565_1

Copyright 2012 by ASME

ABSTRACT

This paper looks at the recent trends in mecha-

tronic design configurations and examines how those ap-

proaches can be applied to the design of Micro Unmanned

Aerial Vehicles. The current challenges in this area in-

clude the design of micro UAV systems that are capable

of precise delivery, minimum volume and lower cost .

This paper examines the use innovative techniques such

as of axiomatic design, TRIZ (theory of inventive prob-

lem solving) and Hardware in the loop to arrive at a sys-

tematic design process. Virtual product design procedures

involving simulation of complex systems allows designers

to develop system without finalizing the hardware. The

simulation procedure can be as what if scenario when the hardware doesnt exist. Virtual simulations enable everyone to work on development before the first proto-

type is completed. Engineers can validate the entire oper-

ating cycle for the machine by driving the simulation with

control system logic and timing. . Given the small volume

available when in launch configuration, the primary driv-

ing parameters were maximizing available wing area and

relative wing effectiveness, while minimizing the required

storage volume. The impact of G-forces on the structural

viability, mechanical complexity and overall system sur-

vivability are important in determining the relative merit

of the design concepts. This paper also addresses some of

the practical applications, advantages and difficulties as-

sociated with the engineering applications of virtual reali-

ty.

.

INTRODUCTION

The research in simulation and modeling along with

virtual prototyping had a major influence on the design and

fabrication of Micro Unmanned Aerial Systems. The

commercialization of these technologies with decreased cost

and size has received attention in both civil and military

applications. Micro UAVs are also used in a small but growing

number of civil applications, such as firefighting or

nonmilitary security work, such as surveillance of pipelines.

Unmanned aerial systems under the category of guided projec-

tiles are also of importance when it is necessary to hit a single

target in a rough terrain. Traditional, unguided projectiles of-

ten require multiple rounds be used to strike a single target.

The guided projectiles, although they are remotely guided at

times are not considered UAVs. UAV is defined as a powered,

aerial vehicle that does not carry a human operator, uses aero-

dynamic forces to provide vehicle lift. It can fly autonomously

or be piloted remotely and can be expendable or recoverable

[1]. UAVs come in two varieties:

Units controlled from a remote location

Units autonomously based on pre-programmed flight plans using more complex dynamic automation

systems.

DESIGN TRENDS IN MICRO UAVs

Identify various concepts and evaluation of each of those concepts using axiomatic design approach.

Apply the concept of TRIZ (theory of Inventive Problem Solving) to arrive at unique solutions

Investigate initial performance estimation and opti-mization of aerodynamic design.

Study and definition of avionics and GCS capability requirements for mission profile of UAV.

Micro UAVs Using Mechatronics Techniques

Devdas Shetty

College of Engineering, Technology &

Architecture, University of Hartford,

CT06117, USA

[email protected]

Louis Manzione

College of Engineering, Technology &

Architecture, University of Hartford, CT 06117,

[email protected]

Proceedings of the ASME 2012 International Mechanical Engineering Congress & Exposition IMECE2012

November 9-15, 2012, Houston, Texas, USA

IMECE2012-87820

1

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System design and creation of the software and initial mechanical design and verification of

baseline avionics

Fabrication of components that are suitable for high G forces (based on the zones where the de-

vice is lunched)

The current challenges include the need for micro UAV

systems that are capable of:

highly precise delivery, cost Complexity

Systems Design Process (SDP) and a quantitative ap-

proach to decision making and can be used as a tool for

improving existing systems or for design of new systems

Micro UAVs, the limited pay load constraint influences

the use of high performance avionics systems with com-

plete inertial and air data sensors Multidisciplinary ap-

proach integrating expertise across areas: fluid dynamics,

aerodynamics, guidance, control theory, flight dynamics,

microelectronics, mechanical design

Design Methodologies:

Axiomatic Design TRIZ Hardware in the loop simulation

There had been different efforts in using design

methodologies for decision making on the construction of

UAVs. The challenge comes from the need for systems

capable of highly precise delivery, cost and complexity.

Axiomatic Design approach has been used in an integrat-

ed design atmosphere to investigate flow and structure. It

is based on the assumption that there is a fundamental set

of principles that represents a good design practice.

