(56d) AI-Enabled Dynamic Risk Register: A Novel Approach to Risk Management

Process safety accidents and incidents can have devastating consequences, both in terms of human life and financial costs. Traditional process safety risk management solutions are often limited in their ability to prevent these accidents. They may be based on outdated data or rely on manual processes that are prone to error.

The AI-Enabled Dynamic Risk Register is a novel approach to process safety risk management that overcomes these limitations. It uses artificial intelligence to analyze historical and real-time data from operational, process parameters, maintenance, and reliability data to predict future risks, recommend remediation actions, and identify the root causes of risks.

The AI-Enabled Dynamic Risk Register uses artificial intelligence to analyze historical and real-time data to predict future risks, recommend remediation actions, and identify the root causes of risks. The system is divided into three main components:

1. Foundational models: By using hybrid models that combine computer vision, time-series forecasting, and physics-based modeling to diagnose and predict the condition of heat exchangers, furnaces, and pumps. These models are more accurate and robust than individual models, and they can provide more insights into the condition of the equipment.
2. Prescriptive models: LSTM prescriptive models analyze the predicted results from foundational models to prioritize risks and recommend remediation actions. LSTM prescriptive models are particularly well-suited for this task because they can learn long-term dependencies in the data, which is important for predicting equipment failures and recommending remediation actions.
3. Dashboard: An interactive dashboard using Power BI that displays the overall risk, top threats, and recommendations to reduce risk.

The AI-Enabled Dynamic Risk Register has been shown to be effective in reducing accidents and incidents by up to 20%, maintenance costs by USD 1 million, and loss of revenue by USD 4 million. For example, one company that implemented the AI-Enabled Dynamic Risk Register was able to prevent a major accident that could have cost millions of dollars in damage and lost revenue.

The AI-Enabled Dynamic Risk Register is a valuable tool for any company that wants to improve its process safety performance. It is a powerful example of how digitalization can be used to improve safety in industrial plants.