Conference Proceedings Vol-I

CONFERENCE PROCEEDINGS BOOK

(Volume I)

iii

International Conference on Modeling and

Simulation

November 25-27, 2013

Department of Mechanical and Aerospace Engineering

Institute of Avionics and Aeronautics

Air University, Islamabad, Pakistan.

Phone: 051 9262557 (ext. 475)

Email: [email protected]

Website: http://portals.au.edu.pk/icoms-2013

http://auconferences.com/icesp

iv

Preface

Air University (AU), a federally chartered public sector university of Pakistan, is a research-intensive

university with focus on many disciplines which include Engineering (Mechanical, Aerospace,

Avionics, Electrical and Mechatronics), Basic Sciences (Computer Science, Physics and

Mathematics), Business Administration and Social Sciences. It has been successful in becoming a

university of choice for national students in a relatively very short span of time. The faculty and

students of the AU are very much focused in both theory and research in the major disciplines

mentioned above. AU has organized the International Conference on Modeling and Simulation

(ICOMS-2013) as part of its vision and mission as a renowned university of Pakistan. Such

conferences are invaluable for dissemination and sharing of knowledge by experts. More such

conference are planned by AU including the International Conference on Energy Systems and Policies

(ICESP-2014), to be organized in November 2014.

Modeling and Simulation (M&S) is a multi-disciplinary specialization relevant to the design

of applications ranging from house-hold to hi-tech products. M&S techniques have become the basis

of rapid prototyping (RP) and rapid product development (RPD) of industrial products. This is both

cost and time effective for products such as 550-passenger Airbus and 1000-passenger Boeing

Aircrafts. Advanced fighter planes such as F-18 Hornet are designed entirely in M&S environment.

These techniques are not only the basis of RP and RPD for engineering products, but also touch

almost all aspects of human life from social behavior to econometrics, business, education, defense,

and even entertainment. The revolution in computers has caused the public awareness of such

techniques. The main aim of the conference was to bring together leading scientists, engineers,

researchers, scholars and academics to exchange and share their experiences and discuss their

research results about all aspects of M&S, and discuss the practical challenges encountered and the

solutions adopted. Such solutions are invaluable for the wellbeing and sustainable development of a

modern progressive society. Many collaborative research endeavors and international MoUs for

exchange of students and faculty, and joint research and degree programs have resulted from this

conference.

An over-whelming response and interest was shown by both national and international

scholars. The total number of technical submissions received, were around 400. After a rigorous

double-blind peer review, only 43% of the total submissions qualified for technical oral presentations,

which appear in this conference proceedings book.

Conference Secretariat

Prof. Dr. Muhammad Afzaal Malik (Conference Chair)

Prof. Dr. Muhammad Naeem (General Secretary)

Engr. Muhammad Sohail Iqbal (Assistant Secretary)

Mr. Muhammad Shoaib Zafar (Conference Coordinator)

v

Acknowledgement

The conference secretariat is highly indebted to Dr. Ijaz A. Malik, our worthy vice chancellor or his

vision, motivation and continuous support for this conference. Thanks are also due to our national and

international key-note/invited speakers, technical participants, reviewers and Air University

administration without whose support, this conference would not have been possible. The compilation

and editing of this compendium was a very laborious task to be accomplished over a relatively very

short period of time. However, this up-hill task was completed with the help of dedicated and

committed hard work of our volunteer scholars under the supervision of Engr. Ahad Nazir, Mr.

Shoaib M. Zafar and Engr. Sohail Iqbal. The volunteer scholars who rendered valuable serviced for

the compilation of this proceedings book are listed below:-

1. Mr. Asaad Hameed 2. Mr. Hamza Bin Ejaz 3. Mr. Mohsin Ali 4. Engr. Ahsan A. Malik 5. Mr. Syed Saad Ali

Conference Secretariat

vi

Table of Contents

Prefaceiv

Acknowledgement..v

Successful CRM (Customer Relationship Management) Implementation and Its

Benefits Nida Shabbir, Farhan Azmat and MirGhulam Kibria.1

Modelling and Simulation of Height Processor of a Generic 3D Radar

Dr Ali Javed Hashmi, Dr Shahid Baqar, Sher Hassan Arbab and Hamza Malik9

Design and Analysis of a Flapping Wing Micro Air Vehicle (FMAV) capable of producing flap

and pitch simultaneously

Hasnain Raza Sarwar, Syed Saad Ali, SohailIqbal and Waseem Abbas.15

Numerical Modeling of Coupled Convection and Radiation Heat Transfer in a

Cylindrical Pit Furnace

Muhammad F. Iqbal, Mansoor H. Inayat and Imran R. Chughtai...21

Layered Network Security Policies on Osi Model

Sabeela Pasha, Attique Shah, Muhammad Aadiland Abdul Rehman..29

The Impact of Number of Interfaces on Ticrn Films Properties

Fawad Ali, Joon Seop Kwak and Fawad Ali38

Design & Development of Surveillance RC Platform

Rizwan Malik , Sagar Riaz, Adnan Maqsood, Farooq Akram, Taimur Shams Abid Ali Khan

and Abdul Munem Khan .42

Study of Effect of Various Joint Boundary Conditions on Stiffness Behavior Of 6DOF

Platforms Top Plate

Umar Nawaz Bhatti, Aamer Ahmed, BaqaiandWasim A.Tarar..48

Bond Graph Modeling of Operational Amplifier and Some of its Applications

Muhammad Wajih Ullah Siddiqi, Muhammad Hameed Siddiqi, Arslan Khalil and A

Mahmood......56

Design and Simulation of Feed Network for Phased Array Radar

Flying Officer Anam, Wing Commander Dr. Shahzad Arshad and Wing Commander Dr.

Muddassir Iqbal....61

Some Simulation Results Pertaining to the Estimation of the CDF and CHF of the

Self-Inverse at Unity Half-Cauchy (SIUHC) Distribution

Syeda Shan E Fatima and Saleha Naghmi Habibullah..65

vii

Evaluation of Fuel Cell Models at Specific Operating Conditions

Bilawal Rehman, Usman Inayat, Dr. A.A.Bhatti, Mashood Nasir and Waqas Tariq

Toor..70

A Local RBF Approximation Method for Time-Dependent Partial Differential

Equations

Marjan Uddin and Muhammad Imran..75

Wind Tunnel Testing Of a Scaled Down Model of Store Carrying Rack in Low Subsonic

Wind Tunnel

Ahmed Bilal, Taimur .A. Shams, Abid A Khan and Kashif Mehmood...79

Control Algorithm Design of Single-Phase Inverter for Zno Breakdown Characteristics

Tests

Kashif Habib, Zeeshan Ayyub, Zheng Xiancheng and Muhammad Imran Nawaz.85

Population Growth and Ecomonic Growth Comparison between Developed and

Developing Countries

Shoaib Ali and Aftab Ahmed Khakwani.93

An Improved P&O MPPT for Distributed PV Applications

Ali F Murtaza, Hadeed Ahmed Sher, Marcello Chiaberge, Diego Boero, Mirko De Giuseppe

and Khaled E Addoweesh..101

Indirect Adaptive Neurofuzzy Based MIMO Control for Multi-type FACTS Controllers

Rabiah Badar and Laiq Khan.108

Chaos based Secure and Reversible Watermarking

Muhammad Tahir Naseem, Atta-ur-Rahman, Ijaz Mansoor Qureshi and Muhammad Zeeshan

Muzaffar.115

Shape Preserving Monotone Surface Data Visualization by Spline Function

Muhammad Abbas, Ahmad Abd Majid and Jamaludin Md Ali120

Coordinated Search with Agent Based Modeling of UAVs using SoS-Engineering

Approach

Khalid Rafique, Mansoor Ahsan, Adnan Ali, Samina Jamil and Hamza Rafique.128

Which web browser work best for detecting phishing

Noman Mazher, Imran Ashraf and Ayesha Altaf...133

Enhancement of Smoke Generation System Endurance Using Cfd

Nabeel Khan, Taimur .A. Shams, Muhammad Ayaz and Abid A. Khan...137

Fluid Structure Interaction of An Oscillating Wing For Flapping Wing Micro Air

Vehicle Applications

Muhammad Arsalan Khan and Dr. Nadeem Shafi Khan...143

viii

Modeling, Simulation and Analysis of Static Aeroelastic Mechanism on an Aircraft

Wing In Ansys

Imran Hayat and Dr. Nadeem Shafi Khan.150

Sensorless Temperature Estimation for Thermal Protection of Vector Controlled AC

Drives Using Fuzzy MRAS

Syed Ali, Asad Rizvi and Dr. Muhammad Bilal Kadri..158

Investigation of Micro-Strains in structural Members using Finite Element Analysis

