Production Planning and Control in Semiconductor Manufacturing [electronic resource] : Big Data Analytics and Industry 4.0 Applications / by Tin-Chih Toly Chen.

Por: Chen, Tin-Chih Toly [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoSeries SpringerBriefs in Applied Sciences and TechnologyEditor: Cham : Springer International Publishing : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: VI, 100 p. 79 illus., 58 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031140655Tema(s): Industrial engineering | Production engineering | Internet of things | Production management | Cooperating objects (Computer systems) | Semiconductors | Industrial and Production Engineering | Internet of Things | Production | Cyber-Physical Systems | SemiconductorsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 670 Clasificación LoC:T55.4-60.8Recursos en línea: Libro electrónicoTexto
Contenidos:
Chapter 1. Big Data Analytics for Semiconductor Manufacturing -- Chapter 2. Industry 4.0 for Semiconductor Manufacturing -- Chapter 3. Cycle Time Prediction and Output Projection -- Chapter 4. Defect Pattern Analysis, Yield Learning Modeling and Yield Prediction -- Chapter 5. Job Sequencing and Scheduling.
En: Springer Nature eBookResumen: This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.
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Chapter 1. Big Data Analytics for Semiconductor Manufacturing -- Chapter 2. Industry 4.0 for Semiconductor Manufacturing -- Chapter 3. Cycle Time Prediction and Output Projection -- Chapter 4. Defect Pattern Analysis, Yield Learning Modeling and Yield Prediction -- Chapter 5. Job Sequencing and Scheduling.

This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.

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