Overcoming Uncertainty with Artificial Intelligence and Machine Learning Insights

Rumsfeld theory states, “we know what we know (known knowns), we know what we do not know (known unknowns), and we do not know what we do not know (unknown unknowns).” The last two statements are the most dangerous statements in the asset integrity industry, as these contribute to uncertain situations and in some cases catastrophic outcomes unless focused action is taken.

Uncertainty in the asset integrity industry comes in many forms. Quite often, limitations produce uncertainties. A few limitations from an exhaustive list are a lack of needed budget, a lack of qualified resources, a lack of objectivity in the inspection process, a lack of knowledge, or a lack of systematic communication. Processes in general, but specifically speaking to asset integrity, are normally vulnerable due to these select few and many other organizational limitations. It has been studied by many credible investigation firms that the most catastrophic failures can be categorized into three sections.

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Shopia Ketheeswararajah is a feature editor contributing to Pump Engineer, Stainless steel World Americas, Hose and Coupling World, and other related print & online media.