optimization of supply chain management by
TRANSCRIPT
OPTIMIZATION OF SUPPLY CHAIN MANAGEMENT BY SIMULATION
BASED RFID WITH XBEE NETWORK
AFTAB AHMED SOOMRO
A thesis submitted in
fulfilment of the requirement for the award of the
Degree of Doctor of Philosophy in Mechanical Engineering
FACULTY OF MECHANICAL AND MANUFACTURING ENGINEERING
UNIVERSITI TUN HUSSEIN ONN MALAYSIA
2015
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ABSTRACT
The aim of every Supply Chain Management (SCM) is to reduce the operational cost
and maximize the benefits. These necessitate the use of advance technology to
optimize the operational activities. Among the widely used technology in recent years
is Radio Frequency Identification (RFID). It is an advanced Auto-ID wireless network
based configuration system used for identification and tracking of items movement
data. Technically, basic requirements for deploying RFID network are to identify the
number of readers needed, location of the readers and the efficient parameter setting
for each reader. Among the problems associated with RFID technology are the multi-
objective optimizations, which include tags coverage, economic efficiency,
interference and load balance. In order to solve this problem, a simulation based
“Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was
developed. This algorithm computes the optimal results of objective functions in a
scientific manner. However, RFID reader is an expensive and has limited data
transmission range. It alone cannot transmit data to the main server. Thus, its
communication range was enhanced by the integration of RFID with XBee (ZigBee)
wireless mesh network devices. Furthermore, the identification data need to be
monitored and transmitted to the business organizations, which are connected through
the network. This has been achieved by the integration of RFID-XBee network with
database connectivity through Internet of Things (IoT). This integrated system
provides the visibility of items at real time identification and tracking activity at single
control platform. This system also provides data sharing activity with business
enterprises using IoT. The benefits of this system include reduction of shrinkage and
data transfer time in global network. This system also increases the accuracy,
productivity and improves delivery of service in supply chain to the optimum level.
This would contribute towards a more sustainable and green supply chain management.
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ABSTRAK
Matlamat setiap Pengurusan Rantaian Bekalan (SCM) adalah untuk mengurangkan
kos operasi dan memaksimumkan keuntungan. Ia memerlukan teknologi canggih,
yang memudahkan untuk melaksanakan dari segi aktiviti operasi dan
mengoptimumkan manfaatnya. Radio Frequency Identification (RFID) adalah satu
teknologi tanpa wayar Auto-ID digunakan untuk pengenalan dan pengesanan data
pergerakan barangan dalam pengurusan rantaian bekalan. RFID adalah sistem
konfigurasi berasaskan rangkaian yang banyak digunakan dalam SCM. Secara
teknikal, keperluan asas untuk menggunakan rangkaian RFID termasuklah
mengetahui bilangan pembaca yang diperlukan, lokasi pembaca dan penggunaan
kuasa yang efisien oleh setiap pembaca. Antara masalah yang berkaitan dilaporkan
bahawa teknologi RFID ialah pengoptimuman pelbagai objektif termasuk liputan tag,
kecekapan ekonomi dan gangguan. Bagi mengatasi masalah ini, satu algorithma
simulasi "Multi-Colony Global Particle Swarm Optimization (MC-GPSO)"
mendapatkan keputusan optimum bagi setiap fungsi objektif secara saintifik. Walau
bagaimanapun, pembaca RFID adalah mahal dan mempunyai penghantaran data yang
terhad. Ia tidak boleh menghantar data kepada pelayan utama secara bersedirian. Oleh
itu, komunikasi telah dipertingkatkan dengan integrasi antara RFID dengan XBee
(ZigBee) peranti rangkaian mesh tanpa wayar. Tambahan pula, data pengenalan perlu
dipantau dan dihantar kepada organisasi perniagaan, yang dihubungkan dengan
rangkaian. Ia telah dicapai melalui integrasi rangkaian RFID-XBee dengan sambungan
pangkalan data mengunakan “Internet of Things” (IoT). Sistem bersepadu
menyediakan pengenalan keterlihatan item pada masa sebenar dan pengesanan aktiviti
di platform kawalan tunggal. Sistem ini juga menyediakan aktiviti perkongsian data
kepada perusahaan perniagaan menggunakan IoT. Antara kebaikan sistem ini
termasuklah ia dapat mengurangkan ketirisan dan masa pemindahan data dalam
rangkaian global. Sistem ini meningkatkan ketepatan, produktiviti dan penyampaian
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perkhidmatan dalam rantaian bekalan pada peringkat optimum. Ini mampu
menyumbang kepada pengurusan rantaian bekalan yang lebih mampan dan mesra
alam.
