cad workbook

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COMPUTER AIDED ENGINEERING

A SEMINAR REPORT

Submitted by

ASWATHY SETHU

Partial fulfilment for the award of the degree of

Master of Technology

DEPARTMENT OF PRODUCTION ENGINEERING

GOVERNMENT ENGINEERING COLLEGE THRISSUR

December 2011


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GOVERNMENT ENGINEERING COLLEGE THRISSUR

DEPARTMENT OF PRODUCTION ENGINEERING

2011

BONAFIDE CERTIFICATE

Certified that this is the report of the seminar titled


Presented by

Ms. Aswathy Sethu

Of first semester M.Tech in partial fulfillment of the requirement for the award

of the degree of Master of Technology in Production Engineering

(Manufacturing Systems Management) of the University of Calicut

Staff-in-charge

Prof. MANJITH KUMAR

Associate Professor

Department of Production Engineering

Government Engineering CollegeThrissur

Prof. P.V. Mary C Kurien

Professor and Head

Department of Production Engineering

Government Engineering College

Thrissur


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ABSTRACT


Computer aided engineering (CAE) is an analysis performed at the

computer terminal using a CAD system. It includes computer-aided design

(CAD), computer-aided analysis (CAA), computer-integrated manufacturing

(CIM), computer-aided manufacturing (CAM), material requirements planning

(MRP), and computer-aided planning (CAP). Its purpose is mainly to analyze

the different materials, products, their performance and quality, such as

durability, stability, etc. It has many advantages like improved safety and

product quality, reduced product cost, customer satisfaction, etc. and so it has

many applications like used to analyze the properties of material, commercial

and flight simulations, etc. It has 3 phases: pre-processing, analysis solver, post-

processing of results.

CAE is mainly of 3 types: finite element analysis (FEA),

computational fluid dynamics (CFD), and Boundary Element Analysis (BEA).

FEA is used to conduct static and dynamic analysis. CFD is used to optimize

components for efficient fluid flow and heat transfer. BEA is used to predict

noise characteristics on various systems.

One of the real world examples is MEMS that is micro electro

mechanical systems. It has the size of a grain of salt or the eye of a needle.

ACKNOWLEDGEMENT


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I take this opportunity to thank the Lord ALMIGHTY for being my driving force

andfor his immense blessings towards the successful presentation completion of my seminar.

I wish to express my deepest gratitude to Dr. K. Vijayakumar, Principal of

Government Engineering College, Thrissur and Prof. P.V.Gopinadhan, H.O.D of

Production Department, Prof. Manjeet, who is my guide. I am deeply indebted to him for the

timey help and meticulous guidance that he provided to help with my seminar. I take this

opportunity to sincerely thank my guide for his guidance and encouragement in carrying out

this seminar.

I would also like to express my profound gratitude to Dr. Haris Naduthodi, Ms.

Mary C Kurian and Mr. Sunil D T, Prof. Parameshvaran, Mr. Satish for their constant

and valuable suggestions while doing the seminar work.

Last but not least I would like to extend my special thanks to my beloved family

members and friends for their inspiration and help during the course of this seminar research.

Thrissur

16-12- 2011 ASWATHY SETHU


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TABLE OF CONTENTS

CHAPTER NO. TITLE PAGE NO.

Abstract iii

Acknowledgement iv

1. INTRODUCTION

2. CONCEPT AND DEFINITION

3. GOALS OF COMPUTER AIDED ENGINEERING

4. PHASES OF CAE

5.

CONCEPT OF CAE DEVELOPMENT

IN A CAR MANUFACTURING COMPANY

6. BENEFITS OF CAE

7. APPLICATIONS OF CAE

8. MEMS

9. CONCLUSION


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1. INTRODUCTION

The future success of a manufacturing enterprise is likely to be determined by

the speed and efficiency with which it incorporates new technologies into its operations. The

process which is currently used to engineer, or re-engineer, manufacturing systems is often ad

hoc. Computerized tools are used on a very limited basis. Given the costs and resources

involved in the construction and operation of manufacturing systems, the engineering process

must be made more scientific. Powerful new computing environments for engineering

manufacturing systems could help achieve that objective.

