Development of an artificial neural network to predict lead frame dimensions in an etching process

Abstract

The electronic industry is rapidly developing, creating high demand for IC production. Etched semiconductor lead frames are the basic material used in IC packaging. IC packaging requires high-precision lead frames. The dimensions of the pilot hole are generally required to be highly precise in lead frame manufacturing. The photo-etching process must control the dimension of the pilot hole and record the manufacturing data of the etching machine and inspection data. This study presents the development of an artificial neural network (ANN) model that can be applied to construct the predicting model. The predictive model can estimate the dimensions of the pilot hole and thus determine the process parameters needed to improve lead frame quality in the etching process.