Data-Driven Prediction of Order Lead Time in Semiconductor Supply Chain
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-24907-5_77
Reference10 articles.
1. Schelthoff, K., Jacobi, C., Schlosser, E., Plohmann, D., Janus, M., & Furmans, K. (2022). Feature selection for waiting time predictions in semiconductor wafer fabs. IEEE Transactions on Semiconductor Manufacturing.
2. Lingitz, L., Gallina, V., Ansari, F., Gyulai, D., Pfeiffer, A., Sihn, W., & Monostori, L. (2018). Lead time prediction using machine learning algorithms: A case study by a semiconductor manufacturer. Procedia Cirp, 72.
3. Burggräf, P., Wagner, J., Koke, B., & Steinberg, F. (2020). Approaches for the prediction of lead times in an engineer to order environment-A systematic review. IEEE Access .
4. Singh, S., & Soni, U. (2019). Predicting order lead time for just in time production system using various machine learning algorithms: A case study. In: 2019 9th International Conference on Cloud Computing, Data Science and Engineering (Confluence) (pp. 422-425). IEEE.
5. Zhang, C., Yella, J., Huang, Y., & Bom, S. (2021). Learning from failures in large scale soft sensing. IEEE International Conference on Big Data .
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