Today, Computer Aided Engineering (CAE) technology contributes decisively

to shortening and optimizing product development cycles in many fields of industry and

research. Computer aided analysis and simulation enables our customers to assess and test the

behaviour of future components, products and processes by subjecting them to a range of

computer simulated physical conditions. This leads to savings in both the time and money

which would have been spent on cost-intensive test runs without any loss in quality and

opens up new possibilities for innovation. Computer aided engineering (CAE) retrieves

description and geometry from a computer aided manufacturing (CAD) database. Computer

aided engineering (CAE) is an analysis performed at the computer terminal using a CAD

system. Thus software tools that have been developed to support the activities in computer

analysis are considered CAE tools. CAE tools are being used, for example, to analyze the

robustness and performance of components and assemblies. The term encompasses

simulation, validation, and optimization of products and manufacturing tools. In the future,

CAE systems will be major providers of information to help support design teams in decisionmaking. In regard to information networks, CAE systems are individually considered a

single node on a total information network and each node may interact with other nodes on

the network. CAE systems can provide support to businesses. This is achieved by the use of

reference architectures and their ability to place information views on the business process.

Reference architecture is the basis from which information model, especially product and

manufacturing models. The term CAE has also been used by some in the past to describe the

use of computer technology within engineering in a broader sense than just engineering

analysis.


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2. CONCEPT AND DEFINITION

2.1 ORIGIN OF CAE:

Historically, engineers analyzed designs by building and testing physical

prototypes, performing calculations by hand or with some computing aid such as a slide rule.

They frequently used tabulated mathematical functions, approximation methods, and data

accumulated from previous experience and physical testing to simplify their analyses. Some

analyses were so time-consuming that, when done at all, they could be completed only for

one simplified example. This frequently led to under- and over-designed systems. The first

case resulted in systems that did not work properly or failed outright. In the second case, the

systems were more expensive than necessary or too heavy to meet their goals. Physical

prototypes were (and remain) very costly and time-consuming to build and testand they

often have to be recreated as designs are changed. The advent of analog and digital computers

provided engineers with systems capable of analyzing designs much more quickly and

allowed them to undertake analyses that were previously impractical to attempt. However,

early computer systems were too slow and limited in capacity (memory, storage, I/O speed)

to handle extremely large or complex mechanical systems. While they provided a base for

new, more extensive design evaluations, many of the historical problems remained and new

problems arose. These included limited access to expensive, high powered computing

systems and difficulties describing the physical form of designs in a way that computers

could work with them efficiently. Therefore, many early analysis programs used

unrealistically simplified, schematic-like descriptions of the physical system. It was

impossible to describe any but the simplest systems geometry within the computing

environment.

Then came the creation of CAD/ CAM systems by the aerospace industry in

the early 1960s to assist with the massive design and documentation tasks associated withproducing airplanes. By the late 1970s, these codes were being distributed to other industries.

CAD/CAM systems have been used primarily for detail design and drafting along with the

generation of numerical control instructions for manufacturing. Gradually, more CAE

functions are being added to CAD/CAM systems. A trend toward open architecture with

flexible geometry interfaces is stimulating the addition of more analysis and manufacturing

functions. Modelling with CAD/CAM systems has become fairly sophisticated. Most popular

commercial systems support 2D and 3D wireframe, surface models, and solid models.


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Rendered surface models differ fr

about the interior of the object.

2.2 DEFINITON OF CAE:

Computer aided eng

terminal using a CAD system. It

analysis (CAA), computer-integrat

(CAM), material requirements pla

mainly depends on CAD. It is usu

industry.

Flow diagra

Computer-aided des

drafting (CADD) ,[1] is the use of

documentation. Computer Aided D

CADD software provides the user

processes; drafting, documentation

the form of electronic files for pri

vector based graphics to depict the

graphics showing the overall appea

Computer Integrate

product development and manufac

om solid models in that the latter have full

neering (CAE) is an analysis performed at t

includes computer-aided design (CAD), co

ed manufacturing (CIM), computer-aided ma

ning (MRP), and computer-aided planning (

lly used in every industry such as aerospace,

for a computer aided engineering

ign (CAD), also known as computer-aided

omputer technology for the process of design

rafting describes the process of drafting with

with input-tools for the purpose of streamli

, and manufacturing processes. CADD outpu

nt or machining operations. CADD software

objects of traditional drafting, or may also pr

ance of designed objects.

