Unveil the Black Box for Performance Efficiency of OEE for Semiconductor Wafer Fabrication

This study has demonstrated practical viability of the proposed approach employing datamining technics, Neural Networks (NNs), to estimate the productivity of individual process tool sets in a semiconductor factory, and to assess the efficiency loss by 15 related individual input factors, which included “process time”, “number of recipes”, “usable tool”, “Q-time constrain”, “standard deviation of lot size”, “batch size”, “sampling rate”, “hot lot ratio” and etc.. An empirical study was conducted by using the equipment data of a real fab. The results showed that the proposed approaches can define performance efficiency of Overall equipment efficiency (OEE) more reasonable, which discover underlying factors for efficiency loss, and help to improve performace efficiency from 91.23% to 94.03%.