Smart Agent System for Cyber Nano-Manufacturing in Industry 4.0
Abstract
:1. Introduction
2. Methodology
2.1. ANN-Based Expert System
2.1.1. Digital Designs and Feature Extraction
2.1.2. Knowledge Base
2.1.3. Data Organization
2.1.4. ANN Algorithm Development
2.2. Cyber Interface Simulator Using the IoT
2.3. Dynamic Nano-M/C Identification System
3. Result and Discussion
3.1. ANN-Based Expert System
3.1.1. First Stage
3.1.2. Second Stage
3.2. Cyber Interface Simulator Using IoT
3.3. Dynamic Nano-M/C Identification System
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Input/Output | Variables | |
---|---|---|
Input | Cost | |
Low | 1 | |
Medium | 2 | |
High | 3 | |
Pattern Complexity | ||
Low | 1 | |
Medium | 2 | |
High | 3 | |
Process Throughput Key | ||
Low | 1 | |
Medium | 2 | |
High | 3 | |
Material Key | ||
Polymer | 1 | |
Metal | 2 | |
Ceramic | 3 | |
Semiconductor | 4 | |
Composite | 5 | |
Output | Nano-Process | |
Dip Pen Nanolithography (DPN) | 1 | |
Nanoimprint Lithography (NIL) | 2 | |
Photolithography (PHO) | 3 | |
Pulsed Laser Deposition (PLD) | 4 | |
Self-Assembly (SA) | 5 |
Input Variable | DPN | NIL | PHO | PLD | SA |
---|---|---|---|---|---|
Cost | [2, 3] | [1–3] | [1, 2] | [2, 3] | [1, 2] |
Pattern Complexity | 2 | [2, 3] | [2, 3] | [1, 2] | [1, 2] |
Aspect Ratio | [0.3–2] | [3–10] | [1–5] | [1–5] | [1, 2] |
Feature Resolution (nm) | [5–20] | [5–20] | [500–800] | [5–20] | [10–50] |
Process Throughput | [1, 2] | [2, 3] | 3 | [1, 2] | [1–3] |
Material | [1–5] | [1–5] | [1–5] | [1–5] | [1–5] |
Set | Cost | Pattern Complexity | Aspect Ratio | Feature Resolution | Process Throughput | Material | Nano- Process | Nano-Process Code |
---|---|---|---|---|---|---|---|---|
1 | 1 | 2 | 8 | 12 | 2 | 4 | NIL | 2 |
2 | 1 | 2 | 8 | 6 | 3 | 1 | NIL | 2 |
3 | 1 | 1 | 2 | 34 | 1 | 4 | SA | 5 |
4 | 2 | 2 | 2 | 7 | 1 | 5 | PLD | 4 |
5 | 2 | 2 | 2 | 511 | 3 | 4 | PHO | 3 |
6 | 3 | 2 | 2 | 10 | 1 | 3 | PLD | 4 |
7 | 1 | 2 | 2 | 567 | 3 | 4 | PHO | 3 |
8 | 2 | 2 | 9 | 6 | 2 | 3 | NIL | 2 |
9 | 2 | 2 | 10 | 20 | 2 | 2 | NIL | 2 |
10 | 2 | 2 | 2 | 14 | 1 | 3 | PLD | 4 |
11 | 3 | 2 | 1 | 5 | 1 | 2 | DPN | 1 |
12 | 1 | 2 | 3 | 591 | 3 | 1 | PHO | 3 |
13 | 2 | 3 | 8 | 15 | 2 | 3 | NIL | 2 |
14 | 1 | 2 | 3 | 516 | 3 | 2 | PHO | 3 |
15 | 1 | 1 | 1 | 30 | 1 | 2 | SA | 5 |
Stage | Designs | Input Variables |
---|---|---|
First | 100 | Pattern Complexity |
Feature Resolution | ||
Process Throughput | ||
Material | ||
Second | 200 | Pattern Complexity |
Feature Resolution | ||
Process Throughput | ||
Material | ||
Cost | ||
Aspect Ratio |
First Stage | |||
---|---|---|---|
GRNN | PNN | BPNN | |
1 | 64% | 48% | 60% |
2 | 72% | 64% | 68% |
3 | 60% | 64% | 56% |
4 | 64% | 72% | 56% |
5 | 72% | 64% | 56% |
6 | 64% | 64% | 64% |
7 | 68% | 76% | 64% |
8 | 68% | 64% | 68% |
9 | 44% | 76% | 68% |
10 | 64% | 60% | 68% |
Average | 64% | 65.20% | 62.80% |
Second Stage | |||||||
---|---|---|---|---|---|---|---|
Run | Training | Testing | |||||
MSE | Gradient | Validation Performance | R-Value | GRNN | PNN | BPNN | |
1 | 4.12 × 10−7 | 0.00015 | 0.01455 | 0.9800 | 98% | 96% | 96% |
2 | 3.84 × 10−7 | 0.00012 | 0.01421 | 0.9820 | 98% | 96% | 98% |
3 | 3.51 × 10−7 | 0.00014 | 0.01475 | 0.9817 | 96% | 98% | 96% |
4 | 3.63 × 10−7 | 0.00012 | 0.01460 | 0.9811 | 96% | 98% | 96% |
5 | 3.86 × 10−7 | 0.00022 | 0.01399 | 0.9700 | 96% | 98% | 90% |
6 | 3.75 × 10−7 | 0.00018 | 0.01400 | 0.9788 | 94% | 96% | 96% |
7 | 3.72 × 10−7 | 0.00020 | 0.01414 | 0.9786 | 96% | 94% | 96% |
8 | 3.88 × 10−7 | 0.00019 | 0.01512 | 0.9814 | 94% | 96% | 94% |
9 | 3.98 × 10−7 | 0.000276 | 0.01537 | 0.9686 | 90% | 94% | 90% |
10 | 3.87 × 10−7 | 0.000250 | 0.01477 | 0.9733 | 92% | 94% | 90% |
Average | 95.00% | 96.00% | 94.20% |
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Almakayeel, N.; Desai, S.; Alghamdi, S.; Qureshi, M.R.N.M. Smart Agent System for Cyber Nano-Manufacturing in Industry 4.0. Appl. Sci. 2022, 12, 6143. https://doi.org/10.3390/app12126143
Almakayeel N, Desai S, Alghamdi S, Qureshi MRNM. Smart Agent System for Cyber Nano-Manufacturing in Industry 4.0. Applied Sciences. 2022; 12(12):6143. https://doi.org/10.3390/app12126143
Chicago/Turabian StyleAlmakayeel, Naif, Salil Desai, Saleh Alghamdi, and Mohamed Rafik Noor Mohamed Qureshi. 2022. "Smart Agent System for Cyber Nano-Manufacturing in Industry 4.0" Applied Sciences 12, no. 12: 6143. https://doi.org/10.3390/app12126143