Manufacturing (CIM) encompasses the enti

turing activities with all the functions being

nformation

e computer

puter-aided

nufacturing

AP). CAE

automobile

design and

and design-

computer.

ing design

is often in

uses either

duce raster

re range of

carried out


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with the help of dedicated software packages. The data required for various functions are

passed from one application software to another in a seamless manner. For example, the

product data is created during design. This data has to be transferred from the modelling

software to manufacturing software without any loss of data. CIM uses a common database

wherever feasible and communication technologies to integrate design, manufacturing and

associated business functions that combine the automated segments of a factory or a

manufacturing facility. CIM reduces the human component of manufacturing and thereby

relieves the process of its slow, expensive and error-prone component. CIM stands for a

holistic and methodological approach to the activities of the manufacturing enterprise in order

to achieve vast improvement in its performance. This methodological approach is applied to

all activities from the design of the product to customer support in an integrated way, using

various methods, means and techniques in order to achieve production improvement, cost

reduction, fulfillment of scheduled delivery dates, quality improvement and total flexibility in

the manufacturing system. CIM requires all those associated with a company to involve

totally in the process of product development and manufacture. In such a holistic approach,

economic, social and human aspects have the same importance as technical aspects. CIM also

encompasses the whole lot of enabling technologies including total quality management,

business process reengineering, concurrent engineering, workflow automation, enterprise

resource planning and flexible manufacturing.

Material requirements planning (MRP) is a production planning

and inventory control system used to manage manufacturing processes. Most MRP systems

are software-based, while it is possible to conduct MRP by hand as well. The basic function

of MRP system includes inventory control, bill of material processing and elementary

scheduling. MRP helps organizations to maintain low inventory levels. It is used to plan

manufacturing, purchasing and delivering activities. "Manufacturing organizations, whatevertheir products, face the same daily practical problem - that customers want products to be

available in a shorter time than it takes to make them. This means that some level of planning

is required." Companies need to control the types and quantities of materials they purchase,

plan which products are to be produced and in what quantities and ensure that they are able to

meet current and future customer demand, all at the lowest possible cost. Making a bad

decision in any of these areas will make the company lose money.


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Computer-aided process planning (CAPP) is the use of computer technology

to aid in the process planning of a part or product, in manufacturing. CAPP is the link

between CAD and CAM in that it provides for the planning of the process to be used in

producing a designed part. Process planning is concerned with determining the sequence of

individual manufacturing operations needed to produce a given part or product. The resulting

operation sequence is documented on a form typically referred to as a route sheet containing

a listing of the production operations and associated machine tools for a workpart or

assembly. Process planning in manufacturing also refers to the planning of use of blanks,

spare parts, packaging material, user instructions (manuals) etc. Process planning translates

design information into the process steps and instructions to efficiently and effectively

manufacture products. As the design process is supported by many computer-aided tools,

computer-aided process planning (CAPP) has evolved to simplify and improve process

planning and achieve more effective use of manufacturing resources.

3. GOALS OF COMPUTER AIDED ENGINEERING

The goals of computer-aided engineering (CAE) are:

improved product quality

improved safety

reduced engineering time, achieved through fewer design iterations

improved product functionality and usability

reduced number of prototypes, ultimately leading to their elimination in many cases

reduced product cost.

These goals has helped computer aided engineering to achieve various heights like:

CAE can be used to perform variety tests like car crash the test simulation

Can be used for Commercial and military flight simulations

It is also used to analyze properties of different types material used in production

application of computerized methods during the design of technical systems

It increases production efficiency and quality through better designs

It is also a Tool for decision making-what the product is going to look like, its

performance characteristics, what improvements need to be made? CAD analysis on be done on the computer screen


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There is no need to build products prototypes

Results of analysis is essential and can be saved for future of the product

Customer satisfaction is priority and can be achieved through CAE

CAE has to be compliant with many U.S. and international standards and so the

product real-world performance and safety is achieved

It also provide the customers with a concept before building expensive prototypes and

pre-production units and hence customer satisfaction can be achieved.

4. PHASES OF CAE

CAE applications support a wide range of engineering disciplines or

phenomena including:

Stress and dynamics analysis on components and assemblies using finite element

analysis (FEA)

Thermal and fluid analysis using computational fluid dynamics (CFD)

Kinematics and dynamic analysis of mechanisms (multi body dynamics)

In general, there are three phases in any computer-aided engineering task:

Pre-processing defining the model and environmental factors to be applied to it. It is

typically a finite element model, but facet, voxel and thin sheet methods are also used

in this phase.

Analysis solver- it is usually performed on high powered computers.

Post-processing of results it is the last phase in any computer aided engineering task

and is done using visualization tools.

This cycle is iterated, often many times, either manually or with the use of commercial

optimization software.