AXIOMATIC METHODOLOGY APPLIED

TO THE DESIGN PROCESS

Many times we identify a distinguishing piece of art

or music, but still we find it difficult to explain why a

particular combination of elements in a work causes it to

be excellent. In other words, these results lack an absolute

frame of reference, which often leads to differing opin-

ions in evaluating the merits in this field. A lot depends

on intuition and experience when we compose music or

design a product or a process. It is difficult to reduce these

facts and observations into a consistent set of statements

and descriptions. Nam Suh (1990) proposed the use of

axioms to represent design. It is based on the assumption

that there is a fundamental set of principles that represents

a good design practice. There are many similarities in the

design methods of diverse fields such as industrial design,

architecture, mechanical design, and software engineering and

also in the development of management policies. In other

words, it can be said that theyre a set of common factors in a good design. These common factors can be applied to other

design situations like natural laws in natural science problems.

Nam Such developed a set of axioms and corollaries to

represent design. These were reduced to a set of two funda-

mental axioms, that if followed would result in a good design.

Axioms are fundamental truths that are always expected to

be true

Corollaries are propositions that follow from the axioms.

Functional Requirements (FRs) are characterization of the

perceived needs for a product or a process. In addition the

minimum set of independent requirements that characterize

the design objectives for a specific need.

Design Parameters(DPs) are the variables that character-

ize the physical entity created by the design process to fulfill

the FRs. The Design begins with the problem definition from

an array of facts into a coherent statement of the questions.

The objective of design is stated in the functional domain,

while the physical solution is generated in the physical do-

main. Design involves continuous interaction between the

objectives of what we want to achieve and how we want to do

it with a physical solution. The design process links these two

domains, which are independent of each other. The next step

in the design process is to determine the designs objectives by defining it in terms of specific functional requirements

(FRs). To satisfy these functional requirements, a physical embodiment is developed in terms of design parameters

(DPs). Design process relates FRs of the functional domain to the DPs of the physical domain. This mapping feature be-

tween FRs and DPs is illustrated below. The design axioms provide principles that aid the creative process of design by

enabling good designs to be identified from an infinite number

of designs.

Two main axioms are:

Axiom 1 The Independence Axiom

Maintain the independence of functional

requirements.

Axiom 2 The Information Axiom

Minimize the information content of the design

The axioms provide an insight into questions like

how one makes design decisions, why a particular

design is better than others. Axiom 1 is related to the

process of translation from the functional to the

physical domain. Axiom 2 states that the complexity

of the design, once axiom 1 is satisfied, should be

reduced. The questions like whether it is a rational

decision, how many design parameters are needed to

2



satisfy the functional requirements are answered.

The same principles are used in all design

situations irrespective of whether it is product

related or process related or organization related.

In mathematical terms, the independence axiom

can be represented as follows:

[FR] = [DM] [DP] where,

[FR] = vector of the functional space to

the vector of the physical space as:

[DP] = vector of design parameters

[DM] = relationship matrix between

functional and physical domain.

An element of [DM], Xij represents the

relationship between each FRi and DPj. If the

FRi is affected by DPj, then Xij has a finite value.

If FRi is not affected by DPj, then Xij is zero. We

can write a design equation and design matrix for

each possible solution. The implementation of

the independence design axiom results in the

case where every functional requirement is

associated with a single design parameter. This is

called the uncoupled design and is represented

by the diagonal matrix of the type. It can be

observed from the first axiom that for a design to

be uncoupled, it requires that the number of FRs

and DPs to be the same. When the matrix is

triangular (e.g., Anm = 0 when n m and m > n), the design is a decoupled design. Both,

uncoupled and decoupled designs satisfy the

independence axiom. All other matrices, which

do not satisfy Axiom 1, are called coupled

designs.

TRIZ METHODOLOGY APPLIED TO THE DE-

SIGN PROCESS

TRIZ is the acronym for a Russian term that translates to

Theory of Inventive Problem-Solving (TIPS) It was developed by Genrich Altshuller in 1946. He began with

the hypothesis that there are universal principles of inven-

tion serving as the basis for creative innovation across all

scientific fields. If these principles are codified and

taught, it would be possible to make innovation more pre-

dictable. To test this theory, he reviewed about 200,000 pa-

tents submitted at that time in the Soviet Union (Russia) The

analysis showed that most patents suggested means for elimi-

nating system conflicts in a system. For a problem to be con-

sidered inventive, it had to pose at least one contradiction.

