My name is Pierre Baviera, CEO of Presidion, Specialised Company in delivering Advanced Analytics Solutions – leveraging data to deliver Business Benefits in Return in Investment Big Data, IoT will create more and more data – data without insights and actions are worthless and at Presidion we are passionate about bridging this gap.
I am going to talk to you about what predictive maintenance delivers for those that have already adapted this approach.
Savings are sustensial, the technique is proven and well beyond hype. We are about to witness a transformation of the maintenance business model.
Pumps - Hour of Production per Annum 50% cheapper thant Reactive Maintenance 30% cheapper than Preventative Maintenance
75% reduction breakdown in Energy Companies
Would like to double the time spent / effort spent on Predictive Maintenance
Business Intelligence – as a paralell Business Intelligence very much suits the reactive and preventive maintenance world Story – 14 pumps broke down last quarter. Out of these 2 2 brand new broke down and this was a real surprise Downtime was 30 hours. This is how it impacted our production by a reduction of 10% of throughput equating $400,000. These were the reasons why it broke down. As a result this is how we are going to review of preventive maintenance policy?
Predictive analytics – Predictive maintenance? These 4 pumps have 90% probabilty to breakdown in the next 48 hours – these are the most probable reasons. 2 of these pumps will have limited impact on production. 2 others are critical and will put the production down as awhole. A workorder is created to address these…
Image is like moving from rules based – conditioning Information to prescriptive maintenance
A Major US-based Oil Company saved tens of million of dollars by preventing oil well collapse Oil and Gas produced in Australia getting 87% accuracy and 48-hour warning about potential equipement failure – saving millions of dollars by minimise downtime A global Oil & gas Company unearthing USD 11 Million by optimisting the production of 12 wells; 97% accuracy in detecting underperformaing wells and allowing to make adjustments US Oil and Gas Producer saved USD53Millions by identifying key reasons linked to stuck pipe situations and getting 85% accuracy in predicting these situations
The list of case study goes on and on and on…
How do you go about answering these questions
So … That is what Predictive Maintenance is about…
Internal/External, stuctured/unstructured data – we all have more data than we think Predictive modelling – pick out what’s unusual, what’s important, identifying the lead indicators to a particular event Act – your work-order
Think big, start small with actiona plan to deliver big
Predictive Maintenance is not magic – there is a proven best practice way of of delivering predictive insights this is CRISP-DM – Presidion participated to its design To make it work you need the right involvement of Line of Business People, Data People and IT people Insights that don’t deliver against a business problem are worthless Insights that cannot be deployed are worthless Always starts with the Business Question / Business Goals and loop back to the Business and deployment – this where you people from the Business will be involved
Preditive Analytics and Predictive Maintenance are proven technologies, these are beyond hype – it is about thinking big and starting small and building momentum Asset Data – volume/quality/availability You have much more data than you assume It is also about low frequency hihg impact
Criticality of failure is key
Our experience has shown that our challenges are about…There are not only about Oil&Gas..We help our customers overcome these challenges
So you need to think about Identifying key business questions or a problem that needs solving through data Identiying key assets Identiying the data that we use Identifying process that might be changed Identifying key stakeholders Identiyfing Performance Indicators
Also different organisations are at different stages
It does not have to be overwhelming and this can
Learn and educate at the beginning
In your situation what process and data will deliver the biggest bang for your bucks – business case and roadmap (think Big)