Cycle-Time Key Factor Identification and Prediction in Semiconductor Manufacturing Using Machine Learning and Data Mining

@article{Meidan2011CycleTimeKF,
  title={Cycle-Time Key Factor Identification and Prediction in Semiconductor Manufacturing Using Machine Learning and Data Mining},
  author={Yair Meidan and Boaz Lerner and Gad Rabinowitz and Michael Hassoun},
  journal={IEEE Transactions on Semiconductor Manufacturing},
  year={2011},
  volume={24},
  pages={237-248}
}
Within the complex and competitive semiconductor manufacturing industry, lot cycle time (CT) remains one of the key performance indicators. Its reduction is of strategic importance as it contributes to cost decreasing, time-to-market shortening, faster fault detection, achieving throughput targets, and improving production-resource scheduling. To reduce CT, we suggest and investigate a data-driven approach that identifies key factors and predicts their impact on CT. In our novel approach, we… CONTINUE READING
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