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TABLE OF CONTENTS
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENT iv
ABSTRACT v
TABLE OF CONTENTS viii
LIST OF TABLES xii
LIST OF FIGURES xiii
LIST OF ABBREVIATIONS xvi
LIST OF PUBLICATIONS xviii
CHAPTER 1 INTRODUCTION 1
1.1 Research Background 1
1.2 Problem Statement 3
1.3 Aim and objectives of research 4
1.4 Scope of the research 5
1.5 Summary 5
CHAPTER 2 REVIEW OF LITERATURE 7
2.1 Auto-ID Technology 9
2.2 Shrinkage 10
2.3 Radio Frequency Identification (RFID) Systems 10
2.3.1 Physical Layer 12
2.3.2 Electromagnetic Propagation (Transmission) 14
2.3.3 Electromagnetic Waves (Radio Waves) 16
2.3.4 Near-Field/Inductive Coupling 20
2.3.5 Far-Field/Backscatter Coupling 20
2.3.6 Link Budget and Read Range 22
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2.3.7 Path loss propagation Model 23
2.3.8 Free space propagation Model 24
2.3.9 Two-ray propagation Model 25
2.3.10 Multipath propagation Model 26
2.3.11 Radar Cross Section propagation Model 27
2.3.12 Radiation Pattern of an Antenna 28
2.3.13 Antenna Gain 29
2.3.14 IT Layer 30
2.4 Application of wireless networks 32
2.5 RFID network planning (RNP) 32
2.5.1 Optimal tag coverage 33
2.5.2 Reader collision avoidance (Interference) 33
2.5.3 Economic efficiency 34
2.5.4 Load balance 34
2.6 Optimization 34
2.7 Basic concept of Particle Swarm Optimization 36
2.8 XBee (ZigBee) (Wireless Sensor Network) 39
2.9 Summary 42
CHAPTER 3 RESEARCH FRAMEWORK 44
3.1 Research Flow 44
3.2 RFID network parameters 47
3.2.1 Tags Coverage 47
3.2.2 Interference 51
3.2.3 Number of readers 52
3.3 Setting parameters of search space 53
3.4 Setting topology of search space 55
3.5 Reader representation 56
3.6 Coding of tags, readers and working area 57
3.7 Coding of objective functions and all variable parameters 59
3.8 Application of MC-GPSO 59
3.8.1 Initialization 60
3.8.2 Setting Optimization criteria 60
x
3.8.3 Operating procedure 61
3.8.4 Simulation Results 62
3.9 Summary 63
CHAPTER 4 INTEGRATION OF RFID-XBEE NETWORK WITH
DATABASE CONNECTIVITY 64
4.1 System Development 65
4.2 Hardware Configuration 67
4.2.1 RFID Reader Connection and Testing 67
4.2.2 XBee Module Connection and communication 71
4.3 RFID-XBee Operating Module 74
4.4 Software architecture of the system 77
4.4.1 LabVIEW Database Connectivity Module 77
4.4.1.1 Database connection tools of LabVIEW
program 80
4.4.1.2 Creation of UDL file for LabVIEW
Database Connection 80
4.4.1.3 The construction of LabVIEW database
functional module 81
4.4.1.4 The LabVIEW Database Connectivity
Programming Model 85
4.4.1.5 Graphical User Interface (GUI) 87
4.4.1.6 LabVIEW developed system 91
4.4.1.7 Validation of RFID-XBee and
LabVIEW database system 94
4.5 Live video operating module 94
4.6 IoT Operating Module 96
4.7 Integrated Module 100
4.8 Summary 105
CHAPTER 5 RESULTS AND ANALYSIS 107
5.1 Implementation of MC-GPSO 107
5.2 RFID-XBee network result 120
xi
5.3 Integrated network of RFID-XBee, database connectivity
and IoT result 120
5.4 Summary 122
CHAPTER 6 CONCLUSION AND RECOMMENDATIONS 123
6.1 Contribution 124
6.2 Recommendation 125
REFERENCES 126
APPENDIX A MATALAB CODE OF MC-GPSO 133
VITA 138
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LIST OF TABLES
2.1: Tangible ROI as a bottom-line positive business benefits 8
2.2: Application of operating frequencies in RFID system 17
2.3: Power comparison in dBm and mW 18
2.4: Conditions of Near-field and far-field region 21
2.5: Path loss exponent n and σ measured in different buildings 27
2.6: Previous reaserch summary of RFID network planning 41
2.7: Previous RFID research works integrated with wireless
technologies 42
3.1: The different case studies 53
3.2: Dimension of each reader for PSO solution 57
4.1: Hardware wire connections 71
5.1: Comparison results of MC-GPSO algorithm at tags 30 109
5.2: Comparison results of MC-GPSO algorithm at tags 50 110
5.3: Comparison results of MC-GPSO algorithm at tags 100 111
5.4: Comparison results of MC-GPSO algorithm at tags 30 112
5.5: Comparison results of MC-GPSO algorithm at tags 50 114
5.6: Comparison results of MC-GPSO algorithm at tags 100 115
5.7: Comparison results of MC-GPSO algorithm at 50 and 100 tags
(TE) 116
5.8: Comparison results of MC-GPSO algorithm at 50 and 100 tags
(TD) 118
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LIST OF FIGURES
2.1: Important Auto-ID technologies 9
2.2: Typical RFID System 11
2.3: RFID system layers 12
2.4: Various RFID Tags 13
2.5: Electromagnetic wave propagation 15
2.6: Electromagnetic wave path loss in free space 16
2.7: Electromagnetic wave 16
2.8: Summary of worldwide UHF band allocations 17
2.9: Radiated field regions of an antenna having maximum
dimension D 22
2.10: Path Loss Propagation Models 24
2.11: Two-ray Path Loss 25
2.12: The graphical representation of the radar system 28
2.13: The 3D radiation pattern of an electrically short current
element 29
2.14: The E-plane and H-plane patterns of an electrically short
current element 29
2.15: RNP basic problems 33
2.16: Types of computational Intelligence 35
2.17: Particle Swarm Optimization flow diagram 38
3.1: Research flow chart 46
3.2: Randomly plotting of tags 48
3.3: Randomly deploy number of readers 49
3.4: Best location of readers in the network 49
3.5: Multiple readers interference 52
3.6: Topology diagram 55
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3.7: Randomly plotting of 100 number of tags in 50m × 50m
working area 58
3.8: Optimization criteria flow strategy 61
4.1: Sustainable Supply Chain Management Optimization Model 65
4.2: Optimal Green Supply Chain Management Model 66
4.3: System Development 66
4.4: Circuit diagram of RFID reader connection with Xbee
Router/End device 68
4.5: Snaps of physical devices network connection 69
4.6: Protocol of the RFID Reader 69
4.7: Tag ID 70
4.8: XBee configuration procedure 72
4.9: Configurations of set of XBees 74
4.10: RFID-XBee Operating Module 76
4.11: LabVIEW Database Connectivity Module 78
4.12: Database connectivity model 79
4.13: Simple LabVIEW Database Construction Model 79
4.14: Microsoft Access database tables 81
4.15: LabVIEW database functional module 82
4. 16: Data execution in sequential order 83
4.17: Data displayed by index array 83
4.18: Verification of data in the database 84
4.19: VISA Close operation 85
4.20: LabVIEW Database Connectivity Programming Model 85
4.21: Vehicle and Item information 88
4.22: Live Cam Tab 89
4.23: Parameter setting Tab 90
4.24: Address source file Tab 90
4.25: LabVIEW Algorithm 92
4.26: Monitoring by LabVIEW Control panel 92
