Cause consequence diagram

Cause-Consequence Diagram These diagrams illustrate the causes and consequences of a particular scenario. They are not widely used because, even for simple systems, displaying all causes and outcomes leads to veiy complex diagrams. Again, this technique is employed by experienced risk analysts. 

In a more quantitative sense, cause-consequence analysis may be viewed as a blend of fault tree end event tree analysis (discussed in tlie two preceding cliapters) for evaluating potential accidents. A major strengtli of cause-consequence analysis is its use as a communication tool. For example, a cause-consequence diagram displays the interrelationships between tlie accident outcomes (consequences) and Uieir basic causes. The method can be used to quantify the expected frequency of occurrence of the consequences if the appropriate chita are available. 

Cause-Consequence Diagram These diagrams illustrate the... 

Nielsen DS (1971) The cause consequence diagram method as a basis for quantitative accident analysis. Danish Atomic Energy Commission, RISO-M-1374 OMG (2010) UML superstructme reference. http //www.omg.Org/spec/UML/2.l.2/Superstruc ture/PDF. Accessed April 2010... 

Cause consequence diagrams A method for illustrating the possible outcomes arising from the logical combination of selected input events or states. 

Supply Chain Design Mean-Variance Optimization Cause-Consequence Diagrams Failure Analysis. 

Cause-consequence diagrams or event trees are tools commonly used in reliability analysis to study the overall impact of a particular failure on the entire system. Based on the supply chain configuration, we can develop cause-consequence diagrams for each failure described above. However, given our interest in developing models for supplier selection, we employ these cause-consequence diagrams to specifically analyze the effect of... 

Figure 3. Cause consequence diagram for supplier non-performance and the resulting outcome...

The mean costs and variability of the costs for each supplier can be obtained from an analysis of their historical performance or by considering the probabilities of their non-performance and the associated costs of handling the consequent impacts. Furthermore, due to the stochastic nature of events in the cause-consequence diagram we can safely assume that in general the final outcomes and associated costs of supplier non-performance will be normally distributed. 

The forward looking part of HAZOPS, SWIFT and functional FME(C)A are all consequence analyses. Includes ETA, cause consequence diagrams, etc. 

Logic Diagram Methods (Fault Tree Analysis, Event Tree Analysis, Cause-Consequence Analysis, Human Reliability Analysis, Success and Failure Trees, etc,)... 

Three hazard evaluation procedures using logic diagrams are (1) fault-tree analysis (FTA), (2) event-tree analysis (ETA), and (3) cause-consequence analysis (CCA). Appropriate references are [2,3,251,261]. 

Cause-Consequence A procedure using diagrams to illustrate... 

To analyze and measure the reliability and maintainability characteristics of a system, there must be a mathematical model of the system that shows the functional relationships among all the components, the subsystems, and the overil system. The reliability of the system is a function of the reliabilities of its components. A system reliability model consists of some combination of a reliability block diagram or cause-consequence chart, a definition of all equipment failure and repair distributions, and a statement of spare and repair strategies (Kapur 1996a). All reliability analyses and optimizations are made on these conceptual mathematical models of the system. 

A quantitative risk review technique. Cause-consequence analysis is a hlend of fault tree and event tree analysis. This technique combines cause analysis (described by fault trees) and consequence analysis (described by event trees), and hence deductive and inductive analysis is used. The purpose of CCA is to identify chains of events that can result in undesirable consequences. With the probabilities of the various events in the CCA diagram, the probabilities of the various consequences can be calculated, thus establishing the risk level of the system. See also Event Tree Analysis (ETA) Fault Tree Analysis (FTA). 

Figure 20.1 Schematic diagram illustrating how antidepressants increase the concentration of extraneuronal neurotransmitter (noradrenaline and/or 5-HT). In the absence of drug (b), monoamine oxidase on the outer membrane of mitochondria metabolises cytoplasmic neurotransmitter and limits its concentration. Also, transmitter released by exocytosis is sequestered from the extracellular space by the membrane-bound transporters which limit the concentration of extraneuronal transmitter. In the presence of a MAO inhibitor (a), the concentration of cytoplasmic transmitter increases, causing a secondary increase in the vesicular pool of transmitter (illustrated by the increase in the size of the vesicle core). As a consequence, exocytotic release of transmitter is increased. Blocking the inhibitory presynaptic autoreceptors would also increase transmitter release, as shown by the absence of this receptor in the figure. In the presence of a neuronal reuptake inhibitor (c), the membrane-bound transporter is inactivated and the clearance of transmitter from the synapse is diminished...

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