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© Presidion 2016Formerly SPSS Ireland
Delivering significant efficiencies through Predictive Maintenance in the Oil & Gas
Industry
Aberdeen, 10 March 2016
© Presidion 20162
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
© Presidion 20163
Predictive Maintenance – Transforming of Maintenance Business Model
Source: Roland Berger
2 75%Reduction in breakdown
4More 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%
Rea
ctiv
e an
d P
reve
ntiv
e
© 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
TimePast
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?
© 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
© Presidion 20166
What if I could tell you that a specific asset is 90% likely to fail within one week for Reasons A, B and C?
Data Predictive Models - Insights
Actions(Work Order)
Anomaly Detection
Diagnostic Analysis
Recommendations and decision support
What should be done next?
PriortiisationWhat 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
© Presidion 20167
How to deliver a Predictive Analytics Project succesfully
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
© Presidion 20168
Asset Data Availability
Criticality of Failure
Trust in Predictive
Technology
When Predictive Maintenance works well
Actionable Insights – Return on Investment
© Presidion 20169
Challenges
Heterogeneous Assets
Changing Operating Conditions
Interoperability
© 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 Analytics3. Improve business
performance
4. Sustain improved
performance
1.1 Advanced Analytics
Transformation Workshop
1. Learn how Advanced
Analytics can transform your
organisation
© Presidion 201611
What if you could deliver these numbers…
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