(FEA)

Assad Anis..165

FPGA Based Compact and Re-configurable 3G Transceiver

Taimur Hassan, Amna Waheed, Adeel Ejaz and Freeha Azmat171

Wireless 3G AV transceiver with Additive White Gaussian Noise channel (Using

MATLAB)

Taimur Hassan and Freeha Azmat.177

A low Cost, Efficient Solution to Desalination of Water Using Solar HDH Technique for

Developing and Impoverished Countries

Shah Zamin, Zhang Lixi and Zahid-Ur-Rehman...182

Complication of Diabetes in District Dir Lower

Zahid Khan and Dr. Sohail Akhtar.192

Dimensional Inspection System for Meso scale Artefacts using Sub pixel Edge Detection

Technique

Adeel Wahab, Azfar Khalid, Umar Shahbaz Khan196

Simulation-Based Hardness Evaluation of a Multi-Objective Genetic Algorithm

Shahab U. Ansari and Sameen Mansha..201

Robust and Reliable Motion Detection and Security Calling System Based on

ARDUINO

Rashid Naseem, Muhammad Usman, Haseeb AhmadMuhammad Babar, Muhammad

Nauman Barki and Sajid Ullah Khan.205

Design of Solar Lighting System for Energy Saving

Irfan Ullah, Qurban Ullah, and Seoyong Shin...209

Energy-efficient Daylighting Systems for Multi-story Buildings

Irfan Ullah, Qurban Ullah, and Seoyong Shin...215

Multigrid Method for Piecewise Smooth Chan Vese (CV) Image Segmentation Model

Hadia Atta, Noor Badshah and Hena Rabbani...222

Variational Models for Image Segmentation with Inhomogeneous Regions

Hena Rabbani, Noor Badshah and Hadia Atta...228

ix

Validation of a Thermosyphon Model and Evaluation of the Effects of Different

Boundary Conditions on Its Performance Using Two-Fluid Methodology

Khurram Kafeel and Ali Turan..234

Bond Graph Modeling With Control Synthesis of Coordinated Fingers Movement.

Maryam Iqbal, Mona Jaffer and Dr. A.Mahmood.240

Development of a Generic Flight Simulator for Fixed Wing Aircraft

Salman Ahmad, Mansoor Ahsan and Farrukh Mazhar..246

Analysis on Measurement Ofvolume of Blood in Human Vesselsa Bond Graph

Approach

Sana Javed and a Mahmood...252

Layup Optimization of Laminated Structures

Mohsin Iqbal, Dr. Afzal Khan, Muhammad Iqbal and Dr. Khizar Azam.259

Does stock price volatility originate from macro shocks? South Asian evidence

Javed Iqbal and Sadia Aslam.263

A Comparative Study On Economic and Sensitivity Evaluation of Different Types of

Efficient Solar Collectors for Domestic Solar Water Heating in Pakistan

Aamir Mehmood, Adeel Waqas and Hammad Ghaffar.269

Optimization of Leading And Trailing Edge Profiles Of Cross Flow Turbine

Mujahid Naseem, Javed A. Chattha and M. Usman Safdar...275

Design and Analysis of Human Resource Decision Support System for Academic

Institutions

Sajid Ullah Khan282

Static vs. Dynamic Analysis of Reinforced Concrete Structures

Huma Khalid..285

Short Circuit Stress Calculation in Power Transformer Using Finite Element Method

Ashfaq Ahmad, Dr. Muhammad Kamran and Asim Maqsood..289

Bond Graph Modeling and PID Controller Stabilization of Single Link Mechanical

Model

Madiha Zoheb and A. Mahmood...297

Optimization of Physical Dimensions for Efficient Parabolic Trough Collectors Using

Mathematical And Computational Models

Gussan Maaz Mufti, Danial Naeem and Dr Adeel Waqas.302

A Nonlinear Steam Boiler Control Based On Adaptive Recurrent Neurofuzzy Strategy

Shahid Qamar, Laiq Khan and Usman Khalid...308

x

Level Control of Coupled Three Tank System Using Adaptive Neurofuzzy Control

Approach

Shahid Qamar, Laiq Khan and Usman Khalid...314

The Blind Adaptive Equalizer Based On Improved Constant Modulus Algorithm

Sana Abid Khan and Shahzad Amin Shaikh..320

Formulation of a Precise Model Governing the Electrical Characteristics of Nickel

Metal Hydride Batteries

Faizan Pervaiz, Ali Imran Rashid, MashoodNasir and Dr. A. Aziz Bhatti324

A Computer Model for Investigating Heat Transfer Characteristics of a Phase Change

Material

Ali Ehsan and Muhammad Saqlain329

Study on the Impact of Integrating Modeling and Simulation in Teachers Training

Anjum Bano Kazimi, Amatul Zehra and Munir Moosa Sadruddin...333

Predicting the Potential of Renewable Energy Resources in Pakistan as Cleaner

Alternatives to Natural Gas, by Using LEAP Model

Aasma Bibi, Rabia Shabbir and Sheikh Saeed Ahmad..337

Simulation study of 100 MWe Solar Thermal Parabolic Trough Power Plant at

Cholistan Desert in Pakistan

Irshad Ahmed and M Khurram Zafar.343

Probabilistic Forecast and Its Validation for Cold waves of Jhelum and Muzaffarabad

by Using Single Model Ensemble Prediction

Shahzadi Amna, Bushra Khalid and Muhammad Abdul Rahman.349

Personal Integrated Process Based Software Architecture Design and Evaluation

Waqar Ul-Hasnain Khokhar and Shahbaz Ahmed.354

Substrate Integrated Waveguide (SIW) to Microstrip Transition at X-Band

Muhammad Imran Nawaz, Khalid Zakim, Kashif Habib, Z. Huiling, Aurangzeb Khan and

Muhammad Kashif.361

Design and Optimization of a Cross-flow Micro Hydro Turbine using Modeling and

Simulation Techniques

Ahsan A. Malik, Khurram Shehzad, Muhammad Zain and Afzaal M .Malik...365

Sensorless Temperature Estimation for Thermal Protection of Vector Controlled AC

Drives Using Fuzzy MRAS

Syed Ali Asad Rizvi and Dr. Muhammad Bilal Kadri...370


Model


xi

ClassSpy: Java Object Pattern Visualization Tool

Tufail Muhammad, Zahid Halim and MajidAli Khan...382

Evaluation of Fuel Cell Models at Specific Operating Conditions

Bilawal Rehman, Usman Inayat, Dr. A.A.Bhatti, Mashood Nasir and Waqas Triq Toor.388

Dimensional Inspection System for Meso scale Artefacts using Sub pixel Edge Detection

Technique

Adeel Wahab, Azfar Khalid and Umar Shahbaz Khan..394

.