4.27: Microsoft Access Database Report (a) & (b) 94
4.28: Live video process diagram 95
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4.29: Live video block diagram 95
4.30: Wireless connection between two computers via IoT 97
4.31: Data server.vi and Data client.vi 98
4.32: Optimal solution of supply chain management 101
4.33: Optimal position of RFID readers 102
4.34: Integrate module 103
4.35: Live monitoring 104
5.1: Simulation results of case study 1 with 30 tags 110
5.2: Simulation results of case study 1 with 50 tags 111
5.3: Simulation results of case study 1 with 100 tags 112
5.4: Simulation results of case study 2 with 30 tags (a), (b) and (c) 113
5.5: Simulation results of case study 2 with 50 tags (a), (b) and (c) 115
5.6: Simulation results of case study 2 with 100 tags (a), (b) and (c)
116
5.7: Simulation results of case study 3 with 50 and 100 tags (a) and
(b) 117
5.8: Simulation results of case study 3 with 50 and 100 tags (a) and
(b) 119
5.9: Physical model of RFID-XBee network 120
5.10: Live Cam monitoring by LabVIEW application 121
5.11: Communication between two computers by IoT 122
6.1: Monitoring of items by RFID-XBee network 125
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LIST OF ABBREVIATIONS
ABC Ant Bee Colony
ACO Ant Colony Optimization
ADO Active X Data Object
AIDC Auto Identification and Data Capture
BFO Bacterial Foraging Optimization
COM Component Object Model
DBMS Data Base Management System
DSN Data Source Name
EA Evolutionary Algorithm
EPC Electronic Product Code
GPS Global Positioning System
GSCM Green Supply Chain Management
GUI Graphical User Interface
HF High Frequency
IZ Interrogation Zone
JIT Just-In-Time
LabVIEW Laboratory Virtual Instruments Engineering Workbench
LF Low Frequency
MAC Medium Access Control
MATLAB Matrix Laboratory
NPV Net Present Value
OCR Optical Character Recognition
ODBC Open Data Base Connectivity
OLEDB Object Linking and Embedded Data Base
ONS Object Naming Service
PAN Personal Area Network
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POS Point Of Sale
PSO Particle Swarm Optimization
RCS Radar Cross Section
RFID Radio Frequency Identifications
RNP Radio Frequency Identifications Network Planning
ROI Return On Investment
RTLS Real Time Locating System
SCM Supply Chain Management
SI Swarm Intelligence
SMI Small and Medium Scale Industry
UART Universal Asynchronous Receiver Transmitter
UDL Universal Data Link
UHF Ultra High Frequency
UPC Universal Product Code
WPAN Wireless Personal Area Network
WSN Wireless Sensor Network
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LIST OF PUBLICATIONS
Journal Articles
1 Integration of Value Stream Mapping with RFID, WSN and ZigBee Network
Aftab Ahmed, Khalid Hasnan, Badrul Aisham, Qadir Bakhsh
Applied Mechanics and Materials, Vol. 465 (2014) pp 769-773
(SCOPUS, EI and ISI Proceedings)
2 Optimization of RFID Real-time Locating System
Khalid Hasnan, Aftab Ahmed, Winardi Sani, Qadir Bakhsh
Australian Journal of Basic and Applied Sciences Vol. 8 (2014) pp 662-668
(ISI Indexed)
3 Optimization of RFID network planning using ZigBee and WSN (In Press)
Khalid Hasnan, Aftab Ahmed, Badrul Aisham, Qadir Bakhsh
Applied Mechanics and Materials Vol. 1660 (2015) pp
(SCOPUS, EI and ISI Proceedings)
4 Impact of RFID and XBee Communication Network on Supply Chain
Management
Aftab Ahmed, Khalid Hasnan, Badrul-aisham, Qadir Bakhsh
Applied Mechanics and Materials Vol. 660 (2014) pp983-987
(SCOPUS and ISI Indexed)
5 A novel optimal RFID network planning by MC-GPSO
Khalid Hasnan, Aftab Ahmed, Badrul-aishama, Qadir Bakhsh, Kashif Hussain
Indian Journal of Science and Technology Vol. 8(17) (2015) pp. 1-7
(SCOPUS Indexed)
6 RFID with XBee communication network enhance the visibility of supply chain
management (Accepted)
Khalid Hasnan, Aftab Ahmed, Badrul-aishama and Qadir Bakhsh
Procedia CIRP ELSEVIER
7 A Novel Integration of RFID Network Planning With XBee Network (Accepted)
Khalid Hasnan, Aftab Ahmed, Badrul-aishama, Qadir Bakhsh, Kashif Hussain
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ARPN Journal of Engineering and Applied Sciences (SCOPUS Indexed)
Conference Presentations
1 International Conference on Mechanical, Automotive and Aerospace
Engineering (ICMAAE 2013). Organized by: IIUM at Kuala Lumpur
Malaysia on July 2-4, 2013
2 2nd International Conference on Engineering and Technology ICET-2013
Organized by: TATIUC at Bali Indonesia on 12-13 December, 2013
3 2nd International Conference on Robotics, Automation Systems ICoRAS-
2013
Organized by: TATIUC at Bali Indonesia on 12-13 December, 2013
4 4th International Conference on Mechanical and Manufacturing
Engineering (ICME 2013)
Organised by: Faculty of Mechanical and Manufacturing Engineering,
Universiti Tun Hussein Onn Malaysia, at Bangi, Putrajaya, Malaysia on 17-
19 December 2013
5 International Conference on Mathematics, Engineering & Industrial
Applications 2014 (ICoMEIA 2014)
Organised by: Institute of Engineering Mathematics, Universiti Malaysia
Perlis Universiti Malaysia Perlis (UniMap) at The Gurney Resort Hotel &
Residences, Penang, Malaysia on 28th ~ 30th May, 2014
6
12th Global Conference on Sustainable Manufacturing
Organized by: Unversiti Technology Malaysia (UTM), Malaysia at The Puteri
Pacific Hotel Johor Bahru on 22-24 September 2014
7 5th International Conference on Mechanical and Manufacturing
Engineering (ICME 2014)
Organised by: Faculty of Mechanical and Manufacturing Engineering,
Universiti Tun Hussein Onn Malaysia, at Grand Preanger Hotel, Bandung,
Indonesia on 29-30 October 2014
8 International conference on Green Computing and Engineering
Technology 2015 (ICGCET'15)
Organized by: Gyancity Laboratory at Radisson Royal Hotel Dubai, UAE on
25-26 July 2015
9 13th Global Conference on Sustainable Manufacturing (Accepted)
xx
Organized by: Technische Universität Berlin (TU Berlin)
Vietnamese-German University (VGU), at Ho Chi Minh City / Binh Duong,
Vietnam on 16th - 18th September 2015
10 Malaysian Technical Universities Conference on Engineering and
Technology (MUCET) 2015 (Accepted)
Organised by: Malaysian Technical Universities Network (MTUN), at Johor
Bahru on 11-13 October 2015
CHAPTER 1
INTRODUCTION
Radio Frequency Identification (RFID) is an Automatic Identification and Data
Capture (AIDC) wireless technology is used for real time identification and data
collection of entities. It has been used since more than half century. Currently the RFID
technology is most commonly used in toll collection, logistics, asset tracking and
supply chain management. It has great potential to use in various applications.
