Wafer defect inspection is an important process that is
performed before die packaging. Conventionalwafer inspections are usually
performed using human visual judgment. A large number of people visually
inspect wafers and hand-mark the defective regions. This requires
considerable personnel resources and misjudgment may be introduced due to human
fatigue. In order to overcome these shortcomings, this study develops an
automatic inspection system that can recognize defective LEDdies. An
artificial neural network is adopted in the inspection. Actual data obtained
from a semiconductor manufacturing company in Taiwan were used in the
experiments. The results show that the proposed approach successfully
identified the defective dies on LED wafers. Personnel costs and
misjudgment due to human fatigue can be reduced using the proposed approach.
Source:IEEE
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