Continuous Risk Management model

Realistically, it has to be concluded that the term ALARP really does not provide much help to risk management professionals and facility managers in defining what levels of risk are acceptable. It may be for this reason that the U.K. HSE chose in the year 2006 to minimize its emphasis to do with ALARP requirements from the Safety Case Regime for offshore facilities. Other major companies have also elected to move away from ALARP toward a continuous risk reduction model (Broadribb, 2008). 

After years of experiments and the nonetheless effective use of these tools making it possible to refine and systematically optimise control of facilities, the tools due to increased performance and possibilities made available by software and other computer equipment, has been improved by increasing the calculation horizon, beyond two gas years by using adapted models (closer to classic reservoir models by taking into account a simplified physical representation). At the present stage with R D works still continuing, they now include more and more complexity (risk management, stochastic simulations, etc), and works are focused on ... 

The continuous improvement cycle, which is fundamental to the heart of QM, is conceptualfy the same as the risk management process. The two models can be compared as follows ... 

Using a primary-care model of treatment, O Malley et al. (2003) initially treated alcohol-dependent patients with open-label naltrexone for 10 weeks, in combination with either CBT or primary care management (PCM), a less intensive, supportive approach. They found no effect of psychosocial treatment on response to treatment, although CBT was associated with a lower risk of drinking. Treatment responders from this study were then randomly assigned to one of two placebo-controlled 24-week continuation studies in... 

For consequence analysis, we have developed a dynamic simulation model of the refinery SC, called Integrated Refinery In-Silico (IRIS) (Pitty et al., 2007). It is implemented in Matlab/Simulink (MathWorks, 1996). Four types of entities are incorporated in the model external SC entities (e.g. suppliers), refinery functional departments (e.g. procurement), refinery units (e.g. crude distillation), and refinery economics. Some of these entities, such as the refinery units, operate continuously while others embody discrete events such as arrival of a VLCC, delivery of products, etc. Both are considered here using a unified discrete-time model. The model explicitly considers the various SC activities such as crude oil supply and transportation, along with intra-refinery SC activities such as procurement planning, scheduling, and operations management. Stochastic variations in transportation, yields, prices, and operational problems are considered. The economics of the refinery SC includes consideration of different crude slates, product prices, operation costs, transportation, etc. The impact of any disruptions or risks such as demand uncertainties on the profit and customer satisfaction level of the refinery can be simulated through IRIS. 

Risk assessment is a continuous process performed throughout the design and development of the business model. During strategic analysis and business process analysis, the engineer reviews the processes and procedures that the enterprise has estabhshed to identify and manage strategic and process risks. 

An adaptation of Reason s original model specifically for the management of medical equipment-related risk is offered and shown in Figure 52.1. In this form, the model is particularly applicable to healthcare because it encourages a focus on three areas that lend themselves to a continued vigilance or... 

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