Adaptive Trajectory Control of Wheeled Mobile Robot (WMR)

Kanwal Naveed, Zeashan Khan, M. Salman, M. Bilal malik and M. Usman Ali..399

Bond Graph Modeling & Design Of Pid Controller Of Air Pump System Using 20-Sim

And Matlab

S.M.Fasih-ur-Rehman, S.M.Fazal-ur-Rehman, Usman Ali Khan, Abdul Rehman Chishti and

Mohammad Jawad Masud..406

Bond Graph Modeling of Customized Robotic Arm

Tayyaba Qaisar, A. Mahmood and Mariam Javaid412

Optimization Of Leading And Trailing Edge Profiles Of Cross Flow Turbine

Mujahid Naseem and Javed A. Chattha.418

Simulation: An Effective Teaching Strategy in Social Sciences

Dr Aamna Saleem Khan and Nasir Iqbal...425


Model


An Efficient Hybrid Digital Watermarking Technique

Dr. Muhammad Kamran, Asim Maqsood, Ashfaq Ahmad and Syed Baqaar Hussain..........435

A Local RBF approximation method for time-dependent partial differential equations

Marjan Uddin and Muhammad Imran442

Medical Image Tamper Localization and Lossless Recovery Using Digital

Watermarking Technology

Gran Badshah, Siau-Chuin Liew, Jasni Mohamad Zain and Syifak Izhar Hisham...446

Miniaturization of Microstrip Patch Antenna with Defected Ground Structure for

Multifunctional Communication Systems

Syed Imran Hussain Shah, Shahid Bashir, Ahsan Altaf and Ghazala Sahib.452

Stability Analysis of a Generic Conveyor Belt System Using Bond Graph Modeling

Technique

Aamir Mairaj, Faraz Sheikh and Rohail Tahir..456

xii

Conceptual Design and Fabrication of Scale-up Mechanical Drive System for a

Flapping Wing Vehicle

Farrukh Mazhar, Arsalan Ali, Nadeem Shafi and Mansoor Ahsan462

Validation of a Thermosyphon Model and Evaluation of the Effects of Different

Boundary Conditions on Its Performance Using Two-Fluid Methodology

Khurram Kafeel and Ali Turan..470

Turbulent Flow Characteristics Of An Open Channel With Stress-Free Rigid Lid

Imran Afgan, Stefano Rolfo, Tim Stallard, David D. Apsley,, James McNaughton and Peter

Stansby...476

Mechanical Enhancement of Glass fiber/epoxy Nano Composites based on Spraying

Methodology with Vacuum Assisted Resin Transfer Molding

Sarim Ali a, Boming Zhang, Wang Changchun and Musharaf Abbas486

Local Badshah-Chen Model for Image Selective Segmentation

Haider Ali, Gulzar Ali Khan, Nosheen, Noor Badshah and Ghulam Murtaza..492

Investigation of higher voltage levels for National Transmission and Dispatch Company

Network Pakistan

Muhammad Faisal Nadeem Khan, Prof.Dr.Tahir Nadeem Malik and Bilal Asad.497

Design and Simulation of a Flapping Mechanism with Asymmetric Frequencies for a

Micro Air Vehicle

Sohail Iqbal, Hammad Nazeer Gilani, Raja Amer Azim and Dr. M.Afzaal Malik...503

A Novel and Compact Planar Inverted F-Antenna (PIFA) for Bluetooth and WLAN

Mobile Phone Applications

M. Muzammel, U. Rafique, A. H. Jaffari and Q. D. Memon508

Modeling the Pipeline in Repairing-Using Simulation

Nosaibeh Nosrati Ghods513

Interpolation Of Two Dimensional Functions Using Radial Basis Function And Haar

Wavelets

Majid Khan, Siraj-ul-Islam and Imran Aziz.520

Approximation of One Dimensional Functions Using Radial Basis Functions and Haar

Wavelets.

Mohammad Taufiq and Siraj-ul-Islam.525

Replacement of CNG in Pakistan with Hybridized solar, Biogas and fuel cell based

Hydrogen filling Stations

Muhammad Faisal Nadeem Khan and Bilal Asad...530

Comparison of Evolutionary Algorithm over Multi objective Optimization Problems

Wali Khan Mashwani..535

xiii

An improved method based on Haar wavelets for numerical solution of nonlinear

integral equations

Imran Aziz and Siraj-ul-Islam.542

Author Index. 548

1

2013-197-001a

Successful CRM (Customer Relationship

Management) Implementation and Its Benefits

Nida Shabbir

Bahauddin Zakariya University

Sub campus sahiwal

[email protected]

Farhan Azmat Mir Bahauddin Zakariya University

Multan

Ghulam Kibria

Bahauddin Zakariya University

Sub campus sahiwal

[email protected]

AbstractCustomer relationship management focuses on

building long-term and sustainable relationships that add

value for both customer and the organization. This

research addresses the issues regarding customer

relationship management implementation and its benefits

based on its successful implementation. The basic purpose

of this research is to investigate the link between

organizational implementations of customer relationship

management and its benefits. This paper employs the

approach of identifying what influence companies can

expect from Customer Relationship Management

implementation on performance and how they can leverage

its implementation impact by using factor analysis and

ANOVA. Analyzing the results of empirical study,

conducted across five telecommunication companies

indicates that management commitment have direct

relationship with the CRM implementation, that enhances

the organizational ability to retain customer and gain

strategic advantage over its competitor. The Customer

Relationship Management successful implementation and

software applications will help organizations to measure

the effectiveness of their CRM activities. And increase in

customer satisfaction, retention, loyalty and profitability.

The research strategy was to survey CRM implementation

activities in organizations that are being incorporated on

what level, looking for similarities and complementarities

in their nature of business strategies. First, the paper

identified the successful determinants of CRM

implementation, their CRM strategies. The paper then

collected detailed information on CRM benefits, in terms of

tangible and intangible.

Key words: CRM, Organizational Implementation, Telecom

I. INTRODUCTION

In todays business world, it is an important objective

for Organizations to make customers satisfied because

they are the ones who keep the business running (Buttle,

1996;Gefen & Ridings, 2002;Ngai 2005) CRM core

concept is simple; organizations are focused on the

efficiency and cost cutting within their organizations,

management is facing problem of acquiring new

customers and retaining customer CRM provides

solution for management to build long term relation with

customer and become customer centric which directly

increase the market share as well as profitability. The

concept is easy theoretically but practically it is quite

difficult and time consuming. CRM needs commitment

of a customer centric vision from top management and

heavy investment and restructuring of organization

processes and strategies.

Fast communication is important tool to survive in the

era of globalization. Trends of telecommunication are

changing rapidly bringing improvement in the overall

economy of the country (PTA, 2006). It is a prime

objective of Pakistan telecommunication authority to

facilitate this process and make telecommunication

services available to every citizen of Pakistan (PTA,

2006).

Telecoms sector of Pakistan is said to be growing at a

fast pace yearly. In fact Pakistan has the highest mobile

penetration rate in the South Asian region. With 170

million population of Pakistan now has 63.1 percent

teledensity, which is the highest in the region (Aslam &

Khan, 2009). Deregulation, which had its humble

beginnings in 2003, has led to privatization of Pakistans

telecom industry and can be singled out as the factor that

has driven growth in this critical sector of the countrys

economy (PTA, 2006). As of July 2009, the mobile

phone subscribers are 95.54 million in Pakistan and, in

fact, still Pakistan has the highest mobile phone

penetration rate in the South Asian region (PTCl, 2009).

Currently Pakistan telecommunication sector is facing

high and intense competition. And companies realized

that customer satisfaction is important to reduce the

biggest war of customer switching (Aslam & Khan,

2009). Heres come the role of management to make

better decisions for their survival and attain good market

share. An effective CRM system includes tools such as

a skilled customer care staff and leading edge automation

mailto:[email protected]:[email protected]

2

and workflow management software platforms are the

basic need of telecom companies. With this tool, it is

possible for a telecom companies to track sales enquiries,

and customer satisfaction surveys. In order to meet

various needs companies tend to adopt differentiated and

customer-oriented marketing strategies to gain

competitive advantage (Buttle, 1996;Gefen & Ridings,

2002).

To develop customer relationship management top

management commitment is essential. CRM needs

commitment of a customer centric vision from top

management, heavy investment and restructuring of

organization processes and strategies (Rodgers &

Howellet, 2000). CRM applications take full advantage

of technology innovations with their ability to collect and

analyze data on customer patterns, interpret customer

behavior, develop practice models, respond with timely

and effective customized communications and deliver

product and service value to individual customers

(Rodgers & Howellet, 2000).

In Pakistani telecommunication scenario the concept of

customer relationship management is emerging,

companies understand the need of CRM. Technological

advancement is also growing to focus more on the

individual customer need. Our organizations are being

transformed into the customer-centric view and

recognize the importance of customers, today customers

have many choices and to keep customers satisfied is

very difficult as well as customer needs and wants are

changing. Consequently organizations focuses on

developing and maintaining efficient customer

relationship management, realistically it is very

important for the organizations to implement customer

relationship. Efficient customer relationship

management can improve organizational performance in

terms of customer satisfaction, customer retention and

customer loyalty.

