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