Incident Prediction and Avoidance Solutions Finally Become a Reality
Keywords: Predictive Analysis, Critical Condition Management (CCM), Incident Avoidance, Multivariate SPC.
"Inevitably, what you don't know will ruin your day." This often-voiced piece of wisdom is particularly true in the process industries, where operations staffs are being asked to do more with less, new technologies are burying them with data, institutional process knowledge is flying out the door, and the financial and other costs of incidents to industrial organizations continue to increase.
To improve this situation, industrial organizations must evolve to become largely proactive cultures in which — rather than reacting to incidents — operational personnel adopt a proactive stance; first predicting and then taking appropriate steps to avoid the occurrence of incidents. This involves cultural, organizational, human, and technical elements. This Insight will address some of the key technical elements.
Since, in today's increasingly complex and fast-paced industrial environments, simple incidents can rapidly escalate into major incidents, more people have to be able make the right decisions at the right times. This requires a "production time" perspective, enabled by predictive analytics. While the concept is not new, the appropriate tools are now available to enable today's operators to predict and effectively avoid incidents. In concert with appropriate cultural, organizational, and human elements, these can play a key role in any critical condition management (CCM) initiative.
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