Data-Driven scheduling of semiconductor manufacturing systems
Intro -- Preface -- Contents -- 1 Scheduling of Semiconductor Manufacturing System -- 1.1 Semiconductor Manufacturing Process -- 1.2 Scheduling of Semiconductor Manufacturing System -- 1.2.1 Scheduling Characteristics -- 1.2.2 Scheduling Types -- 1.2.3 Scheduling Methods -- 1.2.4 Evaluation Indicato...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Singapore
Springer
2023
Beijing Chemical Industry Press 2023 |
| Schriftenreihe: | Advanced and intelligent manufacturing in China
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Tag hinzufügen | Zusammenfassung: | Intro -- Preface -- Contents -- 1 Scheduling of Semiconductor Manufacturing System -- 1.1 Semiconductor Manufacturing Process -- 1.2 Scheduling of Semiconductor Manufacturing System -- 1.2.1 Scheduling Characteristics -- 1.2.2 Scheduling Types -- 1.2.3 Scheduling Methods -- 1.2.4 Evaluation Indicators -- 1.3 Scheduling Development Trend of Semiconductor Manufacturing System -- 1.3.1 Data Preprocessing of Complex Manufacturing System -- 1.3.2 Data-Based Scheduling Modeling -- 1.3.3 Data-Based Scheduling Optimization -- 1.3.4 Analysis of Research Status -- 1.4 Summary -- References -- 2 Data-Driven Scheduling Framework of Semiconductor Manufacturing System -- 2.1 Design of Data-Driven Scheduling Framework -- 2.2 Data-Based Scheduling Architecture of Complex Manufacturing System -- 2.2.1 Overview of DSACMS -- 2.2.2 Formal Description of DSCAMS -- 2.2.3 DSACMS-Based Modeling and Optimization of Scheduling for Complex Manufacturing Systems -- 2.2.4 Key Technologies in DSACMS -- 2.3 Application Examples -- 2.3.1 Overview of Fabsys -- 2.3.2 Object-Oriented Simulation Model of Fabsys (OOSMfab) -- 2.3.3 Data-Driven Forecasting Model in FabSys -- 2.4 Summary -- References -- 3 Data Preprocessing of Semiconductor Manufacturing System -- 3.1 Introduction -- 3.2 Data Standardization -- 3.2.1 Data Normalization Rules -- 3.2.2 Correction of Abnormal Values for Variables -- 3.3 Filling of Missing Data -- 3.3.1 Filling Method for Missing Data -- 3.3.2 Memetic Algorithm and Memetic Calculation -- 3.3.3 Attribute Weighted K Nearest Neighbor Missing Value Filling Method (KNN) Based on Gaussian Mutation and Depth First Search (GD-MPSO): GD-MPSO-KNN -- 3.3.4 Numerical Verification -- 3.4 Outlier Detection Based on Data Clustering Analysis -- 3.4.1 Outlier Detection Based on Data Clustering -- 3.4.2 K-Means Clustering. |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | XI, 266 Seiten Diagramme |
| ISBN: | 9789811975875 978-981-19-7587-5 9789811975905 978-981-19-7590-5 |