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RAM Modelling in the Project Design Phase

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

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RAM Modelling in the Project Design Phase

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  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?

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