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A modeling framework for exposing risks in complex systems
1Department of Industrial Engineering, University of Miami, Coral Gables, FL 33124-0623, USA. jsharit@miami.edu
Summary
This study presents a new modeling framework to identify human errors and adverse outcomes in high-risk systems. It combines accident theory with multiple system viewpoints for better risk analysis.
Area of Science:
- Systems Engineering
- Risk Management
- Human Factors Engineering
Background:
- High-risk systems are prone to human errors and adverse consequences.
- Existing risk analysis methods may not fully capture the complexities of these systems.
Purpose of the Study:
- To introduce and develop a novel modeling framework for exposing risks in high-risk systems.
- To enhance the understanding of human errors and adverse consequences.
Main Methods:
- The framework integrates Perrow's two-dimensional theory of accidents (interactive complexity and tight coupling).
- It incorporates the concept of multiple system perspectives for comprehensive analysis.
- The methodology cross-links these components to reveal hidden work contexts.
Main Results:
- The modeling framework effectively exposes risks related to human errors and adverse consequences.
- Application to a trauma care system demonstrated its utility in identifying complex risks.
- The approach facilitates understanding of otherwise difficult-to-identify system processes.
Conclusions:
- The developed modeling framework offers a valuable tool for risk analysis in high-risk systems.
- It is particularly useful for complex, evolving systems requiring human and system reliability analysis.
- The methodology enhances insight into system processes and potential failure points.