a process modeling
approach based on an adaptive Neuro-Fuzzy Inference System.
For the construction of the prediction model 50 sets of samples,
where the 6 process control parameters are varied are prepared.
These are used for the training of the process prediction model
and a further 15 sets of samples are used for model validation.
An error analysis is then performed to evaluate the model
created. Based on the process prediction model, the
characteristics of the bonding parameters affecting bonding
quality are obtained, that can then be used for the optimization
of wire bonding process