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Case Study 3- Risk Minimization at End of Life

A higb pressure high temperature vessel designed for 30-year lifespan was in operation after 40 years.  Stress Analysis models and a network of sensors were deployed to monitor the vessel. 

What was detected

The left side of the graph includes sensor data during warm-up when t he vessel is being started back onto operation after an outage. It can be seen that some of the sensors were mounted on the vessel surface and varying heights to account for the temperature differences. Also, the majority of the sensors were mounted subsurface (closer to the hot process temperature) with very little variation. All sensors detect temperature variations which can be correlated, in other words they all increase or decrease together.

On the right-hand side of the graph, a divergence in temperatures can be detected. One by one, the sensors showed a drop in temperature. Several minutes after the first divergence, the reactor failed and contents were released. Such a network of sensors could be used to manage risk by sounding alarms and initiating automatic shutdown to safely purge the danger.

With the Internet of Things (IoT) sensors have become inexpensive and wireless technology makes it easier to capture and monitor the data. IoT and MBSE can build on each other to manage existing assets.

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