Research is needed on customer relationship

management in services sector because it is such a large

sector of the economy and there has been little previous

research in understanding the adoption and experiences

of companies implementing customer relationship

management in this sector. Furthermore, it is argued that

customer relationship management is probably more

advanced in services sector than in other sectors, so

organizations in other sectors can learn from the service

sectors experience.

Long term relations with customer are developed by the

Differentiation, consistency, effective communication to

customers. Difficulties exist before implementing CRM

like lack of definition, poor leadership and insufficient

help from CRM vendors (Ramsey, 2003) crm vendors

arewho introduces new tools to organizations.they only

highlight CRM aspects rather than its factors.difficulties

also exist after implementing the disconnection of CRM

vision and execution and the rising Standard for

excellence.

II. LITRATURE REVIEW

Managing and building strong relationships with

customers gives marketing determinants which is its

essence (Webster, 2002). Customer relationship

management provides useful information for managers

to make investment and marketing decisions, which can

improve companys overall performance by making

stronger customer relations and turn these relations into

customer loyalty (Parvatiyar & Sheth, 2001). The

meaning of CRM arises from both business and

technology perspective. CRM is the business philosophy,

describing a strategy which places the customer at the

soul of an organizations processes, activities and culture

(Rodgers & Howellet, 2000).

CRM is a business strategy to acquire grow and retain

customer which create a sustainable competitive

advantage (Porter, 2004). CRM classified as operational

and analytical, Operational CRM includes sales force

Automation, marketing, and customer support with a

opinion to making these functions more efficient and

effective relates Analytical CRM (Santoso, 2008).

A. Customer Relationship management implementation

Before deciding for adapting Customer relationship

management, Customer Relationship Management is

very difficult to implement, history demonstrates that it

took years. Since 1990s the concept of tailor software

packages are introduced which makes the

implementation of CRM easy and companies focus more

on their customers and collect and analyze customer data

according to their need but for the implementation of

CRM scope, vision and risk of success and failure should

always in the consideration. CRM is ongoing process by

the time or according to different changes it is updated

(Rodgers & Howlett, 2000).

Customer relationship management system is known as

technology-based business management tool for

developing and leveraging customer knowledge to

nurture, maintain, and strengthen profitable relationships

with customers (Frow & Payne 2005 ).

Customer relationship management Implementation

varies, according to the existing process, existing

hierarchies, existing power structures, availability of

resources, and Technical Architectures and

importunately. (Finnegan & Willcocks, 2007).

CRM is an incremental approach it is not implemented

overnight, first consideration is to develop profiles

individually then what kind of technology is needed and

how many systems should be developed like product

configuration, marketing automation and database

marketing. These systems are developed according to the

nature of operation or the kind of services. But the

important thing is integration of all the systems into the

one big system, Rodgers and Howlett carry out their

work on the Integration of systems which enables the

management for a unified view of all activities and it

makes easy to understand which activity is affecting

business (Rodgers & Howlett, 2000).

3

The first aspect for implementing CRM and building one-to-one relationship is to understand the

philosophies of relationship marketing. The

relationship philosophies involve a strong emphasis

on building long-term relationship with appropriate

customers and recognize the role of IT as a tool to

achieve the goals (Ryals & Payne, 2001).

The appropriate organizational structure customer is the important aspect. Since IT people possess a rich

knowledge about IT and technology issues but lack of

marketing knowledge, establishing cross-functional

team between IT and marketing people is needed

(Ryals & Payne, 2001). In order to implement CRM

successfully, all team members within a company

must have responsibility to design and implement the

system (which consists of hardware and software)

(Ryals & Payne, 2001).

Depending on the type of organization, Customer relationship management readiness assessment is all

about overview audit which helps managers to assess

the overall position in terms of readiness to progress

with customer relationship management

implementations and to identify how well-developed

their organization is relative to other companies(Frow

& Payne 2005 ). Customer relationship management,

change management involves strategic

organizational change and cultural change and

senior level understanding, sponsorship, leadership

and cross-functional integration are clearly critical in

a complex CRM implementation (Frow & Payne

2005 ).

Successful Implementation needs commitment from the top management, change management culture

strategic objective and concern in the area of human

resource. Trained and experienced consultants are

very important for the implementation provide

enough training for the end user is necessary for

successful CRM adoption (Santoso, 2008). The

training should cover all related materials like

demonstrating features and functionality of CRM,

change management and adaptation into new

business processes (Ryals & Payne, 2001).

Little attention is paid on the employees during CRM implementation but employees are the central part of

the delivery of CRM activities (Boulding, Staelin,

Ehert, & Jhonston, 2005). Organizations ignore these

issues results in the behavioral changes of the

employees which affect the CRM activities (Philip

,Liliana, & Seigyoung, 2008). Affective employee

commitment can be achieved by continuous

communication regarding expected change, create a

culture that fit in it, motivate the employees, develop

cross functional team to improve communication gap

and improve employees skills regarding

technological initiatives (Philip , Liliana, &

Seigyoung, 2008).

B. Customer relationship management Benefits

Reinartz, Krafft, & Hoyer suggest that customer

relationships have stemmed from customer relationship

management processes that positively influence

organizational performance which are termed as CRM

benefits. According to the authors it is expected from

organizations that achieving high levels of customer

satisfaction and retention will realizes higher

profitability, better cost position, and better ROI than do

organizations with lower satisfaction and retention

(Reinartz, Krafft, & Hoyer, 2004).

Customer acquisition is the first aim of customer

relationship, regain customers is as important as to

acquire new customers, Regain customers considered as

significant contributors to success in terms of customer

initiation (Thomas, Blattberg, & Fox, 2004).

Customer maintenance is the core objective of CRM,

which develop customer relations and expand these

relationships on long-term basis and increase profits.

Customer retention is important objective for customer

relationship management, organizations needs to identify

the previous customers which are inactive currently and

develop appropriate strategies to reactive these

customers (Thomas,Blattberg, and Fox, 2004).

Customer relationship management are key to create

customer loyalty as a result of creating loyalty, these

customers cost less to serve, refer others, and spends

more than a new customer. Customer relationship

management Becomes first issue in marketing strategy,

implementing CRM, company could generate better

profit, because CRM could increase customer retention,

customer satisfaction and customer loyalty (Willyanto,

2008).

Customer satisfaction has shown a greater influence on

customers purchases and low levels of customers

complaint (Szymanski & Henrad, 2001) CRM

technological changes having potentials that impact

processes, user, and organization performances (Markus,

2004). High levels of Customer Satisfaction and

Retention can lead to increase revenue by cross selling

and encourages customer to purchase more than thier

actual purchases (Hogan, Lehmann, Merino, Srivastava,

Thomas, & Verhoaf, 2002). CRM improves

communication between the management which is very

important to make solutions regarding management

conflicts. (Shah & Murtaza, 2005).

CRM successful implementation is very important for

the organization, because it makes organization to view

itself where it stands.

4

III. CONCEPTUAL MODEL

A. CRM Intangible Benefits

Different variables are influencing the implementation

of customer relationship management as illustrated in

Figure. Firstly organizations must understand the

determinants of Customer relationship management

implementation.

As it is shown that above determinants are used to

implement customer relationship management like

organizational skills and resources which shows whether

organizations have competencies to manage Customer

relationship management. Top management

commitment or concern towards the Customer

relationship management that is starts of its

implementation phase. Customer relationship

management Implementation varies, according to the

existing process, existing hierarchies, existing power

structures, availability of resources, and Technical

Architectures (Finnegan & Willcocks, 2007)

Organizational skills and resources are supoorted by the

appropriate organizational structure in which integration

of all organizations departments are important.because

overall objective of organization is to achive highest

level of customer satisfaction and high profits.when

organization all departments integrate organization able

to share resources take proper advantage of skills which

is done by proper communication.employees training is

important variable to manage the techonological

resources. By proper organization structure

Organizations can achieve improved decision making,

customers targeting capabilities, service efficiency and

effectiveness, and become more responsive by focusing

on individual needs which turns in to competitive

advantage (Parvatiyar & Sheth, 2001).