Such contradictions arise when a certain parameter cannot be

improved without causing another parameter to deteriorate. A

contradiction between speed and sturdiness is one example. If

we want to design an automobile to be sturdy, it means more

weight. More weight generally results in less speed. How do

we design the same vehicle to run faster? Furthermore, TRIZ

researchers found about 39 parameters, each of which could

be in contradiction with one another. The initial step in using

TRIZ is to find out which design parameters are in contradic-

tion with one another.

TRIZ methodology systematically investigates the problem as

an innovative solution and applies a series of step by step

guidelines to generate solution alternatives, improving the

product parameters while maximizing product changes and

costs. This procedure was developed with a very limited

knowledge of other methodologies, but is based on a large

empirical knowledge base of patents. This concept has been

adopted by many organizations as an effective concept-

generating tool. Apart from solving technological issues, it has

additional capability of affecting key functions in leadership

and management.

TRIZ - Resolution of Technical Contradictions

The basic concept of TRIZ is the resolution of a contradiction.

A contradiction arises from mutually exclusive demands that

may be placed on the same system. Improvement of one of the

system parameters will then lead to deterioration of others. To

resolve this, it is important to find the physical contradictions

that are at the hidden root of the technical problem. The most

effective solutions are achieved when a designer solves tech-

nical problem that contains a contradiction, which generally

occurs when the designer tries to improve on specific parame-

ters. The physical contradictions and principles are combined

in a matrix, the rows and columns of which contain 39 gener-

alized parameters, corresponding to the most common pa-

rameters the engineers try to improve. The complete matrix is

provided in a TRIZ table that has been built after reviewing

about 2 million patents.

DP

..

DP

DP

DP

X 0 0 0

.. .. .. ..

0 .. 0 0 0

0 .. 0 X 0

0 .. 0 0 X

...

N

3

2

1

3

2

1

NFR

FR

FR

FR

3



HARDWARE IN THE LOOP SIMULATION

METHODOLOGY APPLIED TO THE DESIGN

PROCESS

During the design phase of small unmanned aerial

vehicles, Hardware-in-the-Loop (HIL) simulation and

experimental validation are required due to the high cost

of flight tests. Despite the need for real tests, simulation-

based testing also plays a very important role.

In the prototyping step, many of the non-computer

subsystems of the model are replaced with actual

hardware. Sensors and actuators provide the interface

signals necessary to connect the hardware subsystems

back to the model. The resulting model is part

mathematical and part real as shown in Figure 1. Because

the real part of the model inherently evolves in real time

and the mathematical part evolves in simulated time, it is

essential that the two parts be synchronized. This process

of fusing and synchronizing model, sensor, and actuator

information is called real time interfacing or hardware-in-

the-loop simulation and is an essential ingredient in the

modeling and simulation environment.

In particular, hardware-in-the-loop (HIL) simulation

environment supports and validates the UAV autopilot

hardware and software development [2]. To validate the

HIL system and aid the engineers in the assessment of the

systems and subcomponents, field experiments as shown

in Figure 1 are conducted to guarantee all laboratory

simulations in the HIL environment are accurate and

realistic [3]

Ref.

Actuators Mechanical

Systems

Electronics

Sensed Variables Modified Variables

Sensors

Figure 1. Hardware in the Loop Model

Table 1. .identifies the following six distinct functions:

Control: The control algorithm(s) in executable software form.

Computer: The embedded computer(s) used in the prod-uct.

Sensors

Actuators

Process: Product hardware excluding sensors, actuators, and the embedded computer.

Protocol: (optional) for bus-based distributed control applications.

4



Real Hardware

Components

Mathematically

Modeled Components

Description

Sensors

Actuators

Process

Flight Control Algorithm

Modify control system design subject to

unmodelled sensor, actuator, and

machinery errors.

Sensors

Actuators

Control (including the embedded com-

puter)

Process Evaluate validity of process model.

Protocol (for dis-tributed applica-

tions)

Control algorithm

Sensors

Actuators

Process

Evaluate the effects of data

transmission on design.

Signal processing hardware

Control algorithm

Sensors

Actuators

Process

Evaluate the effects of actual signal

processing hardware.