4.1 FINITE ELEMENT ANALYSIS:

The finite element method (FEM)(its practical application often known

as finite elementanalysis (FEA)) is a numerical techniquefor finding approximate solutions

ofpartial differential equations(PDE) as well as integral equations. The solution approach is


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based either on eliminating the differential equation completely (steady state problems), or

rendering the PDE into an approximating system of ordinary differential equations, which are

then numerically integrated using standard techniques such as Euler's method, Runge-Kutta,

etc.

In solvingpartial differential equations, the primary challenge is to create an

equation that approximates the equation to be studied, but is numerically stable, meaning that

errors in the input and intermediate calculations do not accumulate and cause the resulting

output to be meaningless. There are many ways of doing this, all with advantages and

disadvantages. The finite element method is a good choice for solving partial differential

equations over complicated domains (like cars and oil pipelines), when the domain changes

(as during a solid state reaction with a moving boundary), when the desired precision variesover the entire domain, or when the solution lacks smoothness. For instance, in a frontal crash

simulation it is possible to increase prediction accuracy in "important" areas like the front of

the car and reduce it in its rear (thus reducing cost of the simulation). Another example would

be inNumerical weather prediction, where it is more important to have accurate predictions

over developing highly-nonlinear phenomena (such as tropical cyclones in the atmosphere,

or eddiesin the ocean) rather than relatively calm areas.

Example for finite element analysis


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APPLICATION OF FINITE ELEMENT ANALYSIS:

A variety of specializations under the umbrella of the mechanical engineering

discipline (such as aeronautical, biomechanical, and automotive industries) commonly use

integrated FEM in design and development of their products. Several modern FEM packages

include specific components such as thermal, electromagnetic, fluid, and structural working

environments. In a structural simulation, FEM helps tremendously in producing stiffness and

strength visualizations and also in minimizing weight, materials, and costs. FEM allows

detailed visualization of where structures bend or twist, and indicates the distribution of

stresses and displacements. FEM software provides a wide range of simulation options for

controlling the complexity of both modelling and analysis of a system. Similarly, the desired

level of accuracy required and associated computational time requirements can be managed

simultaneously to address most engineering applications. FEM allows entire designs to be

constructed, refined, and optimized before the design is manufactured.

This powerful design tool has significantly improved both the standard of

engineering designs and the methodology of the design process in many industrial

applications. The introduction of FEM has substantially decreased the time to take products

from concept to the production line. It is primarily through improved initial prototype designs

using FEM that testing and development have been accelerated. In summary, benefits of

FEM include increased accuracy, enhanced design and better insight into critical design

parameters, virtual prototyping, fewer hardware prototypes, a faster and less expensive design

cycle, increased productivity, and increased revenue.

4.2 BOUNDARY ELEMENT ANALYSIS:

The boundary element method (BEM) is a numerical computational method of

solving linear partial differential equations which have been formulated as integral

equations (i.e. in boundary integralform). It can be applied in many areas of engineering and

science including fluid mechanics, acoustics, electro-magnetics, and fracture mechanics. The

integral equation may be regarded as an exact solution of the governing partial differential

equation. The boundary element method attempts to use the given boundary conditions to fit

boundary values into the integral equation, rather than values throughout the space defined by

a partial differential equation. Once this is done, in the post-processing stage, the integral

equation can then be used again to calculate numerically the solution directly at any desired

point in the interior of the solution domain.


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BEM is applicable to problems for which Green's functionscan be calculated. These usually

involve fields in linearhomogeneousmedia. This places considerable restrictions on the

range and generality of problems to which boundary elements can usefully be applied.

Nonlinearities can be included in the formulation, although they will generally introduce

volume integrals which then require the volume to be discretised before solution can be

attempted, removing one of the most often cited advantages of BEM

The boundary element method is often more efficient than other methods,

including finite elements, in terms of computational resources for problems where there is a

small surface/volume ratio [1]. Conceptually, it works by constructing a "mesh" over the

modelled surface. However, for many problems boundary element methods are significantly

less efficient than volume-discretisation methods. Boundary element formulations typicallygive rise to fully populated matrices. This means that the storage requirements and

computational time will tend to grow according to the square of the problem size. By

contrast, finite element matrices are typically banded (elements are only locally connected)

and the storage requirements for the system matrices typically grow quite linearly with the

problem size. Compression techniques (e.g. multipole expansions or adaptive cross

approximation/hierarchical matrices) can be used to ameliorate these problems, though at the

cost of added complexity and with a success-rate that depends heavily on the nature of the

problem being solved and the geometry involved.