If Customer relationship management implemented

successfully it achieve benefits like customer acquisition

maintenance and satisfaction which automatically

influences profitibility.Customer relationship

management is on going process it needs investment

regarding technology which improves the organizations

communication which is very important and results in the

efficiency and effectiveness of oragnization. CRM

effectiveness will mediate customer relationship

management practices and businesses performances,

such as to increases customer relationship management

effectiveness attributed to CRM practices will increase

business performance (Chen & Ching, 2005).

Like Intangible benefits include customer acquisition,

Customer relationship management is measured in terms

of Customer acquisition. Acquiring customers will help

the organization to build relations on long term basis.

Previous researches also finds Customer acquisition is

the first aim of customer relationship, regain customers

is as important as to acquire new customers, Regain

customers considered as significant contributors to

success in terms of customer satisfaction (Thomas,

Blattberg, & Fox, 2004).

Customer retention and maintenance influences the

organizations acceptability of customer relationship

management. Organizations want to retain their

customers to achieve high profitability which is

ultimately turns into the customer satisfaction. When

organizations achieved customer satisfaction it will

create customer loyalty as a result of creating loyalty,

these customers cost less to serve, refer others, and

spends more than a new customer.

Companies could generate better profit, because

implementation of CRM could increase customer

retention, customer satisfaction and customer loyalty

(Willyanto, 2008). It is expected from organizations that

achieving high levels of customer satisfaction and

retention will realizes higher profitability than do

organizations with lower satisfaction and retention.

(Reinartz, Krafft, & Hoyer, 2004)

This conceptual framework concludes the important

determinants of CRM, which should be considered for its

successful implementation. If organizations implement

Management

commitment Investment

regarding Technology

Employee

Training Communication

Successful CRM

implementation Explore the success factors

of customer relationship

management.

Impact of CRM on performance level in terms of

CRM benefits.

Customer

Acquisition

Customer

Retention

Customer

Satisfaction

Customer

Loyalty

CRM

Implementati

5

CRM successfully, it will turn into several benefits which

automatically gain competitive advantage

IV. RESEARCH FRAMEWORK AND HYPOTHESES

To explore the relationships between organizational

characteristics and the process of adopting a CRM

strategy in the telecommunication sector of Pakistan.

Hypotheses were developed to test the proposed

framework figure1. The model shows implementation

level of CRM strategy, Once a organizations successfully

implement CRM strategy, organizations achieve long-

term in terms of tangible and intangible benefits.

Therefore, this study hypothesized the following

directional relationships:

H1: The Management commitment will positively

influence the successful customer relationship

management implementation.

The previous finding shows that Top management

recognizes that customers are the core of a business and

the success of a company relies on effectively managing

relationships with them (Remenyi, Williams, Money, &

Swartz, 1998). The research sets out the CRM

implementation factors like Employees training,

department integration, Technological investment and

communication. The resulting hypothesis are

H2: There is significant relationship between employees

training and CRM implementation activities.

H3: There is significant relationship between

technological investment and implementation of

customer relationship management.

H4: Communication regarding customer relationship

management implementation positively influences the

implementation of customer relationship management.

V. RESEARCH METHOD

To test these hypotheses, Questionnaire was designed

and distributed among the telecom managers including

Top, middle and low level managers. The variables in the

questionnaire included the management commitment,

Employees training, Technological investment,

communication and perception of CRM benefits,

A. Data collection and analysis

A sample of 150 managers or customer care staff of six

telecom companies in Pakistan was selected. To improve

the external validity of the research, the sample was

randomly selected. This is a common sampling method

to examine differences between each stratum (Malhotra,

1993). The questionnaire was pilot tested for content

validity and instrument reliability, and the revised

questionnaire was sent to CRM managers in telecom

sector. For the data analysis, descriptive statistics,

ANOVA, Regression and correlation were used to test

the statistical significance of the hypothesized

relationships.

B. Results

The target population, that population to which we

would like to draw inferences, Comprises the Customer

service departments and software personnel of

telecommunication companies in Pakistan. The unit of

analysis Customer service department includes the

customer service officers, Customer service

representatives, customer service managers and also IT

personnel to see the performance impact of Customer

relationship management. Data Reliability measures are

done by chronbacs alpha results in .867.

Correlation is a statistical technique that can show

whether and how strongly pairs of variables are related.

Table1: Correlation

Variables 1 2 3 4

Technology

Investment

1.00

Communication

about CRM

Implementation

.506** 1.00

Employee

Participation &

Training

.508** .601** 1.00

Top Management

Support

.419** .354** 407** 1.00

Communication, employees training and Top

management support shows the strong relationship,

which shows that successful customer relationship

management implementation need the strong

relationship of these variables.

C. Hypothesis testing:

For the testing of Analysis of variance is used to

determine the significant relationship between the

variables, for the implementation of successful

customer relationship management. ANOVA is

computed by taking overall company performance by

different cities and companies and taking five

independent variables.

Table2: ANOVA

Determinants Overall

Company

Performance by

Duration of

implementing

CRM

F Sig

Top Management

Support

Overall

Company

Performance

6.935 .000

Employee

Participation &

Training

Overall

Company

Performance

1.621 .187

Communication

about CRM

Implementation

Overall

Company

Performance

.943 .422

6

Technology

Investment

Overall

Company

Performance

2.613 .054

Different sizes of organizations are still motivated to

implement Customer relationship management to create

the stronger relationships with their customers more

efficiently and effectively.

H1: The Management commitment and support will

positively influence the successful customer relationship

management implementation.

As we have considered the result of ANOVA we have to

accept the hypothesis it shows the management role is

very crucial towards the CRM implementation.

Regression results also shows positive relation with

overall company performance and top management

support.

H2: There is significant relationship between employees

training and CRM implementation activities.

Employees training and participation shows significant

relationship by calculating according to different studies

previous studies shows Organizations recognizes that

employees contributes significant value CRM

implementation Organizations cant appropriately

develop and operate customer-centric customer

relationship management processes and systems without

having trained and motivated employees (Frow &

Payne, 2005)

H3: There is significant relationship between

technological investment and implementation of

customer relationship management.

Technological investment positively influences the

implementation of CRM. Organizations should focus the

technological aspects. Focus of information technology

projects are on improvement of technical performance,

but technological changes having potentials that impact

processes, user, and organization performances by

implementing CRM (Markus, 2004).

H5: Communication regarding customer relationship

management implementation will positively influences

the implementation of customer relationship

management.

Communication is very important to implement CRM

because effective communication improves the

efficiency of overall program of CRM implementation.

VI. DISCUSSION AND IMPLICATION:

All of the telecom companies realize the importance of

CRM implementation program. Organization realizes the

success factors of CRM implementation program like

management commitment, Employees training,

department integration, Technological investment and

communication. Having sustainable relationship with

customers can eventually resulted into the greater

customer loyalty and retention and, also, profitability

(Ngai, 2005). Moreover, the rapid advancements in

communications technology have significantly

influences the organizations to deal with their customers,

to enhance relationships (Bauer et al., 2002).

Organizations must understand that by implementing

Successful implementation of CRM programs leads

towards the long term benefits. Previous researches also

support the tangible and intangible benefits of CRM.

Managers must understand that implementation phase

should be implemented well to attain CRM benefits.

CRM focuses on keeping existing customers rather than

acquiring new ones. Ultimately this has resulted in the

number of benefits such as customer retention, loyalty,

and satisfaction, which lead to the appearance of

economic measures like profitability and increased

market share (Osarenkhoe and Bennani 2007). Thats

why, organizations required to improve their financial

performance (FP) by increasing their customer retention

rate (Parvatiyar and Sheth, 2000; Bodenberg, 2001).

This resulted to the appearance of CRM as a management

concept that has the potential to positively impact the

cost-revenue ratio by aligning the company with its

customers and focusing on its resources (Geib et al

2006).Customer retention means existing customer loss

rate, customer satisfaction depends upon innovative

products and services, customization, convenience, etc,

acquisition and profitability as the major assessment

tools in evaluating organizations CRM readiness for its

implementation (Jutla et al. 2001).

