Contents

1 Big Data Analytics for Semiconductor Manufacturing . . . . . . . . . . . 1

1.1 Big Data and Big Data Analytics . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Big Data Analytics for Manufacturing . . . . . . . . . . . . . . . . . . . . . 2

1.3 Classification of Big Data Analytics Techniques and Tools . . . . . . 5

1.4 Big Data Analytics for Semiconductor Manufacturing. . . . . . . . . . 8

1.5 Assessing the Benefits of Big Data Analytics for Semiconductor Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . 13

1.6 Problems with Existing Methods . . . . . . . . . . . . . . . . . . . . . . . . . 14

1.7 Organization of This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2 Industry 4.0 for Semiconductor Manufacturing . . . . . . . . . . . . . . . . 21

2.1 Industry 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.2 Industry 4.0 for Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.2.1 Cyber-Physical Systems . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.2.2 Digital Twins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.2.3 Internet of Machines . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

2.2.4 Cloud and Ubiquitous Manufacturing . . . . . . . . . . . . . . . . 31

2.3 Industry 4.0 for Semiconductor Manufacturing . . . . . . . . . . . . . . . 32

2.3.1 Cyber-Physical System Applications . . . . . . . . . . . . . . . . . 33

2.3.2 Internet of Things Applications . . . . . . . . . . . . . . . . . . . . 36

2.3.3 Problems with Existing Methods . . . . . . . . . . . . . . . . . . . 37

3 Cycle Time Prediction and Output Projection . . . . . . . . . . . . . . . . . 41

3.1 Cycle Time Prediction in Semiconductor Manufacturing . . . . . . . . 41

3.2 Industry 4.0 and Big Data Analytics for Cycle Time Prediction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.3 Cycle Time Prediction Methods. . . . . . . . . . . . . . . . . . . . . . . . . . 44

3.3.1 Production Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3.3.2 Principal Component Regression . . . . . . . . . . . . . . . . . . . 45

3.3.3 Parallel Radial Basis Function Networks . . . . . . . . . . . . . . 50

3.3.4 Classifying Feedforward Neural Networks. . . . . . . . . . . . . 53

3.3.5 Fuzzy C-Means-Back Propagation Network Ensemble . . . . 56

3.3.6 Random Forest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

4 Defect Pattern Analysis, Yield Learning Modeling, and Yield Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.1 Defect Pattern Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.2 k-means Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

4.3 Parallel k-means Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

4.4 Applications of Other Machine Learning and Artificial Intelligence Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

4.5 Yield Learning Modeling and Yield Forecasting . . . . . . . . . . . . . . 72

5 Job Sequencing and Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5.1 Job Sequencing and Scheduling in Semiconductor Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5.2 Industry 4.0 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5.2.1 Cyber-Physical System and Internet of Things Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5.2.2 Radio Frequency Identification and Internet of Machines Applications . . . . . . . . . . . . . . . . . . . . . . . . . 81

5.3 Big Data Analytics Applications . . . . . . . . . . . . . . . . . . . . . . . . . 83

5.3.1 Dispatching Rules Based on Big Data Analytics . . . . . . . . 83

5.3.2 Optimization Using Big Data Analytics . . . . . . . . . . . . . . 87

5.3.3 Multiple-Criteria Job Dispatching Based on Big Data Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

5.3.4 Optimization Using Big Data Analytics . . . . . . . . . . . . . . 91

5.3.5 Decomposition of a Big-Data Job Scheduling Problem . . . 92