Table 1. Different configurations for hardware-in-the-loop simulation

Figure 2. Hardware-in-the-loop (HIL) simulation environment

Autopilot HIL

Hardware

Ground

Station

Wireless

Modem Simulink/Matlab

Dynamic model

Real time

Simulation

Flight

Dynamics

Visualization

Real time Simulink,

Two way communication

Sensor data

processing

Flight control

Flight

Dynamics

Simulation

900MHz

wireless

5



The comprehensive development of mechatronic systems

starts with modeling and simulation, model building for

static and dynamic models, transformation into simulation

models, programming and computer based control and

final implementation. In this atmosphere, hardware-in-the-

loop plays a major part. Using visual simulation tools in a

real time environment, major portions of the mechatronic

product could be simulated along with the hardware in the

loop.

It is possible to simulate the electronics, where the

actuators, mechanics and sensors are the real hardware. On

the other hand, if appropriate models of the mechanical

systems, actuators, and sensors are available, the

electronics could be the only hardware. There are different

ways in which hardware in the loop could be simulated

such as: electronics simulation, simulation of actuators and

sensors, or simulation of mechanical systems alone.

OTHER DESIGN TRENDS

Identify various concepts and evaluation of each of those concepts and analysis of each of those

concepts.

Investigate initial performance estimation and op-timization of aerodynamic design.

Study and definition of avionics and GCS capabil-ity requirements for mission profile of UAV.

Analyze the line of sight verification and demon-stration of motion optical tracking capability for

the UAV

System design and creation of the software and in-itial mechanical design and verification of base-

line avionics

Experimental design work, fabrication testing of a Zone-1 to 4 G-test device

GENERAL AERODYNAMIC MODELING OF

SMALL UAV [4,5,6,7 and 8]

The baseline concept should be capable of at least a 3:1

glide-slope, carrying a predetermined payload. Initial

focus should be on the viability of the aerodynamics.

Mechanical design should be initially limited to basic

size/fit and balance verification, with provisions for a

three-axis control system. This work is followed by

computational fluid dynamics work for the design that

must confirm lift/drag and neutral or positive aerodynamic

stability in all three axes.

Once the above requirements are satisfied based on the

modeling, fabrication and testing of a wind-tunnel model

of the baseline design should be conducted, in order to

confirm and/or adjust the CFD results. Further CFD

modeling is conducted, to develop a dynamic model of the

aircraft. Pitch, roll, and yaw rates are determined, and

control response. Baseline wind-tunnel model should

include functional actuators, to allow verification of the

CFD results. Iterative design procedures are used to

optimize the aerodynamic performance of the design.

Free-flight testing of low-speed sub-weight flight article

may be conducted, if deemed appropriate.

In Aerodynamics the nature of the boundary layer

viscous airflow is determined by a single dimensionless

parameter the Reynolds Numbers (Re)

oe

e

VRV

V

VVlR

0

where:

is the density of the airflow depending on the temperature, pressure, altitude and humidity of the air.

V is the mean velocity of the UAV relative to airflow

l is a characteristic linear dimension, representing the travelled length of the airflow

is the dynamic velocity of the airflow and is very dependent on temperature but particularly independent of

pressure.

l

V

0 is the constant speed for the given

l and ,

For modeling and simulation of a small UAV, the standard

six degree of freedom equations of motion for conventional

aircraft are used.

The governing equations are:

6



1. Force Equations

sin)(sin 000 gRrRqVm

Fgvrwq

m

Fu

vw eexx ,

cossin)(cossin 000 gRrRpVm

Fgurwp

m

Fv

uw eeyy

coscos)(coscos 000 gRqRpVm

Fguqvp

m

Fw

vv eezz

where

wand v,u - components of velocityV along x, y, and z body axes.

