Biomedical Engineering Reference
In-Depth Information
2.5.5
5 Why Analysis
5 Why analysis is the process of repeatedly asking “why” something occurred.
The rule of thumb is to ask “why” five times. But it could be more or less than
five times. The process is to keep asking “why” until the result is unchangeable
or is out of control. The benefit of the 5 Why Analysis is that it facilitates the
identification of deep underlying causes of problems and failures.
2.5.6 Histograms
Histograms or bar charts graphically summarize the frequency distribution of the
data set. Histograms can be used in decision making by identifying outliers of
data from a risk assessment where risk priority numbers are assigned.
2.5.7 Pareto Analysis
Pareto analysis is a decision-making technique that prioritizes information under
the principle that 80% of the problems are produced by 20% of the causes. This
technique is useful as a benchmark and should not be used as being an accurate
measurement of risks, but more for identifying the risks that have the most impact
on a system.
2.5.8 Control Charts
Control charts are often used in process quality control to determine whether or
not a process is in a state of statistical control. This tool can be used to distinguish
real process variations from “noise.” If the chart indicates that the process is not
in control, it can be used to determine the source of the problem so the process
can be controlled back to steady-state. Control charts can also be used for risk
mitigation (by improving detection) or monitoring.
2.6 COMPARISON OF RISK ASSESSMENT TOOLS
This section will look at various risk assessment tools and compare them to each
other on the basis of:
1. Scope—the scope of the risk analysis to be performed, how broad.
2. Granularity—the level of detail in the analysis and shown in the docu-
mented output.
3. Inductive or deductive—Inductive is forward looking and planned, deduc-
tive is backward looking.
4. Interactions versus individual risks.
5. Complexity—a rating of complexity from low to high.
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