(Fjermestad and Romano 2003:Scullin et al.2002) states

the important benefits of successful CRM

implementations, increased customer loyalty, one to one

marketing , sorting the type and timing of purchases,

producing targeted campaigns and tracking their

effectiveness by having detailed customer information

(Fjermestad and Romano 2003:Scullin et al.2002).

(Ab Hamid and Kassim 2004) have demonstrated that

CRM implementation improves understanding of

consumer behavior and delivering personalized services

as well as consumer loyalty. Successful CRM

implementation has resulted in increased

competitiveness for many organizations as witness by

increased market share and lower operational costs.

(Reichheld, 1996a, b; Jackson, 1994; Levine, 1993).The

success factors of CRM implementation are recognized

and are very helpful in implementing CRM.CRM

implementation resulted in Benefits like customer

acquisition, retention, loyalty and satisfaction.

Ultimately these benefits also affect the performance and

it will become competitive edge of companies.

VII. CONCLUSION

This paper contributes to the existing literature on

customer relationship management by providing insights

7

into how to implement CRM. Even though numerous

studies have investigated several drivers of CRM

performance, little knowledge has existed as to whether

CRM implementations actually meet their objectives of

initiating, maintaining, and retaining customer

relationships. This research finds the determinants of

CRM implementation Management commitment,

Employees participation and training, technological

investment and Communication regarding CRM

implementation. This research paper contributes in terms

of finding management determinants of implementing

CRM activities.

The paper examines the Success factors of the CRM

implementation processes, as well the relationship

among these outcomes and business performance in the

telecommunication sector of Pakistan. We conducted a

survey on companies operating in the Pakistan, which

revealed that the successful CRM implementation is

important generates superior business performance.

Successful CRM implementation results in different

benefits like customer satisfaction, retention and

Loyalty.

The paper give insight about the implementation

determinants supported by the existing literature of

different authors and proved by the use of different

statistical techniques, there are some limitations founded

especially in responses from respondents and it is very

difficult to specify the every determinant of successful

CRM implementation.

Future research might investigate other variables related

to the organizational performance. And it really needs

more investigation on the performance dimension of

customer relationship management in terms of the

tangible benefits like ROI, market share, and customer

growth.

VIII. SUGGESTIONS\ RECOMMENDATIONS

By concluding the Successful Customer relationship

management implementation in Telecom sector,

following suggestions and recommendations are

necessary for the telecom sector of Pakistan.

Management commitment is most important in the success of Customer relationship management.

Organizational current structure should be viewed before implementing Customer relationship

management.

Customer relationship management requires continuous training programs.

CRM application software should be compatible according to the nature of business.

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http://www.google.com/http://www.google.com/

9

2013-199-002

Modelling and Simulation of Height Processor of a

Generic 3D Radar

Dr Ali Javed Hashmi

Department of Avionics

Engineering NUST,

Islamabad, Pakistan

[email protected]

Dr Shahid Baqar


Engineering NUST,

Islamabad, Pakistan

Sher Hassan Arbab


Engineering NUST,

Islamabad, Pakistan

[email protected]

Hamza Malik


Engineering NUST,

Islamabad, Pakistan

[email protected]

Abstract Height calculation of a target is of great significance

in modern day Radars. In this paper, an algorithm for height

calculation of a target, employed in the Digital Height Processor of

a generic 3D Radar, is modeled and simulated. The hypothetical

Radar under consideration has a cosecant squared beam pattern

whose target returns are phase coded. These phase coded target

returns after matched filtering, pulse compression and analog to

digital conversion are routed to the Digital Height Processor for

height calculations. The algorithm employed in the Height

Processor incorporates various factors that affect the height of a

target including Earth's curvature, atmospheric refractions,

multipath effects, terrain adjustments and several other factors.

This work will help in better understanding of Digital Height

Processor of a generic 3D Radar. Furthermore, this paper would

find its applications not only in military field but also in civilian

domain, especially academia, where it can provide basis for future

research related to digital height processing in radars.

KeywordsHeight calculation, 3D Radar and Digital Height

Processor

I. INTRODUCTION

3D radars have become important because of their ability to determine the height of a target, along with its range and azimuth. Because of its better angular resolution, 3D radar provides a higher-gain antenna and, arguably, a greater resistance to jamming and other forms of Electronic Counter Measures (ECM).

It is important to mention that height in radar is always a derived rather than a measured quantity because radar can only measure range and angle of arrival of target returns. Surface-based radars derive the height of a target from the range (time) of the echo return and elevation coordinate measurements. Radar on a ship, aircraft, or space satellite may be required to convert tri-coordinate measurements relative to the antenna to an inertial reference system as part of the height calculation. The accurate calculation of height from radar measurements must provide for such effects as the location and orientation of the radar antenna in the desired reference coordinate system, the curvature of the earth, the refractive properties of the atmosphere, and the reflective nature of the earth's surface. Furthermore, if the target height is to be referenced to the local

terrain, then the height of that possibly irregular terrain below the target must also be taken into account.

There are many types of radars that provide 3D information by simultaneously measuring the three basic position coordinates of a target (i.e. range, azimuth, and elevation). However, conventional 3D surveillance radar will be discussed here, whose antenna mechanically rotates in azimuth (to measure range and azimuth) and which obtains the elevation-angle measurement by scanning the air space with a stack of six elevation beams that are at fixed angles. This pattern of beams is known as the Cosecant Squared Beam Pattern. In stacked-beam radars with a Cosecant Squared Beam Pattern, the target is illuminated by any one of the fixed elevation beams whose returns are then processed by the radar receiver to find the different characteristics of the target including the height.

To illustrate the processing of height data in radars, first of all the processing of the target returns in the receiver will be discussed briefly followed by the algorithm that is employed in the Digital Height Processor. And lastly, the simulation results will be explicated.

II. RADAR RECEIVER

A. Antenna Front End Processing

The return signals from a target are received by the feed horns and sent to six RF receivers through six channels, each having different signal strengths. In the RF receivers, super-heterodyne conversion of the RF returns is done by mixing the target return signals with a stalo frequency to obtain 30 MHz IF phase-coded signals, as shown in Fig 1.

10

Fig. 1 RF Receiver

B. Height Receiver

The height receiver determines which beam pair contains the strongest target return and interpolates between adjacent beam pairs to find the angular distance of the target from the beam centers.

As previously stated, six channels of the 30 MHz IF return signal from the main radar system are input to six height IF receivers. In each height IF receiver, the return signals are amplified, match-filtered and sampled. The sampled video pulses are held until a target detection occurs. The sampled outputs from all of the six height IF receiver channels are then applied to beam pair selector and beam subtractor. This is illustrated in Fig 2.

Fig. 2 Height Receiver

The beam pair selector sums pairs of adjacent channels

producing five beam pair signals. The highest beam pair with significant target video amplitude is selected and applied to the Digital Height Processor. The base angle B is determined by the crossover point of the selected beam pair containing the target returns. In addition, the selected beam pair also enables the corresponding beam target amplitude difference to be applied to the height signal processing circuits from the beam subtractor. The interpolation angle i (amplitude difference) then determines the amount by which the target lies above or below the base angle. This is illustrated in Fig. 3.

Fig. 3 Base Angle and Interpolation Angle

III. DIGITAL HEIGHT PROCESSOR

The Digital Height Processor performs the computation required to find the height of the target. It basically consists of six adders, which add up various terms and multipliers which multiply the various factors taking part in the height calculations. The equation that is employed in the height computer is:

H= [ T TF + R Ke + sin B +( Ki cos B) i]R+S.E (1)

Where,

H = Computed target height

T = Antenna dynamic tilt

TF = Antenna fixed tilt

Ke = Earths curvature correction factor

sinB = Base angle

Ki cosB = Interpolation constant

i = Interpolation angle

R = Slant range

S.E = Site elevation

The detail of these parameters is as follows:

A. Antenna Dynamic Tilt (T)

The dynamic tilt correction is due to the variation in the angle of the antenna due to natural causes such as winds or storms. It is a variable input and depends upon the extent to which the radar is tilted from its mean position.