222V ,cossinV w,sinV v,coscos wvuVu

)(tan 1

u

w - angle- of- attack (onto vertical plane), )(tan22

1

wu

v

- sideslip angle

0g the gravity of the Earth

as wellas and are the Euler angles and they are named as the bank angle )( , pitch angle )(

and heading angle ).( [4,5] zy F and F ,xF -total forces along x, y and z body axes. They are composed of

gravitational, aerodynamic and propulsive forces.

r and p ,q -pitch, roll and yaw rates about the bodys x, y and z axes,

m-mass of body and w and v , u - accelerations according to the components of the velocity.

wu eeR andR ,

veR - are the Reynolds numbers for the speeds v, u and w

0

e0

e wuR , R ,

V

w

V

u

V

vR

oev

2. Moment Equations

zx

xzz

x

x

zx

xz

x

zy

zx

yxxz

x

xz

zx

xz

II

IM

I

M

II

I

I

IIqr

II

III

I

Ipq

II

Ip )()

)(()1(

21

2

y

y

y

xz

y

xz

I

M

I

Irp

I

IIprq

)( 22

zx

xzx

z

z

z

xz

zx

zyxz

z

yx

zx

xz

zx

xz

II

IM

I

M

I

I

II

IIIqr

I

II

II

Ipq

II

Ir )()()1(

21

2

7



Where,

r and q , p -accelerations due to the roll, pitch and yaw rates about the bodys x, y and z axes

zy I and I ,xI -are the moments of inertia about x, y and z body axes and xzI is the cross product of inertia with

respect to x and z body axes.

,2

1

i

n

i

ix xmI

,2

1

i

n

i

iy ymI

,2

1

i

n

i

iz zmI

ii

n

i

ixz xzmI

1

n is the number of the bodies, i elementary masses im and ii z and y ix are their coordinates.

zy M and M ,xM -total moments about x, y and z body axes, which are produced by aerodynamic and propulsive

forces. Mx is rolling moment, My is pitching moment and Mz is yaw moment.

2M ,

2M ,

2

2

z

2

y1

2Ne

NMe

Me

Ix

SbCRSbCq

CcSRCcSq

SbCRSbCqM

here 2

2

1Vq - dynamic pressure, - density of air current, S- wing total area, b- wing span

c - mean aerodynamic chord.

N , C and MI CC -are the coefficients of roll, pitch and yaw moments [4,5]

These moments are related to the drag (D), lift (L) and side (crosswind) forces (Y) through the expressions

YLD SCqSCqSCqD Y ,L ,

Y , C and LD CC -are the coefficients of drag, lift and side (crosswind) forces[6]

3. Kinematic Equations:

seccossecsin

sincos

tancostansin

rq

rq

rqp

where:

and , are the Euler angles and they are named as the bank angle )( , pitch angle )( and

heading angle [7, 8, 9]. and , are the rate of change of those angles.

8



4. Navigation equations

)cossincossin(sin)cossinsinsincos(coscos0 wvu eeeN RRRVp

cossinsinsin(cos)sinsinsincos(cossincos0 wvu eeeE RRRVp coscoscossinsin0 wvu eee RRRVh

Where, h and P , E

NP are the velocities, representing the derivatives of the geometrical coordinates aligned with north (N), east (E) and altitude (h) of the UAV.

5. The flying coordinates

0

0

0

ziZhYgXz

yfZeYdXy

xcZbYaXx

Where,

z andy ,x are the coordinates of UAV according to the ground stationary vision system which is used

for controlling the traffic of the UAV.

Zand Y ,X are the coordinates of the detecting object according to the miniature mobile vision system.

o 00 z andy ,x are the initial coordinates of UAV

according to xyz coordinate system

i andh g, f, e, d, c, b, ,a are the coefficients of the various combinations of multiplications and summations

of the sines and cosines of the Euler angles between

the axes of the xyz and XYZ coordinate systems [9,10 and 11]

SURVIVABILITY FROM G-FORCES AND

MECHANICAL SHOCK

Once the external form is defined, the internal

structure and mechanical/electromechanical installation is

attempted. At this point, the at least some results from the

G-survivability screening should be available, as well as

initial results from the optical tracking software

development, allowing selection of internal components.

Since the baseline model already has the majority of the

mechanical components worked out, the focus will

primarily be on refinement of the components, developing

mounting arrangements for onboard equipment and

analysis to confirm structural G-tolerance.

Material choices should be conventional whenever possible,

to simplify fabrication. Weight/balance analysis should

also be performed throughout this stage.

