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Sample Ishikawa diagram shows the causes contributing to problem. The defect, or the problem to be solved, [1] is shown as the fish's head, facing to the right, with the causes extending to the left as fishbones; the ribs branch off the backbone for major causes, with sub-branches for root-causes, to as many levels as required.
In software testing, a cause–effect graph is a directed graph that maps a set of causes to a set of effects. The causes may be thought of as the input to the program, and the effects may be thought of as the output. Usually the graph shows the nodes representing the causes on the left side and the nodes representing the effects on the right side.
Current reality tree example. A CRT begins with a list of problems, known as undesirable effects (UDEs.) These are assumed to be symptoms of a deeper common cause. To take a somewhat frivolous example, a car owner may have the following UDEs: the car's engine will not start; the air conditioning is not working; the radio sounds distorted
Failure effects are determined and entered for each row of the FMECA matrix, considering the criteria identified in the ground rules. Effects are separately described for the local, next higher, and end (system) levels. System level effects may include: System failure; Degraded operation; System status failure; No immediate effect
graph with an example of steps in a failure mode and effects analysis. Failure mode and effects analysis (FMEA; often written with "failure modes" in plural) is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects.
Interrelationship diagrams (IDs) displays all the interrelated cause-and-effect relationships and factors involved in a complex problem and describes desired outcomes. The process of creating an interrelationship diagram helps a group analyze the natural links between different aspects of a complex situation.
A link marked -indicates a negative relation where an increase in the causal variable leads, all else equal, to a decrease in the effect variable, or a decrease in the causal variable leads, all else equal, to an increase in the effect variable. A positive causal link can be said to lead to a change in the same direction, and an opposite link ...
The seven basic tools of quality are a fixed set of visual exercises identified as being most helpful in troubleshooting issues related to quality. [1] They are called basic because they are suitable for people with little formal training in statistics and because they can be used to solve the vast majority of quality-related issues.