Currently the enterprises are going towards advance RFID technology in place
of barcode system. However, RFID is an enabling and promising technology, even
though it has challenging issues of the optimal deployment of RFID network are tags
coverage, interference, economic efficiency and load balance (Chen et al., 2011b).
RFID network has multi-objective optimization functions, which can be solved by
optimization algorithm. However, the RFID reader has limited communication range
and high cost. It has been found that the RFID reader can easily integrate with XBee
(ZigBee) wireless mesh network to increase communication range. RNP-XBee
network can integrate with database connectivity and Internet of Things (IoT) to
enhance business benefits by data sharing among enterprises.
1.1 Research Background
Radio frequency identification (RFID) wireless technology has been used for automatic
identification and data capture of entities at real time locating system through
electromagnetic waves (Turcu, 2010). It has also been used in a library management
system and various other applications. This technology has been used by thousands of
2
companies for a decade or more. It quickly gained attention because of its ability to
track moving objects. As technology is refined, RFID tags are used in different works
tends to spreading throughout.
RFID and barcode technologies are used for the same purpose, but the principle
of operation is different and has various advantages. The advantages of RFID over
barcode are that it can track through human body and non-metallic materials. It does
not require direct orientation to scan. Moreover it can detect large number of items at
the same time and is able to read in harsh and dirty environment. RFID tags have longer
read range and large storage data as compared to the barcode tag and it can be writable
to update the data at any time (Lehpamer, 2008).
The implementation of RFID system based upon network configuration. The
RFID network planning (RNP) has some challenging issues that includes coverage,
interference, economic efficiency and load balance. Before deploying RFID readers
consider the basic requirement for achieving the optimized network such as minimum
number of readers deployed at strategic placement and best suitable parameter setting
for each reader (Chen et al., 2011b, Gong et al., 2012).
In this research particle swarm optimization algorithm was used innovatively
for solving RNP issues by using multi-colony global particle swarm optimization (MC-
GPSO) algorithm.
However, RFID reader has limited communication range and high cost. It has
been found that the RFID can easily be integrated with XBee (ZigBee) wireless mesh
network devices for increasing the node placement and wider the range of
communication (Bolic et al., 2008). XBee (ZigBee) is low cost and low power
consumption network device in RFID system. RFID-XBee integrated system can
increase the overall function and efficiency to get real time information of supply chain
effectively resulting to cut the product loss (shrinkage) and bullwhip effect (Sumi et
al., 2009, Elshayeb et al., 2009). RFID has been widely used in supply chain cycle
(Soon & Gutiérrez, 2008, Kok et al., 2008). Aim of every supply chain is to maximize
the overall benefits which depend on several decisions relating to the real time flow of
information, product, and funds for successful supply chain management (Darla et al.,
2012).
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This research focuses on novel approach to solve RFID network planning
(RNP) and to integrate with XBee (ZigBee) wireless network devices, database
connectivity and IoT. It enhances the efficiency of supply chain management.
The benefit of integrated system is to increase the range of communication of
RFID system by low cost XBee (ZigBee) network. It can provide accurate real time
visible picture of items flow status at single platform and update the database during
running operation. This information can share among networked organizations and it
is useful to forecast the business benefits at each level of supply chain. It could control
product loss or shrinkage. The system also has ability to significantly reduce the
wastage in terms cost, expenditure, time and services which makes the organizations
in supply chain green and sustainable.
1.2 Problem Statement
Mostly organizations use optical barcode technology for items scanning process,
because barcode system can easy to implement, less expensive/economic and it takes
few minutes to train the operator for scanning items. However, the barcode scanning
system has some drawbacks e.g. It needs proper orientation for scanning by human
intervention. Each item scan individually takes longer time and might be human error
happened by missing of an item during scanning activity. Currently business
enterprises are going towards advance RFID auto-ID technology for collecting the
object movement data, which can cut labor cost significantly (Kao & Lee, 2011). There
are various advantages of RFID over barcode technology in terms of accuracy, speed,
quality and flexibility of operational strategy and it can scan multiple items at longer
distance (Ferrer et al., 2010).
The implementation of RFID system based upon network configuration. It is
difficult to implementation in any specific area. The basic issues of RNP include
coverage, economic efficiency, interference and load balance (Irfan et al., 2012, Tsai
& Lin, 2013, Nawawi et al., 2014). Before deploying the optimal reader network
following queries are raised.
i. How many minimum readers are required to cover all tags?
ii. Where to deploy these minimum readers?
4
iii. What parameters are to be set for each reader?
The RFID network planning (RNP) is a multi-objective optimization problem
(Lee, 2010), need to solve innovatively using optimization techniques to achieve the
goal of optimum RFID network planning for sustainable competitive business benefits
of enterprise operations focus on green supply chain management.
Due the limited communication range and high cost of RFID reader, it has been
found that the RFID reader can easily integrate with XBee (ZigBee) wireless mesh
network devices. This can increase the number of node placement and enhance the
communication range of RFID reader (Sumi et al., 2009, Bolic et al., 2008).
The RNP-XBee integrated system is used to identify and data collection of
items at longer distance. The collected data can be monitored and updated on real time
basis at single control platform of LabVIEW database connectivity program (Elshayeb
et al., 2009). This data can be shared among other organizations, which are connected
in to the global network by using IoT to enhance the optimal business benefits.
1.3 Aim and objectives of research
The aim of this research was to develop an optimal RFID network and to integrate with
XBee (ZigBee) wireless network devices, database connectivity and IoT module, to
achieve the competitive business benefits of green supply chain management by real
time data exchange into the network organization. The specific objectives of this
research are included:
i. To develop and implement multi-colony global particle swarm optimization
algorithm for RNP issues.
ii. To integrate RNP with XBee wireless network devices.
iii. To integrate RFID-XBee network with database connectivity and Internet
of Things (IoT) module for data exchange into the network connected
organizations.