9



G-survivability G-Test Rig for UAV Tests

In order to facilitate in-house testing of small components

(primarily avionics and guidance elements), a pneumatic

G-test rig is essential. Testing results confirm mechanical

functionality at the design loads. If the UAV is designed

for Zone-1 applications, peak accelerations of 2100 G have

to be generated. Based on dynamic modeling, the

acceleration profiles provide a reasonable facsimile of the

acceleration data. An instrumentation package will allow

measurement of the payload velocity as it leaves the

accelerator stage, which in turn will allow estimation of the

average acceleration

Camera

Analog transmitters

Digital transceivers

IR horizon sensors/processors

Autopilot

GPS receiver

Actuators

Battery pack In addition, the mounting fixtures include damping

materials and special mounting arrangements, to allow

evaluation of G-mitigating techniques.

Shock Response Study

UAV components encounter mechanical shock from a va-

riety of sources. Components must be designed and tested

accordingly to ensure reliability. For example, the design-

ers must anticipate transportation and shipping shock. For

example, if the container is placed on a truck which runs

over a speed bump, the avionics components are encased in

foam packing material inside a shipping container. The

avionics component may receive a half-sine shock pulse.

This type of pulse can be readily represented in the time

domain by its duration and peak amplitude. Also, repro-

duction of this pulse in an environmental test laboratory is

usually straightforward. Eventually, the avionics compo-

nent is integrated into a spacecraft. The component must

now withstand a series of flight shock pulses. These pulses

result from rocket motor ignition, staging, and deployment

events. Linear shape charge and pyrotechnic devices are

typically used to initiate staging events.

CONCLUSION

In conclusion, some of the design methodologies

in determining the relative merit of the different concepts

are discussed. The major challenges are in the areas of

evaluation of structural viability, mechanical complexity

and overall system survivability by G forces. This paper

examines some of the design methodologies and hardware-

in-the loop simulation environment to support and validate

the UAV hardware and software development.

NOMENCLATURE

Hybrid Unmanned Aerial Vehicles, Micro UAVs, G-Test,

Axiomatic Design, TRIZ, Aero-dynamic design, Hardware

in the loop

ACKNOWLEDGEMENT

The authors thank the support given by Mr. Leon Manole

of ARDEC, Piccatiny, NJ

REFERENCES

1. Chafac, M., Howell, K., Williams, C and Sexton, J Transforming Projectile System Proceedings IEEE systems and Information Engineering Design University of Virginia, Charlottesville, April 23, 2010

2. Lyons. D.H., A Military Perspective on Small Unmanned Aerial Vehicles IEEE magazine of Instrumentation and Measurement Vol. 7, Issue 3, Sept. 2004

3. Jung, D and Tsiotras P Modeling and Hardware-in-the-Loop Simulation for a Small Unmanned Aerial Vehicle,

Georgia Institute of Technology, Atlanta, GA, 30332-

0150, American Institute of Aeronautics and

Astronautics

4. Sean M. Calhoun, Dr. Frank Van Graas and Dr. Douglas Lawrence. Aerodynamic Modeling for the Ohio University UAV. (2001) Identification of Aerodynamic Coefficients for a UAV (2003). Avionics Engineering Center, Ohio University.

5. F-16 Aircraft Model. University of California at San Diego, NASA Lab.

6. Bei Lu. Linear Parameter-Varying Control of An F-16 Aircraft at High angle of Attack. Ph.D. Dissertation. NC State University. (2004)

7. Laban, M. On-line Aircraft Aerodynamic Model Identification. Ph.D. Dissertation. Delft University of Technology (1994).

8. Stevsns, B. L., and Lewis, F. L. Aircraft Control and Simulation. John Wiley & sons, Inc. (1992).

9. Morelli, E., Global nonlinear parametric modeling with application to F-16 Aerodynamics. Dynamics and control Branch, NASA Langley research Center. (1998)

10. Valasek, J. and Smith, D. Comparison of Agility Metrics to Beck Agility Metrics Using Linear Error

Theory. Texas A&M University; College Station. Journal of Guidance, Control and Dynamics, Vol. 26.

No. 1. January-February 2003.

11. Sadraey, M and Colgren, R. A Dynamic Performance Evaluation technique for Unmanned Aerial Vehicles. The University of Kansas. ALAA Atmospheric Flight

Mechanics Conference , August 2006

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565_1

Documents

design concepts

design trends

design of micro uav

aerodynamic design

micro uavs

axiomatic design approach

simulation of complex

systematic design process