Managing the tradeoff between productivity and safety: Risk management strategies for critical engineering systems

Productivity and safety are important objectives in many industries. This is particularly true in safety-critical production systems (e.g., nuclear power generation). While the primary purpose of such systems is to produce, inherently dangerous technology demands attention to safety. Industries are acutely aware of production levels because of direct implications for industry profits. System safety also receives significant attention, but cannot be directly measured in the absence of accidents, which is the case for those critical systems in which accidents are rare. Safety can be measured through the use of Probabilistic Risk Analysis (PRA).;While the tools are available to analyze these two primary objectives, the relationship between productivity and safety is not always fully understood. It is sometimes believed that productivity is highly correlated with safety. This is true if interruptions in operation are caused by events that are also accident initiators. In fact, there is probably a positive correlation in the long run. However, since most technical systems operate under resource constraints, the dual objectives may compete for these resources in the short term. In failing to adequately recognize and manage tradeoffs, some industries have difficulty giving the more abstract notion of safety a high priority at the expense of the more obvious and immediate goals of high production and reduced operating costs.;This research provides decision support for designing risk management strategies in safety-critical systems. The research uses a dynamic systems analysis approach to adapt management strategies to characteristics of the physical system. Combining probabilistic risk analysis and dynamic stochastic models, we compute expected risk, production, and cost patterns over the life of the system as functions of strategic options and operating policies. System safety and productivity are optimally balanced using decision analysis. The methodology is applied to decisions encountered in the management of planned and unplanned outages in nuclear power plants.