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1.4 Scope of the research
The scope of this research is wide aimed at enhancing business profits by improved
supply chain cycle through updated data on commodities on trade and in transit.
However solution of integrated RFID and XBee network will help:
i. Developing and implementing multi-colony global particle swarm optimization
(MC-GPSO) algorithm for the solution of RNP issues.
ii. Developing the physical RFID-XBee wireless communication module for data
collection of items and to communicate at longer distance.
iii. Developing a database connectivity module for RFID-XBee applications to
monitor the data collection of items at single control platform.
iv. Develop an Internet of Things (IoT) module, which is used for data exchange
to the business related organizations connected into the network to enhance
business benefits.
1.5 Summary
The outline of this research begins with the introduction of RFID and its application.
The background study is focused on supply chain management. On the basis of
background study the problem statement has to be identified and establish the aims and
objectives of research. Finally followed by scope of research is outlined to achieve the
target of research outcomes.
The literature review is explained in Chapter 2, which describe the Auto-ID
technology, shrinkage, the basics of RFID wireless communication system and its type
(near field & far field), link budget and read range, path loss propagation model,
optimization of RFID network planning by PSO, XBee (ZigBee) wireless mesh
network and its application are introduced. At the end the research gap is defined.
On the basis of research gap the research framework is explained in Chapter 3,
which describes the RFID network parameter and their objective functions (coverage,
interference and number of readers). The parameters and topology of search space was
set, and then represent coding of tags, reader and objective function. Followed by the
6
application of MC-GPSO its operating procedure and their simulation results are
explained.
The modules of RFID-XBee network, database connectivity, live video, IoT
and integrated module were developed and their implementation is explained in
Chapter 4. After development of integrated module, the results and their analysis are
explained in Chapter 5. Finally conclusion and recommendations are explained in
Chapter 6.
CHAPTER 2
REVIEW OF LITERATURE
The real time information is the back bone of every supply chain; this can be achieved
by Radio Frequency Identification (RFID) auto-ID wireless technology to meet the
target of real time information exchange of enterprise operations. The numbers of
organizations produce, distribute, handle or sell various goods. These organizations are
exploring what RFID can do to improve operating efficiency, product quality, reduce
inventory, shrinkage and bullwhip effect also drive additional revenue opportunities in
supply chain (Bottani et al., 2010). Decreasing of tag cost has been widely recognized
as the important factor influencing the widespread usage of RFID technology (Lin &
Ho, 2009). The wide adoption of RFID across the supply chain will bring significant
benefits leading to reduce operational costs and increase profits (Mueller & Tinnefeld,
2008). Many experts in financial matters suggested that, this will happen in following
basic areas.
i. Reduced inventory and shrinkage
ii. Reduce labor expenses in store, warehouse and on shop floor to get benefit.
iii. Minimize out-of-stock items
iv. Bullwhip effect
Various scientists are believed that the application of RFID technology would
not be failed; if following issues are to be resolved.
i. Tag prices and efficiencies
ii. RFID standards must be harmonize,
iii. Interoperability throughout the supply chain
iv. Large volumes of data handle by IT infrastructure
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v. Modification or change of work and labor practices
vi. cost of deployment properly shared
vii. Privacy issues
According to Alinean research, the new RFID projects could cut supply chain
costs by 3-5% and achieve 2-7% increase in revenue. RFID provides accurate and real
time visibility of entities in the supply chain. This can make every project as sustainable
to get benefits on long term basis. On average basis, over 90% of projects need a formal
business case justification in order to get approval of projects. RFID wireless
technology gives promise of bottom-line positive business benefits and a tangible ROI
(Pisello, 2006, de Souza et al., 2011) as shown in Table 2.1.
Table 2. 1: Tangible ROI as a bottom-line positive business benefits (Pisello, 2006)
Goal Typical Savings Tangible Benefits with Manufacturing Case
Study
Productivity improved
through automation
18% productivity
improvement $3.5M annual recurring labor cost savings
Reduce production-
related expectations
21% reduce in
expectations
$8.4M annual recurring labor and cost
avoidance
Reduce purchase order
processing costs
30% productivity
improvement
$860,000 annual recurring productivity
improvements/potential labor cost savings
Inventory savings 10% inventory reduction
(safety stock)
$500,000 one-time working capital savings
$55,000 annual recurring carry-cost reduction
Reduce inventory
scrap 45% write-off avoidance $40,000 in annual savings
Reduce days sales
outstanding
8% days sales
outstanding (DSO)
improvement
$5.7M one-time accounts receivable working
capital improvement
Reduce accounts
receivable disputes 40% dispute avoidance $2.3M annual write-down cost avoidance
Improve net fixed asset
utilization
2-3% NFA utilization
improvement $2M one-time working capital improvement
Lost asset recovery 40% reduction in loss
assets $25,000 annual recurring savings
Improve plant asset
maintenance 48% cost avoidance $75,000 annual recurring savings
Improve customer
satisfaction*
1.5% improvement in
customer retention
$1.5M annual recurring customer attrition and
replacement cost avoidance
Over all project summary
Total investment: $17M
Net Present Value (NPV) of benefits: $26M
Project time span: 3 years
Return On Investment (ROI): 188%
Payback period: 11 months
*Indirect (soft) benefits are risk adjusted to 10% of original value before calculating ROI
9
2.1 Auto-ID Technology
Klaus, (2010), presented the Automatic Identification and Data Capture (AIDC)
technologies are used for automatically identifying objects, data collection, and to
transmit that data directly in to computer systems without human intervention. AIDC
include the following technologies such as bar codes, biometrics, Optical Character
Recognition (OCR), smart cards, and Radio Frequency Identification (RFID), (Su et
al., 2007) as shown in Figure 2.1.
Figure 2.1: Important Auto-ID technologies (Klaus, 2010)
Automatic identification (Auto-ID) technologies are very popular at present; it
provides information about, people, animals and items in transit. Among these
identification technologies, barcode is the most widely used technology, because it has
very low cost but it has some deficiencies i.e. (low storage capacity and cannot be
reprogrammed and it need to be very close to optical reader for scanning).