4.3 COMPUTATIONAL FLUID DYNAMICS:

Computational fluid dynamics, usually abbreviated as CFD, is a branch

of fluid mechanics that uses numerical methods and algorithms to solve and analyze

problems that involve fluid flows. Computers are used to perform the calculations required to

simulate the interaction of liquids and gases with surfaces defined by boundary conditions.With high-speed supercomputers, better solutions can be achieved. Ongoing research yields

software that improves the accuracy and speed of complex simulation scenarios such as

transonic or turbulent flows. Initial validation of such software is performed using a wind

tunnel with the final validation coming in full-scale testing, e.g. flight tests. The fundamental

basis of almost all CFD problems are the NavierStokes equations, which define any single-

phase fluid flow. These equations can be simplified by removing terms describing viscosity

to yield the Euler equations. Further simplification, by removing terms describing vorticity


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yields the full potential equations. Finally, these equations can be linearized to yield

the linearized potential equations.

In this approach, these procedures are followed:

Duringpreprocessing

The geometry(physical bounds) of the problem is defined.

The volumeoccupied by the fluid is divided into discrete cells (the mesh). The mesh

may be uniform or non uniform.

The physical modeling is defined for example, the equations of motions

+ enthalpy+ radiation + species conservation

Boundary conditions are defined. This involves specifying the fluid behaviour and

properties at the boundaries of the problem. For transient problems, the initial

conditions are also defined.

The simulationis started and the equations are solved iteratively as a steady-state or

transient.

Finally a postprocessor is used for the analysis and visualization of the resulting solution.

4.4 KINEMATIC AND DYNAMIC ANALYSIS:

"Motion study" is a catch-all term for simulating and analyzing the movement

of mechanical assemblies and mechanisms. Traditionally, motion studies have been divided

into two categories: kinematics and dynamics. Kinematics is the study of motion without

regard to forces that cause it; dynamics is the study of motions that result from forces. Other

closely related terms for the same types of studies are multibody dynamics, mechanical

system simulation, and even virtual prototyping. Kinematic analysis is a simpler task than

dynamic analysis and is adequate for many applications involving moving parts. Kinematic

simulations show the physical positions of all the parts in an assembly with respect to the

time as it goes through a cycle. This technology is useful for simulating steady-state motion

(with no acceleration), as well as for evaluating motion for interference purposes, such as

assembly sequences of complex mechanical system. Many basic kinematic packages,

however, go a step further by providing "reaction forces," forces that result from the motion.

Dynamic simulation is more complex because the problem needs to be further defined and

more data is needed to account for the forces. But dynamics are often required to accurately

simulate the actual motion of a mechanical system. Generally, kinematic simulations help


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evaluate form, while dynamic simulations assists in analyzing function. Traditionally,

kinematics and dynamics have followed the classic analysis software method of pre

processing (preparing the data), solving (running the solution algorithms, which involve the

solution of simultaneous equations), and post processing (analyzing the results). Even though

today's programs are much more interactive, most programs follow this basic process since it

is a logical way to solve the problem. Most solvers are available as independent software

programs. The basic output of motion studies are numerous, including animation, detecting

interference, trace functions, basic motion data, and plots and graphs. Animated motions are

the classic output of simple kinematic analyses. Initially, the designer uses simple animation

as a visual evaluation of motion to see if it is what is desired. More sophisticated animations

can show motion from critical angles or even inside of parts, a definite advantage over

building and running a physical prototype. The ability to detect and fix interferences without

switching between software is one of the primary benefits of integrating motion simulation

and CAD.

Most systems provide colour feedback, for example, by turning to red parts

that experience interferences. More useful, however, are systems that turn the interference

volume into a separate piece of geometry, which can then be used to modify the parts to

eliminate the interference. Trace functions provide additional information about motion. The

motion of a joint or a particular point on a part can be plotted in 3D as a line or surface. Or,

the system can leave copies of the geometry at specified intervals. Such functions can provide

an envelope of movement that can be used to design housings or ensure clearances. Motion

data, such as forces, accelerations, velocities, and the exact locations of joints or points on

geometry can usually be extracted, although such capabilities are more applicable to dynamic

simulations rather than kinematic studies. Some systems allow users to attach instruments to

their models to simplify specifying what results they want to see. Most packages provide aplethora of plotting and graphing functions. Plots and graphs are most commonly used

because values vary over time and are more meaningful than a single value at any given time.

