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Predictive Maintenance for Oil and Gas

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Presidion present on delivering significant efficiencies through predictive maintenance in the oil and gas industry.

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Predictive Maintenance for Oil and Gas

  1. 1. © Presidion 2016 Formerly SPSS Ireland Delivering significant efficiencies through Predictive Maintenance in the Oil & Gas Industry Aberdeen, 10 March 2016
  2. 2. © Presidion 2016 1. Significant Financial Benefits linked to Predictive Maintenance 2. What Predicitve Maintenance is about 3. How Predictive Maintenance works 4. How to make a success of Predictive Maintenance What I will cover 2
  3. 3. © Presidion 2016 Predictive Maintenance – Transforming of Maintenance Business Model 3 Source: Roland Berger 2 75% Reduction in breakdown 4 More data = More accuracy = More value 1 $18 /hp p.a. $9 /hp p.a $13 /hp p.a. 3 15%Time spent on Predictive Maintenance only 75% 15% Reactiveand Preventive
  4. 4. © Presidion 2016 Predictive Analytics help connect data to effective action by drawing reliable conclusions about current conditions and future events 4 High Low Business Value Time Past Business Intelligence Sense and Response Future Predictive Analytics Predict and Act Techniques and Data • Optimisation, predictive modelling, forecasting, statistical analyis • Structured/Unstructured Data, Internal/External Data, Massive Data Sets Driving Questions to be answered • What will happen next? Why? • Why is this happenin? • What if? • What's the optimal scenario for our business? Techniques and Data • Reporting, dashboarding, alerts, queries • Structured Data, Manageable Data Sets Driving Questions to be answered • What happened last quarter / month /week? • How many pumps did break down? How much did we spend on maintenance? How much downtime on these assets? How many preventive actions have we completed? • Where is the problem?
  5. 5. © Presidion 2016 How does Predictive Maintenance deliver? Unearthing characteristics that lead to an increased frequency of failures Predicting impact or consequence scores to enhance Alarms Management so that key alarm events are prioritised Identifying factors that increase ownership cost and downtime over the life of a system Identifying assets at risk of failure even when they have no previous failure history Mining free text from thousands of logs that describe the maintenance performed on systems to accurately categorise maintenance reports and identify areas of risk Finding patterns in maintenance operations that could point to opportunities for improvements
  6. 6. © Presidion 2016 What if I could tell you that a specific asset is 90% likely to fail within one week for Reasons A, B and C? 6 Data Predictive Models - Insights Actions (Work Order) Anomaly Detection Diagnostic Analysis Recommendations and decision support What should be done next? Priortiisation What to attend to first depending on fault severity? Evaluate impact Procurement & Supply Chain Sensors GIS Data Historian Asset Management Maintenance Management Automation Change Management Real Time Other Sources
  7. 7. © Presidion 2016 How to deliver a Predictive Analytics Project succesfully 7 Determine Business Objectives and Data Mining Goals 1 Collect, describe, explore and verify quality of Data 2 Select, clean, construct, integrate and format data 3 Select, Generate, Build and Evaluate Models 4 Evaluate how the results help to achieve business objectives 5 Integrate new knowledge into your business processes 6 Business Understanding Data Understanding Data Preparation Modelling Evaluation Deployment
  8. 8. © Presidion 2016 Asset Data Availability Criticality of Failure Trust in Predictive Technology When Predictive Maintenance works well 8 Actionable Insights – Return on Investment
  9. 9. © Presidion 2016 Challenges 9 Heterogeneous Assets Changing Operating Conditions Interoperability
  10. 10. © Presidion 2016 End-to-End approach is required 10 2.1 Tactical Audit for Advanced Analytics 2.2 Maturity Assessment for Advanced Analytics 2.3 Roadmapping and Business Case Development 3.1 Advanced Analytics Capability Building 4.1 Performance Monitoring and Business Benefits Realisation 2. Prepare yourself for success in Advanced Analytics 3. Improve business performance 4. Sustain improved performance 1.1 Advanced Analytics Transformation Workshop 1. Learn how Advanced Analytics can transform your organisation
  11. 11. © Presidion 2016 What if you could deliver these numbers… 11 Source: us department of energy's o&m best practise guide, Imagine if you add IoT data 4 10 xReturn on Investment 1 25%Increase in production output 30% 2 Reduction in maintenance costs 45% 3 Reduction in downtime
  12. 12. © Presidion 2016 www.presidion.com Pierre.baviera@presidion.com Q & A Thank You

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