B. Antenna Fixed Tilt (TF )

The static or fixed antenna tilt correction is adjusted during the leveling of the antenna at the time of installation. It is a constant input and is set manually depending upon the terrain on which the radar is located.

C. Earths Curvature (R Ke)

It is the correction composed of true Earths curvature factored with the measured target range. It is a function of

LNA

Stalo

Frequency

IF Amp

30 MHz

IF

Height

Receiver

6 Channels 6 Channels

RF Receiver (Channel 1)

Beam Pair

Selector

Height

Processor

Beam

Subtractor

30 MHz IF from

RF

Receiver

Sample Video

IF Receiver (Channel 1)

Base Angle Video

(B)

(1 Beam Pair

Channel)

Interpolation Angle Video

(i)

(5 Beam Pair

Channel)

IF

Amp

Matched

Filter

Sample

and

Hold

11

parameters such as geographic location on the Earth, weather, time of day and season of the year.

D. Base Height (R sinB )

The height above the horizon is computed from the target range and the sine function of the known base angle of adjacent beam pair having the greatest target signal strength. The base angle of each beam pair is a known quantity because the crossover point of each beam pair is at fixed elevation angles. The sine and cosine function of each base angle is a constant input and is automatically selected by the identity of the adjacent beam pair selected.

E. Interpolation Height [( Ki cos B) i R]

The target distance above or below the base angle selected

is calculated by the product of the interpolation constant (Ki cos

B ), a constant input, and the interpolation angle (i), a variable

input, factored with the range of the target.

F. Slant Range (R)

The slant range to a target is a variable input and is derived

from a range counter within the Digital Height Processor.

G. Site Elevation (S.E)

The site elevation is a constant input which converts height

measurements from height above radar to altitude above the sea

level. This constant is the actual site elevation above sea level.

The terms of the Height Equation are illustrated in Fig 4.

Fig. 4 Terms of Height Equation

IV. HEIGHT ALGORITHM

The flow chart of the algorithm that is employed in the Digital Height Processor is shown in Fig 5.

First of all the antenna tilt signal voltage from the receiver is sent to the analog to digital converter before the start of each receive period. This places the tilt word on the line to adder 1. The fixed tilt word is summed in adder 1 with the dynamic tilt. The output of adder 1 is summed in adder 2 with a scalar constant when the top most beam pair contains the target else the output of adder 2 is the same as that of adder 1. The output of adder 2 is then on line to adder 3 to be summed with the Earths curvature constant.

The Earths Curvature constant is applied to an adder accumulator, where it is merely added to itself over and over again by the adder accumulator until a target is detected. The result is then sent to adder 3 where it is add to the output of adder 2.

The output of adder 3 is on line to adder 4 where it is summed with the sine of the base angle, which is a constant input selected by the beam pair that contains the target. Till now the output of adder 4 is

T TF + R Ke + sin B (2)

The product of interpolation angle constant and the interpolation angle word is added to the output of adder 4 in adder 5.

T TF + R Ke + sin B +( Ki cos B) i (3)

The output of adder 5 is then multiplied with the range of the

target, which is then sent to adder 6 to be summed with the site elevation of the radar.

H= [ T TF + R Ke + sin B +( Ki cos B) i]R+S.E (4)

The final output of the Digital Height Processor is the actual target height.

12

Fig. 5 Height Algorithm Flow Chart

V. SIMULATIONS

(Fixed Input)

Target

Height

(Fixed Input)

(Fixed Input)

(Fixed Input)

(Fixed Input)

(Variable Input)

(Variable Input)

(Variable Input)

Earths Curvature

Ke Accumulator

If

Target

Pres

ent

Add Add Add Add Add

Product

Product

Range

R

Fixed Tilt

TF

Dynamic Tilt

T

Interpolation

Constant

KicosB

Interpolation Angle

i

Base Angle

B

Base Constant

SinB

Site Elevation

SE

13

I simulated and coded the Height Equation and

the algorithm flowchart. The results were observed

by varying certain factors of the height equation

while keeping the other factors constant.

A. Variable Inputs

The factors that were taken as variables are:

Antenna Dynamic Tilt

Target Range

B. Constant Inputs

That factors that were assumed as constants are:

Antenna Fixed Tilt

Earths Curvature

Interpolation Angle

Base Angle

Slant Range

C. Variation of Dynamic Tilt

The dynamic tilt was assumed to be an 8 bit word with positive Dynamic Tilt words from 0 to 127 and negative words from 127 to 255. The negative tilt words are in the form of 2s complement.

When the Dynamic Tilt word T was varied and the other factors were kept constant, the plot shown in Fig. 6 was obtained.

Fig. 6 Dynamic Tilt (T) vs. Height

For positive Dynamic Tilt words, the antenna is

tilted downwards due to wind or some other external effects. Thus the target appears to be located at a shorter height. In order to compensate for this downward antenna tilt, the 8 bit Dynamic Tilt word becomes more positive from 0 to 127. This causes the target height to be increased, thus resulting in the actual or corrected height of the target.

From 128 to 255, the Dynamic Tilt is negative.

This indicates that the antenna is tilted upwards

because of wind or some other external effects

which causes the target to appear at a greater height.

Now in order to compensate for the upward antenna

tilt, the Dynamic Tilt word becomes more negative

as the tilt increases thus decreasing the target height

which gives us the corrected or actual height of the

target.

D. Variation of Range

Each beam pair of a stacked beam radar is at a

fixed elevation angle, which limits the maximum

height calculation of a target in a beam pair. So it

implies that beam pairs with greater elevation angles

can detect targets at a greater height.

Within a particular beam pair, the height of a

target will increase as the distance from the radar

increases and vice versa. When the height limit for a

particular beam pair is exceeded, it means that a

target has now shifted from the current beam pair to

the next beam pair.

The plot in Fig. 7 was obtained for beam pair 1-

2 when the range was varied and the other factors of

the height equation were kept constant.

Fig. 7 Range vs. Height (Beam Pair 1-2)

This plot shows that beam pair 1-2 can calculate

a maximum target height of up to 18,000 feet and within its height limits, the target height increases as the distance from the radar increases.

For beam pair 2-3, the plot shown in Fig. 8 was obtained. It shows that this beam pair has height limits 18,000 feet to 45,000 feet and as long as a target remains within its height limits, its height increases as the distance from the radar increases. When the height limits of this beam pair are exceeded, it means that a target has now shifted from the current beam pair to the next beam pair i.e. beam pair 3-4 and vice versa.

14

Fig. 8 Range vs. Height (Beam Pair 2-3)

.

VI. CONCLUSION

In this research, a mathematical model was

presented for the Digital Height Processor of a

stacked beam radar that provides compensation for

radar antenna tilts from its mean position, the

Earths curvature and the geographical location of

the radar. This model gives us a height accuracy of

about 2000 ft at a target range of 175 nautical

miles and a height of 30,000 ft. Moreover, the

algorithm that is employed in the Digital Height

Processor was simulated and the results were

observed for the different factors that affect the

height of a target in actual radars.

For the radars that a have stacked beam radiation

pattern, the simulated algorithm gives us a good

performance and it can be readily implemented in

operational radars for more reliable and precise

target height calculations.

REFERENCES

[1] Jeffrey S. Fu, Guoan Bi and Liong Hai Tan, Phase coded pulse compression implementation for radar performance analysis

[2] John W. Taylor and Herman J. Blinchikoff, Quadriphase code code A radar pulse compression signal with unique characteristics

[3] Westinghouse Defense and Electronic Systems Center, Defense Acquisition Radar

[4] David J. Murrow, Height finding and 3D Radars.

