Applications of Artificial Intelligence Techniques in Industry 4.0

70 Pages·2019·3.158 MB·English

by  Aydin Azizi

SPRINGER BRIEFS IN
APPLIED SCIENCES AND TECHNOLOGY
Aydin Azizi
Applications
of Artificial
Intelligence
Techniques in
Industry 4.0
123
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Aydin Azizi
fi
Applications of Arti cial
Intelligence Techniques
in Industry 4.0
123
AydinAzizi
Department ofEngineering
German University of Technology inOman
Muscat,Oman
ISSN 2191-530X ISSN 2191-5318 (electronic)
SpringerBriefs inApplied SciencesandTechnology
ISBN978-981-13-2639-4 ISBN978-981-13-2640-0 (eBook)
https://doi.org/10.1007/978-981-13-2640-0
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To My Family
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Aims and Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Structure of Book. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Modern Manufacturing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 Internet of Thing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 Radio Frequency Identification Technology . . . . . . . . . . . . . . . . . 10
2.2.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.2 Components of RFID System. . . . . . . . . . . . . . . . . . . . . . 12
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3 RFID Network Planning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.2 Mathematical Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.1 Coverage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2.2 Redundant Antennas . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.3 Interference. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.4 Transmitted Power. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
4 Hybrid Artificial Intelligence Optimization Technique . . . . . . . . . . . 27
4.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.2.1 Redundant Antenna Elimination Algorithm . . . . . . . . . . . . 30
4.2.2 Ring Probabilistic Logic Neural Networks. . . . . . . . . . . . . 34
4.3 Genetic Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
vii
viii Contents
5 Implementation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2 Working Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2.1 Static Working Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2.2 Dynamic Working Area. . . . . . . . . . . . . . . . . . . . . . . . . . 50
5.3 Parameters of the Proposed Hybrid Algorithm . . . . . . . . . . . . . . . 52
5.3.1 Population of the Possible Answers . . . . . . . . . . . . . . . . . 52
5.3.2 Fitness Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5.4 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.4.1 Static Working Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.4.2 Dynamic Working Area. . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Reference. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
List of Figures
Fig. 1.1 Proposed methodology of optimizing RNP problem... ..... .. 3
Fig. 1.2 Structure of this book. ..... .... .... .... .... .... ..... .. 5
Fig. 2.1 Definition of Internet of Things [4] ... .... .... .... ..... .. 8
Fig. 2.2 Internet of Things: intelligent systems framework [7].. ..... .. 8
Fig. 2.3 IoT model for manufacturing and industrial automation [7] .. .. 9
Fig. 2.4 Connected enterprise [7].... .... .... .... .... .... ..... .. 10
Fig. 2.5 Integrated equipment and appliances [7].... .... .... ..... .. 11
Fig. 2.6 The digital retail store [11].. .... .... .... .... .... ..... .. 11
Fig. 2.7 Components of an RFID system [18].. .... .... .... ..... .. 13
Fig. 2.8 Interactions between components of RFID system [19] ..... .. 13
Fig. 2.9 RFID tag [21]... .... ..... .... .... .... .... .... ..... .. 13
Fig. 2.10 RFID tag with printed barcode on it [22]... .... .... ..... .. 14
Fig. 2.11 RFID active tag [24].. ..... .... .... .... .... .... ..... .. 15
Fig. 2.12 RFID passive tag [25]. ..... .... .... .... .... .... ..... .. 15
Fig. 3.1 RFID technology components [2]. .... .... .... .... ..... .. 20
Fig. 3.2 Steps of defining an RNP... .... .... .... .... .... ..... .. 21
Fig. 3.3 Working area and distributed 20 tags.. .... .... .... ..... .. 21
Fig. 3.4 Example of tag coverage, if PTa1;tn(cid:1)Ttn ^PAtn;a3(cid:1)Ta3,
then Cv (1) = 1 [3]... ..... .... .... .... .... .... ..... .. 22
Fig. 4.1 Proposed hybrid optimization technique.... .... .... ..... .. 28
Fig. 4.2 RNP optimization process... .... .... .... .... .... ..... .. 29
Fig. 4.3 Proposed hybrid artificial intelligence optimization
process [16] .... .... ..... .... .... .... .... .... ..... .. 31
Fig. 4.4 Flowchart of the proposed redundant antenna elimination
algorithm [16]... .... ..... .... .... .... .... .... ..... .. 33
Fig. 4.5 Biological neuron [18] ..... .... .... .... .... .... ..... .. 35
Fig. 4.6 Example of artificial neural networks [18] .. .... .... ..... .. 35
Fig. 4.7 A RAM neuron [28].. ..... .... .... .... .... .... ..... .. 36
Fig. 4.8 A RAM discriminator [30].. .... .... .... .... .... ..... .. 37
Fig. 4.9 Flowchart of training algorithm of RAM neural network .... .. 38
ix
x ListofFigures
Fig. 4.10 Probabilistic Logic Neuron (PLN) [16]. .... .... .... ..... .. 39
Fig. 4.11 Pyramidal PLN neural network structure [16].... .... ..... .. 39
Fig. 4.12 Example of a PLN neural network structure [16]. .... ..... .. 40
Fig. 4.13 RPLNN structure [16]. ..... .... .... .... .... .... ..... .. 41
Fig. 4.14 Flowchart of the proposed RPLNN algorithm to optimize
RNP .. .... .... .... ..... .... .... .... .... .... ..... .. 42
Fig. 4.15 Example of roulette wheel [37]... .... .... .... .... ..... .. 45
Fig. 4.16 a Two-point crossover, b single-point crossover [16].. ..... .. 45
Fig. 4.17 Example of mutation [37]... .... .... .... .... .... ..... .. 45
Fig. 5.1 Proposed static working area .... .... .... .... .... ..... .. 50
Fig. 5.2 FMS [1] ... .... .... ..... .... .... .... .... .... ..... .. 50
Fig. 5.3 Proposed dynamic working area.. .... .... .... .... ..... .. 51
Fig. 5.4 Proposed population of possible answers ... .... .... ..... .. 53
Fig. 5.5 Example of encoded answer in population of answers . ..... .. 53
Fig. 5.6 Calculated number of deployed antennas in the network
by the proposed hybrid algorithm and GA in each iteration.. .. 55
Fig. 5.7 Calculated coverage of the RFID network by the proposed
hybrid algorithm and GA in each iteration.. .... .... ..... .. 55
Fig. 5.8 Calculated ITF of the network by the proposed hybrid
algorithm and GA in each iteration.... .... .... .... ..... .. 56
Fig. 5.9 Normalized fitness function values of the proposed hybrid
algorithm and GA in each iteration.... .... .... .... ..... .. 56
Fig. 5.10 Optimized RFID network... .... .... .... .... .... ..... .. 57
Fig. 5.11 Calculated number of deployed antennas in the network
by the proposed hybrid algorithm and GA in each iteration.. .. 58
Fig. 5.12 Calculated coverage of the RFID network by the proposed
hybrid algorithm and GA in each iteration.. .... .... ..... .. 58
Fig. 5.13 Calculated ITF of the network by the proposed hybrid
algorithm and GA in each iteration.... .... .... .... ..... .. 59
Fig. 5.14 Normalized fitness function values of the proposed hybrid
algorithm and GA in each iteration.... .... .... .... ..... .. 59
Fig. 5.15 Optimized RFID network... .... .... .... .... .... ..... .. 60