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Advanced Quality Control (AQC) of Silicon Wafer Specifications for Yield Enhancement for Smart Manufacturing
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Advanced Quality Control (AQC) of Silicon Wafer Specifications for Yield Enhancement for Smart Manufacturing (2020)Advanced Quality Control (AQC) of Silicon…Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor (2020)Deep reinforcement learning f…UNISON data-driven intermittent demand forecast framework to empower supply chain resilience and an empirical study in electronics distribution (2019)UNISON data-driven intermitte…Overlay Error Compensation Using Advanced Process Control With Dynamically Adjusted Proportional-Integral R2R Controller (2013)Overlay Error Compensation Us…A system for online detection and classification of wafer bin map defect patterns for manufacturing intelligence (2013)A system for online detection…Design of a sampling strategy for measuring and compensating for overlay errors in semiconductor manufacturing (2003)Design of a sampling strategy…Economic Control of Quality of Manufactured Product. (1932)Feature-based control chart pattern recognition (1997)Statistical quality control : a modern introduction (2009)An empirical study of design-of-experiment data mining for yield-loss diagnosis for semiconductor manufacturing (2013)Business Intelligence in Industry 4.0: State of the art and research opportunities (2018)Multi-objective artificial bee colony algorithm for multi-stage resource leveling problem in sharing logistics network (2020)Stability and Sensitivity of an EWMA Controller (1993)Run by run process control: combining SPC and feedback control (1995)Run-to-Run Process Control: Literature Review and Extensions (1997)Hierarchical Equipment Health Index Framework (2019)Adaptive Cautious Regularized Run-to-Run Controller for Lithography Process (2021)Forecasting and Stock Control for Intermittent Demands (1972)A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products (1987)forecast: Forecasting Functions for Time Series and Linear Models (2009)A multivariate approach for multi-step demand forecasting in assembly industries: Empirical evidence from an automotive supply chain (2020)Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda (2022)Review and analysis of artificial intelligence methods for demand forecasting in supply chain management (2022)Information Distortion in a Supply Chain: The Bullwhip Effect (1997)Financial time series forecasting using support vector machines (2003)Introduction to time series analysis and forecasting (2008)Enhancing supply chain management with deep learning and machine learning techniques: A review (2024)Machine Learning and Deep Learning Models for Demand Forecasting in Supply Chain Management: A Critical Review (2024)Semiconductor supply chain resilience and disruption: insights, mitigation, and future directions (2024)Constructing the OGE for promoting tool group productivity in semiconductor manufacturing (2007)
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References

  • 2020Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor140 cited
  • 2019UNISON data-driven intermittent demand forecast framework to empower supply chain resilience and an empirical study in electronics distribution138 cited
  • 2013A system for online detection and classification of wafer bin map defect patterns for manufacturing intelligence90 cited
  • 2013Overlay Error Compensation Using Advanced Process Control With Dynamically Adjusted Proportional-Integral R2R Controller51 cited
  • 2003Design of a sampling strategy for measuring and compensating for overlay errors in semiconductor manufacturing36 cited

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