Being known for capital- & asset-intensive assets, lengthening
the lifespan of an asset is one of the prime goals of oil & gas industry. However, the irony of the situation is that as
per OEE [Overall Equipment Effectiveness] index, oil and gas industry lags
behind others when it comes to maintaining assets effectively.
Now, across the globe, oil & gas industries are
employing predictive analytics to overcome the challenges of critical asset equipment
performance, life cycle, integrity, security, and utilization. Based on the insights provided by predictive
analytics, companies are not only predicting the equipment failure in advance
but also are overcoming the challenges of diminishing and limited personnel
expertise in maintaining assets effectively. Besides, they also attained the
capability to intelligently operate multiple assets from a centralized location,
which helps them maintain their assets in a cost-effective manner.
Lately, companies started employing predictive analytics at
3 different levels when it comes to maintaining assets.
- At the production unit level, they are deploying analytics to understand how equipment is performing. Automated analytics could be used to improve uptime, efficiency, and throughput.
- At the facilities level, they are deploying analytics to understand about procurement, production scheduling, and shipping goods.
- At the enterprise level, they are deploying analytics to understand the larger business context. For example, to understand the impact of fluctuating costs, changing market conditions, asset performance, etc.
As you already know, Predictive Modeling draws from
statistics and optimization techniques to extract accurate information from
large volumes of data. From preventive maintenance to alert management,
predictive analytics helps to do asset management system aimed at minimizing
production costs and extending the life of assets.
Following are the advantages of using predictive analytics to
maintain assets in oil & gas industry:
- Increases asset availability
- Reduces resource non-productive time
- Helps to resolve defect rates, speedily
- Reduces spares inventory holding costs
- Reduces maintenance costs
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