We are looking at a future where cars are driving themselves, meetings are accomplished through distance, and drones deliver food. In fact, many of these are already happening right this second. At the rate of growth of our technology, we humans work smarter — and not only harder.
What about how machines maintain operation in the oil and gas sector — one of the largest industries in the world where billions of dollars are generated by the second. Because in this field, as if it wasn’t stressed enough, time matters and should malfunction occur, a lot of man hours, resources, and money are on the line.
It is no secret that many large businesses have turned their attention to the innovation of artificial intelligence for the foreseeable future. This is no surprise when businesses are seeking ways to streamline their costs and work efficiently — and these are what artificial intelligence can offer.
Albeit a significant investment, this could be an invaluable choice to make as artificial intelligence has advanced to the point it can calculate the rate at which risks and errors are bound to happen — this feature can be simply described as predicting.
And analytics-based maintenance is considered to be at the top of the food chain of this innovation as it offers businesses with the key feature of constantly calculating numerics, obtained from sensors embedded in machines, against pre-programmed algorithm — in order to detect anomalies when numbers deviate from input which are installed by engineers.
In events where this predictive form of maintenance detect abnormal behaviors, engineers and experts are ready to notify companies on responsive action to approach the potential risks which is essential as this maintenance form, not only helps businesses avoid unforeseen and costly breakdown, but helps reduce routine checks and unnecessary maintenance checks.
The bottom line is the predictive artificial intelligent-based maintenance which heavily relies on statistics and analytics programming is an option worth looking into in order to streamline costs where profit can be retained for company growth and put human resources to more effective use.
From past to present, we take a look at how engineers assessed risks based on different models of maintenance from corrective to predictive methods.
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Unplanned shutdown in oil production is a costly disaster but it could happen. The question is: how can it be prevented?
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