Soft Markov Chain Relations For Modeling Safety Management

Abstract

This paper addresses the safety effects of organizational and operational factors, showing that they can be quantitatively measured. The work grew out of a preponderance of evidence that the safety "culture" (attitude of employees and management toward safety) was frequently one of the major root causes behind accidents or safety-relevant failures. The approach is called "Markov latent effects" analysis, and is based on a "Markov chain relations" structure that evolves from "Reason" (James Reason) models and Markov (A. A. Markov) probabilistic chained transitions. Since safety also depends on a multitude of factors that are best measured through well known risk analysis methods (e.g., fault trees, event trees, FMECA, physical response modeling, etc.), the Markov latent effects approach supplements and can be combined with conventional safety assessment methods.