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Risk assessment should still be a manual process, but AI can streamline data collection to enable sound engineering judgments.
In this episode, Trish and Traci welcome guest Dheerajkumar Narang, whose research examines how AI and machine learning can enhance process safety compliance. Traditional compliance methods are time-consuming and fragmented across different systems, while AI can automate data collection, identify leading indicators and predict compliance outcomes. Key challenges include system integration with legacy infrastructure and maintaining domain expertise for regulatory updates. AI should streamline processes to allow operators to focus on critical tasks.
By chemicalprocessingsafety5
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Risk assessment should still be a manual process, but AI can streamline data collection to enable sound engineering judgments.
In this episode, Trish and Traci welcome guest Dheerajkumar Narang, whose research examines how AI and machine learning can enhance process safety compliance. Traditional compliance methods are time-consuming and fragmented across different systems, while AI can automate data collection, identify leading indicators and predict compliance outcomes. Key challenges include system integration with legacy infrastructure and maintaining domain expertise for regulatory updates. AI should streamline processes to allow operators to focus on critical tasks.

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