Neither author has a financial or proprietary interest in any material or method mentioned.

Many disasters have occurred because organizations have ignored the warning signs of precursor incidents or have failed to learn from the lessons of the past. Normal accident theory suggests that disasters are the unwanted, but inevitable output of complex socio-technical systems, while high-reliability theory sees disasters as preventable by certain characteristics or response systems of the organization. We develop an organizational response system called incident learning in which normal precursor incidents are used in a learning process to combat complacency and avoid disasters. We build a model of a safety and incident learning system and explore its dynamics. We use the model to motivate managers to implement incident learning systems as a way of moving safety performance from normal accidents to high reliability. The simulation model behavior provides useful insights for managers concerned with the design and operation of incident learning systems.

No abstract

The SRK/T formula has nonphysiologic behavior that contributes to IOL power prediction errors. A modification to the formula algorithm, the T2 formula, can be directly substituted for SRK/T, resulting in significantly improved prediction accuracy.

This article describes a system dynamics analysis of the 1992 Westray mine disaster in Nova Scotia, Canada. It examines the causal structure of the Westray system, including relationships that could have led to conditions that caused the fatal explosion at the mine. The value of simulation is its ability to capture a ''mental model'' of the safety system, which can stimulate discussion among safety experts as to the systemic causes of a disaster. By taking into account feedback loops and non-linear relationships, which is not possible with conventional root-cause analysis, a dynamic model of the system provides insights into the complex web of causes that can lead to disaster and valuable lessons for organizational learning.