[5] Labtech Microwave, Log video amplifiers

[6] Jalal Al-Roomy and Akram Abu-Raida, Wave generation, Islamic University of Gaza

[7] Agilent Technologoes, Techniques for radar and EW signal simulation for receiver performance analysis

[8] T.A Alberts, P.B Chilson, B.L Cheong and R.D Palmer, Evaluation of binary phase coded pulse compression schemes using time series weather radar simulator

[9] R.M ODonnell, Detection and false alarm performance of a phase coded radar with post MTI limiting

[10] Merrill I. Skolnik, Introduction to Radar Systems

15

2013-202-003

Design and Analysis of a Flapping Wing

Micro Air Vehicle (FMAV) Capable of

Producing Flap and Pitch Simultaneously

Hasnain Raza Sarwar

Department of Mechanical & Aerospace

Engineering

Air University

E-9, Islamabad, Pakistan

[email protected]

Syed Saad Ali


Engineering

Air University


[email protected]

Sohail Iqbal


Engineering

Air University


[email protected]

Waseem Abbas


Engineering

Air University


[email protected]

Abstract: Micro Air Vehicle (MAV) is an active area of

research in the world, covering some major fields of

study that is aerodynamics, control, mechanics and

navigation. Micro Air Vehicle (MAV) can be utilized

by both military and civil sectors that include aerial

surveillance, reconnaissance and photography, traffic

control, spying and a lot more. An attempt has been

made to design a mechanism that can produce flap and

pitch simultaneously with minimum number of

actuators. The research paper deals with the kinematic

and dynamic analysis of each constituent of Micro Air

Vehicle (MAV) by using commercial software

packages like Creo-Pro and ANSYS. A Computational

Fluid Dynamics (CFD) Analysis is done to study the

behavior of air over the surface of wing. The Velocity

and pressure contours obtained from CFD analysis are

discussed in detail in this research paper.

KEYWORDS: MAV, Flapping Wing, Five Bar

Mechanism, CFD, Dynamic and kinematic Analysis.

I. INTRODUCTION The modeling and analysis of flapping wing Micro

Air Vehicle (FMAV) is presented in this paper,

which includes the kinematics and dynamic analysis

of the mechanism along with the computational

Fluid Dynamics analysis of a specific wing profile.

Drones technology is not sufficient and efficient

technology for surveillance because of its size and

maneuverability issues that they cannot enter in

narrow places and are easily recognizable during

their course of action. On the other hand more

efficient and covert surveillance can be done by

means of unmanned aerial vehicles on smaller

scales. Micro Air Vehicles are unrecognizable and

can access tight and narrow spaces and openings.

Micro air vehicles are beneficial for both military

and civil uses.

A. Historical Overview In 1863 Air Balloons were used as Unmanned Air

Vehicles for bombing set by timers [1]. These

balloons were used by Charles Perley in a civil war.

In 1883 a kite was used as an Unmanned Aerial

Vehicle for the aerial surveillance in Spanish-

American war. The first real Unmanned Aerial

Vehicle was a U.S Curtiss N-9 trainer Air craft

which could carry 300pounds bombs for 50 miles

but this plane was never used in the war [2].The wing

flapping micro air vehicles were first launched by

FESTO in 2011, an ultra-light but powerful model

with extra aerodynamic qualities having wing span

of 2m and weight of 0.450kg [3].

B. Relevant Mechanisms Floris van Breugel&Hod Lipson of Cornell

University designed a mechanical ornithopter

capable of flapping through a cable actuator control.

The design included three servos attached to each

wing through a symmetrical cable system such that

when the servo turned in one direction one cable

would pull on the wing and the other would give

mailto:[email protected]:[email protected]:[email protected]:[email protected]

16

slack at the bottom thus generating flap [4].

Fig. I

V. Malolan, M. Dineshkumar and Dr. V. Baskar of

Madras Institute of Technology designed a

mechanism that runs via single gear. The designed

mechanism produces equal lift on both the wings at

all times. This does not cause any oscillatory motion

along the lateral direction. The motion providing

part is a single crank disk [5]. The mechanism is

shown in the following figure II:

Fig. II

II. SYSTEM DESCRIPTION The FMAV is modeled and analyzed in Creo-pro

whereas Computational Fluid Dynamics (CFD)

analysis is done using fluent (A Software package of

ANSYS):

a. Creo-pro (Kinematic analysis)

b. ANSYS (Static analysis)

c. Fluent (CFD analysis)

The designed mechanism is based on Five Bar

Mechanism consisting of a main driving gear,

cranks, coupler and wings .Two cranks of FMAVare

operated with a single motor which drives the two

couplers each attached with wings of each side.

Couplers are attached on the body of crank via pin

joint and from the other end each coupler is attached

with each wing. Wings on their turn are split into

two parts both joined through pin joint with one

another. Wing is split to provide efficient lift and

less drag as compare to a solid straight wing. The

designed Micro Air Vehicles assembly is shown in

the figure III.

Fig. III

a. Crank: Crank is a circular wheel having 60 teeth whose function is to provide 360 degrees of

revolution in order to offer a two dimensional up and

down motion to the coupler. The crank is teethed

because it has to transfer motion from motor gear to

the coupler. Figure IV shows solid model of crank.

b. Coupler: Coupler is used to transmit the rotary motion of crank into the up and down 2-

Dimensional (oscillating) motion in the wings. The

coupler is attached on the body of crank, as the crank

complete one revolution the coupler moves in such

a motion that wings of the Micro Air Vehicles

complete their up and down motion once.

Fig. IV

Wing

joint

17

c. Wings: Wings are the most significant parts of Micro Air Vehicles. Theshape of the Aerofoil of

the wings determines the coefficient of lift and

drags which consequently manages the flight of

the FMAV. As air reaches the leading edge of the

wings of FMAV, the force acted by air on the

wing is divided into two components. One of the

components provides lift and the other component

offers drag. Katzmayr conducted wind tunnel tests

to verify that the sinusoidally oscillating effective

angle of attack of the airfoil in the free-stream

produced a thrust force [6].Figure V shows the

designed wing.

Fig. V

d. Modeling of 2-D Airfoil The two dimensional airfoil of NACA 0012 is

modeled in ANSYS WORKBENCH. The co-

ordinates of the respective airfoils are

downloaded from the given databases and

surfaces are formed from the coordinates in the

work bench as shown in the Fig (VI) [7].

Fig. VI

After modeling the surface of airfoil the next step is

to generate the appropriate mesh of two-dimensional

airfoil to study the details at several points of the

airfoil. The meshing is done by influencing on the

effect on the air as it strikes the leading edge of

airfoil. This is done by generating a mesh domain

around the surface of the airfoil.As the leading edge

of the airfoil is a smooth curve so the start of the

mesh domain is from a circular pattern as shown in

the figure (VII).

Fig. VII

This type of meshing domain is known as C-mesh

which contains the air foil in its centre. Meshing is

done by refining the mesh while moving towards the

centre of meshing domain where the airfoil lies and

coarse mesh on the both far ends of airfoil because

more precise and accurate results are needed around

the surface of airfoil. The meshed airfoil along with

its surroundings is shown in the fig (VIII).

Fig. VIII

More refined the mesh is the more accurate and

precise results are obtained. The surroundings of the

airfoil is meshed rather the surface of the airfoil

because pressure distributions and velocity contours

are obtained in the surrounding air as it passes airfoil

at some speed.

III. ANALYSIS A. Kinematic Analysis

Simulation was performed for plane motion with6

degree angle of flight assumed as a preliminary

criterion. The position, velocity and acceleration

plots of the mechanism are given in the following

figures. Position plots illustrate the amplitude of

flap, it is fixed in the case of the designed

mechanism, and however it can be changed by

adjusting the link lengths of mechanism. For the

designed mechanism amplitude is asymmetric to

generate more lift. Asymmetric behavior is because

the wing swaps more upward angle than the

downward angle [5] [8].

Fig. IX: Position of Wing-X axis

18

Fig. X: Position of Wing-Y axis

Fig. XI: Angular Position of Wing Joint

Fig. XII: Overall Angular Velocity of Wing

Joint

Fig. XIII: Angular Velocity of Wing Joint-X axis

Fig. XIV: Angular Velocity of Wing Joint-Y axis

Fig. XV: Overall Angular Acceleration of Wing Joint

B. Dynamic Analysis Dynamic analysis is carried out to find the forces

and torque on different links of the mechanism.

These forces will help in designing a structurally

efficient mechanism, it will provide with the power

requirements of the mechanism so that the

appropriate actuators and battery can be selected.

Fig. XVI: Overall Radial Force on the Wing Joint

Fig. XVII: Radial Force on the Wing Joint-X axis

Documents

Conference Proceedings Vol-I