From analyses of the defect cycle, the manufacturing system variables, and the adequacy of the control
procedures within the management of a manufacturing plant, the probabilities for the occurrence and frequency of
variables causing defects can be estimated. Subsequently, a density and probable time for a defect and its source can be
determined. The fault tree, as shown in Fig. 2, can be structured in order to determine the overall probability for
the production of a defective product; the fault tree can
also attribute the cause of the defect to a specific area. P ðdefective partÞ ¼ ðB1 B2Þ [ ðB3 B4Þ[ ðB5 B6Þ [ ðB7 B8Þ.
The fault tree as shown in Fig. 2 assumes that a single fault,
or a combination of all faults, may lead to a defective
product. Therefore, the quality improvement process
requires efforts to restrict the possibility of the occurrence
of further faults.
From analyses of the defect cycle, the manufacturing system variables, and the adequacy of the control
procedures within the management of a manufacturing plant, the probabilities for the occurrence and frequency of
variables causing defects can be estimated. Subsequently, a density and probable time for a defect and its source can be
determined. The fault tree, as shown in Fig. 2, can be structured in order to determine the overall probability for
the production of a defective product; the fault tree can
also attribute the cause of the defect to a specific area. P ðdefective partÞ ¼ ðB1 B2Þ [ ðB3 B4Þ[ ðB5 B6Þ [ ðB7 B8Þ.
The fault tree as shown in Fig. 2 assumes that a single fault,
or a combination of all faults, may lead to a defective
product. Therefore, the quality improvement process
requires efforts to restrict the possibility of the occurrence
of further faults.
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