However the RFID technology is superior to barcode technology because its
user does not need to know where an object is and does not need to get close to scan it
(Konsynski & Smith, 2003). Since RFID tags can be read at a distance and do not
require line-of-sight, it can provide more applications across a supply chain; which
holds a promise of significantly improving business operational efficiencies and
increasing the visibility of business objects. It also reduces inventory and shrinkage.
Auto-IDAuto-ID
RFIDRFID
Biometric Biometric
Optical Character Recognition
Optical Character RecognitionSmart CardSmart Card
Bar CodeBar Code
Fingerprint
procedure
Voice
identificatio
n
10
Stanton, (2005) presented that the tags are just high-tech barcodes, attached to items to
allow them to be tracked through the supply chain and make life easier at supermarket
checkouts. The other technologies are either lack of automation capability or lack of
ability to attach to business object.
A unified EPC and ISO, globally interoperable RFID standard is an ideal to
earn the full benefits of RFID applications (Baars et al., 2008). But due to the lack of
a complete security, privacy and unified RFID standard issues, it has caused many
people and companies to hesitate in adopting the RFID system (Stanton, 2005, Jungbae
et al., 2009).
2.2 Shrinkage
The one of the major issues in the supply chain management is product loss or
shrinkage. Radio-Frequency Identification (RFID) as an emerging technology has
generated tremendous amount of interest in the supply chain domain to reduce the
shrinkage. The shrinkage is the difference between recorded and actual inventory
(Elshayeb et al., 2010). The loss of inventory is caused by some factors, including
employee theft, shoplifting, administrative error, vendor fraud and damage in transit or
in store and cashier errors that benefit the customer. According to the National Retail
Security Survey, conducted by the University of Florida, shrinkage in the United States
during 2009 represented 1.44% of retail sales (A. Kok et al., 2008). This percentage
amounts to billions of dollars in lost inventory each year for U.S. retailers. Thus,
security guards, security tags and cameras are used by retailers as an effort to reduce
shrinkage.
2.3 Radio Frequency Identification (RFID) Systems
The RFID has become an integral part of our life. It increases productivity and
convenience. It has been used in many applications such as preventing theft of
automobiles and other commodities; tolls collection without stopping; managing
traffic; control entrance into buildings; automating parking; controlling access of
vehicles, corporate campuses and airports; distributing goods; providing ski lift access;
11
tracking library books; to track assets in supply chain management (Landt, 2005,
Sabbaghi & Vaidyanathan, 2008) describing the modality of this system. Dressen,
(2004) mentioned that this system works on different radio frequencies such as LF, HF,
UHF and Microwave based on its nature of utility. RFID has five basic components
such as tag, reader, antenna, middleware and application software (Chuang & Shaw,
2007, Ahsan et al., 2010). The working principle of an RFID system as an electronic
data carrier device “tag” is physically attached to the object having unique ID that is to
be identified. In a remotely application, RFID reader transmit radio wave signals
through antenna. Tags in the range of radio wave at a distance attached to the objects
will transmit response back through an attached antenna to identify the object
instantaneously (Asif, 2005). Then the collected data transmit to communication
infrastructure (middleware) which update the information, finally sends information to
the enterprise application according to the business requirements (Ahmed et al., 2014)
as shown in Figure 2.2.
Figure 2.2: Typical RFID System ((Hasnan, et al., 2013)
RFID helped millions of people around the world to protect their property and
make their workplaces secure. Its need for privacy issues that technology solves
through this viable system has also been realized (Stanton, 2005).
Ilie-zudor et al., (2006), has explained the overview of principles of the RFID
technology, tags and readers, commonly used frequencies and identifier systems,
12
current and predicted fields of application, as well as advantages, concerns and
limitations of use explained. It is further advised that the RFID needs to be standardized
in order to large-scale usage in the retail supply chain; this process is currently in
progress. On the global front, two international bodies are involved: EPCglobalTM
(www.epcglobalinc.org) and the International Organization for Standardization (ISO)
(www.iso.org) (Loebbecke, 2005).
Due to the numerous advantages of RFID systems as compared to other
identification systems, RFID systems have super seated the mass markets.
The RFID system is divided into two layers as shown in Figure 2.3.
i. Physical layer
ii. IT layer
Figure 2.3: RFID system layers (Karmakar, 2010)
2.3.1 Physical Layer
The physical layer comprises tag (transponder), reader (interrogator), and questioning
zone or interrogation zone (IZ).
I. Tag (transponder)
RFID System
Physical Layer
Tag
Interrogation Zone
Reader
IT Layer
Middleware
IoT
Enterprize Application
13
Tag is a microprocessor chip, consists of an integrated circuit with memory and antenna.
It is similar to the optical barcodes, which are attached to the items or case having
unique identification. It can be grouped in to basic categories are Power source,
memory type, operating frequencies, functionality, protocol, energy transfer and
communication. It may be active (battery powered and proactively radio frequency
signal) or passive (unpowered and reactively emitting a radio frequency signal).
Bhattacharya et al., (2011), proposed that the information about object could be serial
No; Model No. or other characteristics of object for identification purpose and
distinguish from others or to track the movement of object e.g TAG = [Type of product
| Subtype | Product-ID | Position | Date]. Various tags according to different application
requirements are shown in Figure 2.4.
Figure 2.4: Various RFID Tags (Ahmed et al., 2013)
II. Reader (interrogator/transceiver)
RFID reader is a device which talks to tags. A reader may support one or more
antennas; it can read and /or write data to an RFID tag (Su et al., 2007, Ngai et al.,
2008, Grillmayer, 2013). Its types are hand held, vehicle mounted, post mounted and
hybrid. The interfaces that connect the reader with the host computer are one or more
Microchip
Antenna
Capacitor
Contact Terminal
14
of the following: USB, Ethernet, Wi-Fi, RS232, RS485, PCMCIA, and Compact Flash
etc Su et al., (2007). Readers basically contain two components: the antenna and the
interrogator circuitry. The antenna is used for communication with the tag using
electromagnetic waves. Whereas the interrogator circuitry is a channel or negotiator
between the reader antenna and the IT layer. Interrogator circuitry performs the task of
sending data through the reader antenna and also receiving data and then sending it to
the back end for processing. Interrogator circuitry also carries out an action of
coordination between different reader antennas for the efficient and successful reading
of tags.
