Near-Miss Management LLC

Daniel Shumway

Ulku G Oktem

Ankur Pariyani

Brett Emaus

Steven DeLaurentis

Matthew L Dering

Andrew Schneider

The invention provides a dynamic risk analyzer (DRA) that periodically assesses real-time or historic process data, or both, associated with an operations site, such as a manufacturing, production, or processing facility, including a plant's operations, and identifies hidden near-misses of such operation, when in real time the process data appears otherwise normal. DRA assesses the process data in a manner that enables operating personnel including management at a facility to have a comprehensive understanding of the risk status and changes in both alarm and non-alarm based process variables. The hidden process near-miss data may be analyzed alone or in combination with other process data and/or data resulting from prior near-miss situations to permit strategic action to be taken to reduce or avert the occurrence of adverse incidents or catastrophic failure of a facility operation.

Dynamic prediction of risk levels for manufacturing operations through leading risk indicators: dynamic risk pattern match method and system

Dynamic prediction of risk levels for manufacturing operations through leading risk indicators: dynamic exceedance probability method and system

Dynamic prediction of risk levels for manufacturing operations through leading risk indicators: dynamic risk sloping trend method and system

A dynamic risk fault tree (DRFT) for displaying and analyzing risk levels for manufacturing operations. The DRFT incorporates a Dynamic Risk Analyzer (DRA) to periodically assesses real-time or historic process data, or both, associated with an operations site, such as a manufacturing, production, or processing facility, including a plant's operations, and identifies hidden near-misses of such operation, when in real time the process data appears otherwise normal. DRFT assesses the process data in a manner that enables operating personnel including management at a facility to have a comprehensive understanding of the risk status and changes in both alarm and non-alarm based process variables. The DRA and hidden process near-miss data may be analyzed alone or in combination with other process data and/or data resulting from prior near-miss situations to permit strategic action to be taken to reduce or avert the occurrence of adverse incidents or catastrophic failure of a facility operation.

Dynamic prediction of risk levels for manufacturing operations through leading risk indicators: dynamic risk fault tree method and system

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Philadelphia, PA, United States of America

Daniel Shumway