. Improving Business Decisions • Predict performance over time. • Validate design changes. • Quantify ($) cost and impact of failure. • Identifies Critical Equipment • where to focus improvement efforts. • where to focus training. • where to consider redundancy. • where to hold critical spares (MTTR).

32. Asset’s Operations Phase • Traditionally this is done poorly (if at all). • Barriers • Lack of buy in / support from operations & maintenance . • involve O&M in model build and assumptions. • Modelling – inaccuracy, no understanding of operating context. • Rigorous review of data and facility configuration – engage operations.

33. Asset’s Operations Phase • Barriers • Lack of confidence in model / data. • Use valid data, document assumptions, involve operations & maintenance. • Review actual performance compared to design over time – feedback into model. • Consider the model to be “live” – regularly update to improve accuracy.

34. Operations Phase - Benefits • Highlight improvement opportunities. • Justify cost of upgrades. • Quantify BENEFITS of past projects. • Assess effectiveness of maintenance. • Assess risk of shutdowns – optimize shutdown intervals.

35. Summary • RAM modelling is a valuable tool in Reliability Engineering. • Important to use valid data and involve operations & maintenance. • Useful in all industries, for large and small projects. • Can improve business decisions by quantifying loss and benefits in $ terms.

36. Questions?