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The Normal Accident Theory (NAT) attempts to understand why accidents occur in systems with high-risk technologies. NAT is characterized by two attributes: complexity and coupling. The combination of these attributes results in unplanned and unintended catastrophic consequences. High-risk technology systems that are complex and tightly coupled have a high probability of experiencing system failures. The mining industry has experienced significant incidents involving haulage operations up to and including severe injuries and fatalities. Although the mining industry has dramatically reduced fatalities and lost time accidents over the last three decades or more, accidents still continue to persist. For example, for the years 1998 - 2002, haulage operations in surface mines alone have accounted for over 40% of all accidents in the mining industry. The systems thinking was applied as an approach to qualitatively and quantitatively evaluate NAT in mining haulage operations. A measurement index was developed to measure this complexity. The results from the index measurements indicated a high degree of complexity that exists in haulage transfer systems than compared to loading and unloading systems. Additionally, several lines of evidence also point to the applicability of NAT in mining systems. They include strong organizational management or safety system does not guarantee zero accidents, complexity is exhibited in mining systems, and they are interactive and tightly coupled systems. Finally, the complexity of these systems were assessed with results indicating that a large number of accidents occur when there are between 4 or 5 causal factors. These factors indicate the degree of complexity necessary before accidents begin to occur.

The evaluation of risk is often performed assuming static conditions when in reality, conditions are continually evolving. In the following dissertation, the evaluation of risk with changing conditions over time is considered for a specific project - placing overburden into an active, open pit mine. The research focuses on the geotechnical components of risk with the goal of identifying whether and to what extent it is possible to place overburden on mined out portions of the open pit slopes. The relevant factors, which change with time or impact risk, are first identified and an evaluation is performed to estimate a probability of failure at various stages of the project life. Potential damages are then assessed by first evaluating the run out distance and post failure geometry of a slope failure and then estimating the percentage of material that would have to be removed to continue extraction of ore. To convert the uncertainty into economic terms, unit values for savings that result from placing overburden in the pit and costs associated with cleaning up failure debris are estimated. The probability of failure, potential for cleanup, and unit values are combined to produce estimates of the likely costs and benefits associated with dumping overburden in the open pit.The results of the analysis indicated that risk varies considerably with time. However, it is possible to place overburden in the central portion of the open pit up to a limit of approximately 80 million tons while maintaining a positive net value of expected costs and benefits.

In 1988 Skinner produced the Blended Diagnostic System (BDS) which was an attempt to provide the Aerospace Guidance and Metrology Center (AGMC) with an expert system capable of diagnosing faults in the Dual Miniature Inertial Navigation System (DMINS). Skinner proposed the blending of a traditional rule-based system with a model-based system. The techniques used to perform the model-based reasoning in BDS are however primitive compared to other techniques currently available. This thesis describes the development of a model-based diagnostic system using techniques pioneered by Randall Davis, and substantially more sophisticated than those used in BDS. A diagnostic prototype for the DMINS was developed which provides a more thorough and consistent diagnosis than does Skinner's model-based system. The models in our prototype were created using the Intelligent Diagnostic Expert Assistant (IDEA) software developed by AI Squared Inc., of North Chelmsford MA. IDEA is based on extensive research by Davis at the Massachusetts Institute of Technology (MIT). Theses. (RRH)