III. Interrogation Zone (IZ)
According to Karmakar, (2010), the interrogation zone is the Euclidean space (three-
dimensional physical space) between reader and tag where the electromagnetic (EM)
wave is used for communication activity of reader reads/writes data from/to a tag. The
basic characteristics of interrogation zone are defined in detail as follows.
2.3.2 Electromagnetic Propagation (Transmission)
According to Hunt et al., 2007, Brown et al., 2007, Thornton & Sanghera, 2011, an
electromagnetic wave propagates in the direction to the right angles with the vibrating
electric and magnetic field vectors. It carries energy from its base station radiation
source “RFID reader” to the tag. Figure 2.5 shows that the electric and magnetic fields
are perpendicular to each other.
All electromagnetic waves travel at the same speed in vacuum, at the speed of
light, 299,792,458 meters per second (m/sec). The speed of light is denoted by the
lowercase letter c and is usually approximated to 3×108 m/sec is used for all
calculations.
15
Figure 2.5: Electromagnetic wave propagation (Brown, 2007)
The relationship of speed of electromagnetic waves (c), with frequency (f) and
wavelength () is as follows;
𝑐 = × f (2.1)
As electromagnetic waves travel in 3D space, the same power is dispersed in
all radial directions of the surface of sphere. The power density reduces as the wave
travels away from the source. This phenomenon is called path loss. Figure 2.6 shows
a transmitter antenna TX at the center of a sphere and a receiver antenna RX at the
surface of the sphere. The distance between the two antennas is “d” and the effective
area of the receiver antenna is A.
𝑃𝑎𝑡ℎ 𝐿𝑜𝑠𝑠 =𝑅𝑥 𝑒𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑎𝑟𝑒𝑎
𝑡𝑜𝑡𝑎𝑙 𝑎𝑟𝑒𝑎 𝑜𝑓 𝑠𝑝ℎ𝑒𝑟𝑒=
𝐴
4.𝜋.𝑑2 (2.2)
The power density (PD) of a radio wave at a distance (d) from its source is
inversely proportional to the square of the distance, or power attenuates with the square
of the distance.
Mathematically PD 1/d2.
16
Figure 2.6: Electromagnetic wave path loss in free space (Dobkin, 2008)
2.3.3 Electromagnetic Waves (Radio Waves)
According to Dobkin, (2008) Radio waves are part of the electromagnetic spectrum. It
has longest wavelength in the entire electromagnetic spectrum. The range of radio
waves available at different frequencies bands include {LF (30kHz-300 kHz), HF
(3MHz - 30MHz), UHF (300MHz - 1000MHz) and Microwave (1GHz - 6GHz)}.
RFID technology uses the radio waves among the available frequencies from
LF (125 kHz -134 kHz), HF (13.56 MHz), UHF (433 MHz & 860 MHz -960 MHz)
and Microwave (2.4 GHz to 5.8 GHz) as shown in Figure 2.7.
Figure 2.7: Electromagnetic wave (Dobkin, 2008)
RX
A
nt
en
na
17
An RFID system is working on different operating frequencies according to the region
of the world located, as shown in Figure 2.8.
The selection of operating frequency of RFID readers and tags for specific application
depends upon various parameters to be considered. These parameters are maximum
read range (especially for passive tags), reading speed, sensitivity to water and
humidity etc. Application of different operating frequency bands are illustrated in
Table 2.2.
When the radio waves travels in the medium, their signals are attenuated in different
ways according to the objects properties in their path. The attenuation of signal strength
is called path loss. The propagation of original signals will vary in their strength due to
the objects in their path than the resultant (signal strength) received is reduced.
Figure 2.8: Summary of worldwide UHF band allocations (Dobkin, 2008)
Table 2.2: Application of operating frequencies in RFID system (Curtin, 2007)
18
Frequency
band
Description Operating
Range
Applications Benefits Drawbacks
(125-134)
KHz
LF <0.5m or 3
ft
Access Control
Animal Tracking
Vehicle
immobilizers
Product
authentication
POS applications
Work well
around water
and metal
products
Short read
range and
slower read
rates
13.56 MHz HF <1m or 3 ft Smart card
Smart shelve tags
for item level
tracking
Library books
Airline baggage
Maintenance data
logging
Low cost of
tags
Lower read
range than
UHF
433 MHz UHF (1–100) m
or 300ft
Defense
applications, with
active tags
Larger read
range
Higher tag cost
(860-930)
MHz
UHF 3m or 9.5 ft Pallet tracking
Cartoon tracking
Electronic toll
collection
Parking lot access
EPC standard
built around
this frequency
Does not work
well around
items of high
water or metal
contents
2.4 GHz Microwave 1m or 3 ft Airline baggage
Electronic toll
collection
Fast read rates Most
expensive
The signal strength quality and level is very important in the RFID system designing
and application. It is measured in dBm or mW. It depends upon the distance between
the transmitter (Tx) and receiver (Rx) (Dobkin, 2008). The power in dBm is the 10
times the logarithm of the ratio of actual Power/1 milliWatt.
The formulas are used to measure power in dBm and power in watt as follows.
P(dBm) = 10 · log10( P(W) / 1mW )
P(W) = 1W · 10(P(dBm) / 10) / 1000
Where
P(dBm) = Power expressed in dBm (decibel milliwatts)
P(W) = the absolute power measured in Watts
mW = milliWatts
log10 = log to base 10
The power calculated in dBm and milli-watt is shown in Table 2.3
Table 2.3: Power comparison in dBm and mW
19
The negative number is representing small value but it shows positive number
on a logarithmic scale. In logarithms, the value indicated represents an exponent. for
example, under a log 10 scale, a value of -1 represents 10 to the -1 power, which equals
to 0.1. Similarly a value of -2 represents 10 to the -2 power, which equals to 0.01. In
similar manner, a negative dBm means that a negative exponent in power calculations;
0 dBm equals 1 mW of power, so -10 dBm equals to 0.1 mW, -20 dBm equates to 0.01
mW, and so forth. a weak signal as -100 dBm equal to 0.0000000001 mW.
Radio signal propagates in the RFID system and is used as free space
propagation. It is the short range communication system (Brown et al., 2007). For
economic and technical reasons, the standard of spectrum is harmonized worldwide for
regulating various aspects of radio spectrum use. There are two types of
communication methods in RFID system relative to the frequency of operation and
distance between reader and tag are near field or inductive coupling and far field or
backscatter coupling (Karmakar, 2010).
