A Machine Learning Approach for Improving Wafer Acceptance Testing Based on an Analysis of Station and Equipment Combinations
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References listed on IDEAS
- Hyun Joong Yoon & Junjae Chae, 2019. "Simulation Study for Semiconductor Manufacturing System: Dispatching Policies for a Wafer Test Facility," Sustainability, MDPI, vol. 11(4), pages 1-21, February.
- Yong Jin Suh & Jin Young Choi, 2022. "Efficient Fab facility layout with spine structure using genetic algorithm under various material-handling considerations," International Journal of Production Research, Taylor & Francis Journals, vol. 60(9), pages 2816-2829, May.
- Eduardo e Oliveira & Vera L. Miguéis & José L. Borges, 2022. "On the influence of overlap in automatic root cause analysis in manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 60(21), pages 6491-6507, November.
- Chia-Yu Hsu & Wei-Chen Liu, 2021. "Multiple time-series convolutional neural network for fault detection and diagnosis and empirical study in semiconductor manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 823-836, March.
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Keywords
DRAM manufacturing; statistical quality control; clustering; associative analysis; case study;All these keywords.
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