Deep neural networks (DNNs) have been applied to predict the cycle times of jobs in manufacturing accurately. However, the prediction mechanism of a DNN is complex and difficult to communicate. This limits its acceptability (or practicability) in real-world applications. An explainable...

Experts often have unequal authority levels in organizations. However, this has rarely been considered reasonably in solving problems in the manufacturing system. In addition, a fuzzy collaborative estimation method can be more flexible and effective if experts have unequal authority levels. We...

Methods based on artificial neural network (ANN) or deep neural network (DNN) applications have been proposed to predict job cycle time effectively. However, the predicting mechanism of ANNs (or DNNs) is often difficult to understand and communicate. This problem has hindered their acceptability...

The cycle time of a wafer lot refers to the time that the wafer lot has experienced from its input to output. Predicting the cycle time of each wafer lot is a crucial task for a wafer fabrication factory (wafer fab), but existing prediction methods cannot achieve 100% accuracy. Therefore, if the...

There is a localization wave in the semiconductor industry for pushing wafer foundries to transfer their production capacity to where chip designers are located. The main reasons for the localization of semiconductor supply chains include the US-China trade war, geopolitics, COVID-19, the...