P(dBm) P(mW)
Strong Transmitter
Sensitive Receiver
50 100000
40 10000
30 1000
20 100
10 10
0 1
-10 0.1
-20 0.01
-30 0.001
-40 0.0001
-50 0.00001
-60 0.000001
-70 0.0000001
-80 0.00000001
-90 0.000000001
20
2.3.4 Near-Field/Inductive Coupling
Coupling is the full duplex communication or transfer of EM energy between reader
and tag (Want, 2004). Near field is the three-dimensional space surrounded by an
antenna, where the plane wave has not yet fully developed it is separated from the
antenna. The magnetic field strength attenuates as inverse cube of the distance (∝1/ d3).
The distribution of waves in near field is fairly omni-directional, and the magnetic field
strength is translated in to power available to the tag, the power attenuates is inversely
proportional to the sixth power of the distance (d) from the antenna (∝1/ d6). The
energy transfer through shared magnetic field and frequencies of operation used are LF
and HF of RFID tags (Brown et al., 2007). The boundary limit of near field
communication or the range of outer edge depends upon frequency of operation and
size of antenna. The transmission of energy fluctuates by change of current flow
through “inductive coil.” in one device that induces current flow in the other device in
a “push–pull” manner, and the antenna used as a transformer (Karmakar, 2010). The
applications of RFID near field are item tagging, animal tagging, and library database
management system etc.
2.3.5 Far-Field/Backscatter Coupling
The area in the three-dimensional space beyond the near field is called “far field”. The
communication between tag and reader takes place by EM radiation backscatter
coupling (Want, 2006). EM energy is continuously transmitted “away” from the
antenna in a radial manner and the power drops, obeying the inverse square law of
distance (d) from the antenna (∝1/d2). The EM energy transmits from the reader’s
antenna and encounters the tag’s antenna, where it is reflected or absorbed depending
on the tag antenna’s radar cross section (RCS) or reflection cross section. If the tag is
terminated with a matched load, almost no energy is reflected back, whereas if the tag
has an open/short-circuit termination, most of the energy is transmitted back (Karmakar,
2010). The tag IC, depending on the data to be transmitted to the reader, switches
between a load and an open/short circuit and thus controls the reflected EM wave. This
technique of changing RCS of the tag antenna is called the “antenna load modulation.”
21
This reflected EM wave, which is much smaller in magnitude compared to the incident
wave, is detected at the reader antenna by means of a directional coupler/circulator and
then amplified, decoded to extract the data sent by the tag. This kind of communication
is prevalent in the UHF and microwave frequency ranges of passive RFID tags (Brown
et al., 2007). The communication efficiency depends on the size of antenna. If the
largest physical linear dimension of antenna is greater than the wavelength, it will be
the much higher efficient as compared to inductive coupling. It is found that if increase
the power level consequently the communication read range increases between reader
and tag.
The region between the reactive near field and the far field is a transition region
and is known as the “radiating near field (or Fresnel region)” where the reactive field
becomes smaller than the radiating field. All three field regions are summarized in
Table 2.4 and shown in Figure 2.9 (Huang & Boyle, 2008).
Table 2.4: Conditions of Near-field and far-field region (Huang & Boyle, 2008)
Antenna size D D << D ≈ D >>
Reactive near field d < / 2 d < / 2 d< / 2
Radiating near field / 2 < d< 3 / 2 < d< 3 and 2D2/ / 2 < d < 2D2/
Far field d > 3 d > 3 and 2D2/ d > 2D2/
Where
D = Maximum linear dimension of antenna in (m)
d = Radial distance from (reader to tag) antenna in (m)
= Wavelength of radiated signal in (m)
22
Figure 2.9: Radiated field regions of an antenna having maximum dimension D
2.3.6 Link Budget and Read Range
Link budget calculation in wireless communications specifies the power budgeting for
the transmitter and receiver, the antenna gain, and effective isotropic radiated power
(EIRP) of the reader antenna to obtain a certain link distance (reading range). The link
budget helps to calculate the required antenna gain and related specification to obtain
a robust and viable communication in the specific conditions of wireless
communications. The communication from the reader to the tag is called the “downlink”
and the communication from the tag to the reader is called the “uplink”.
Therefore, the link budget is a calculation used to specify the read range in any
RFID system. It encounters all the losses and gains taking part in the communication
23
and thereby, depending on the sensitivity of the components, determines the distance
at which reliable communication can take place between the tag and the reader in any
RFID system. Factors like noise floor, cable losses and free space losses are taken into
account in calculating the link budget (Brown et al., 2007, Karmakar, 2010).
2.3.7 Path loss propagation Model
In every RFID system it is important decision to select path loss propagation model. It
is defined as the difference between the transmitted power form source antenna and the
received power at receiver antenna. The propagation model can calculate the estimation
of coverage area of RFID reader accurately.
The signals are attenuated by the distance between the reader and tag,
interference from adjacent readers and obstacles in the system. The most common path
loss propagation models and their parameters are shown in Figure 2.10.
These models are grouped on the basis of downlink or the uplink
communication channels. For the downlink channel the free space, two-ray and
multipath models are used. These same path loss propagation models can be used for
uplink channel and in an addition of the radar cross section (RCS) model used for
more precise calculations. The each type of path loss propagation model is described
as follows.
24
Figure 2.10: Path Loss Propagation Models (Huang & Boyle, 2008)
2.3.8 Free space propagation Model
The communication between Tx antenna and Rx antenna in Free Space (FS)
propagation model takes direct Line of Sight (LoS). The FS propagation model is
desirable for outdoor RF communications without obstacles in the environment. It also
can be used in an indoor environment in the far-field region. The signal power at the
receiving antenna is calculated by Friis's transmission equation as shown in equation.
𝑃r = 𝑃𝑡 × 𝐺𝑡 × 𝐺𝑟 × (
4 𝑑)2 2.3
d = 𝑐
𝑓⁄
4√𝑃r/𝑃𝑡×𝐺𝑡×𝐺𝑟 2.4
Where
= signal wavelength (m)
c = Speed of light (m/s)
f= operating frequency (Hz)
Pr = received signal strength (W)
126
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