An especially useful capability for studying design alternatives is to plot the results of two

different simulations on the same graph. Such data can also help designers determine the size

of motors, actuators, springs, and other mechanism components. Forces that result from

motion are of particular interest because they can be used as loads (or, at least, to calculate

them) for structural analysis of individual members. Typically, the highest load for a cycle is

used to perform a linear static finite element analysis (FEA) of critical individual components


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of a mechanism. Integration of solid modelling, motion simulation, and FEA software can

greatly streamline this processespecially important when studying design alternatives,

where many analyses are required.

5.

CONCEPT OF CAE DEVELOPMENT IN A CAR

MANUFACTURING COMPANY

The example for the usage of computer aided engineering is taken from

Stadco automotives, a car manufacturing company. Stadco is the UK's largest Tier 1 supplier

of BIW pressings and assemblies and the only one with a full product design capability from

styling and concept development through to production design, launch support and

production facility implementation. Stadco has operations in the UK, Germany, Russia and

now, India. Stadco has also delivered a number of projects in India, North America, South

America and Europe. Stadco Automotive Pvt. was formed in 2008 and will offer Engineering

services, BIW prototyping and BIW manufacture through a phased move into the Indian

market. Stadco established its Indian technical centre in Chennai in 2008, supporting both

international OEM's and domestic Indian automotive manufacturers.


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The process in the manufacture of car consists of many process like concept of CAD

development, CAD design, PDM and DMU development, Durability simulation, NVH

simulation, Vehicle crash development.

5.1 CONCEPT OF CAD DEVELOPMENT:

Stadco integrates Concept CAD development for a quick cost effective

method, by which to establish proposals / ideas for evaluation. Stadco's concept team is best

used in parallel to complement detailed sketches and illustrations. It has the benefit of 3D and

is dimensionally accurate. Realistic visuals at this early stage enable the design process to

move forward quickly to satisfactory conclusions by using an integrated team approach.

5.2 CAD DESIGN:

Stadco has been in the forefront of CAD design for decades. Our experienced

design team uses cutting edge technology to realise design benefits for our customers. Our

team's experience covers a range of different CAD systems so they can deliver excellently

engineered products in the appropriate format for our customers. This also allows us to utilise

the best software for any given design. The engineering design team can use parametric

modeling solutions. The parametric modelers are aware of the characteristics of components

and the interactions between them. By maintaining relationships between elements a model

can quickly be manipulated, allowing variant or face-lifts of vehicles to be achieved in very

competitive time scales.

5.3 PDM AND DMU DEVELOPMENT:

DMU, Digital mock-up is one of the most powerful engineering tools

currently available. Through using part information stored within Computer Aided Design


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packages, prototype builds can be simulated. The Stadco programme teams have access to

projection facilities to allow life-size screening during design reviews. This ensures the core

team can simultaneously view areas of concern. In addition Stadco uses secure remote

computer conferencing to allow international multi-site project teams to collaborate whilst

viewing the same packaging data. Discussions are aided by using clash detection routines and

dynamic sectioning options. DMU technology is a powerful tool to detect problem areas long

before any metal parts are formed. This reduces the number of prototypes required and

maximises the benefit of using builds to trial assembly processes and not to trial designs.

5.4 DURABILITY SIMULATION:

Stadco's specialists in durability can design and develop structures with the

ability to meet a combination of abuse loads (strength) and cyclic loads (fatigue). In the case

of abuse loads these are well understood, however the cyclic loads generally require

measured road load data. Stadco's relationship with the top testing houses across the world

gives us the capability to capture real road load data to cover all our customers' requirements,

however unique.

5.5 NVH SIMULATION:

Noise, Vibration, and Harshness (NVH) is of strategic importance in

delivering the brand values and in meeting customers increasing level of expectations for

quality and vehicle comfort.

Stadco understands the process of converting the brand values into objective vehicle targets,

which in turn are cascaded down to sub-system and component level. This gives thefundamental requirement for engineering NVH character of the vehicle. The NVH


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performance of the vehicle covers many different operating conditions and spans a wide

frequency range. In order to design for these numerous conditions, a large number of

simulation and test activities are undertaken to address performance at both the vehicle and

component levels. Stadco has powerful, dedicated cluster hardware enabling numerous

simulations to be undertaken quickly, often around the clock. This ensures calculation ofperformance levels and the timely generation of optimum solutions.

5.6 VEHICLE CRASH DEVELOPMENT:

Vehicle safety targets are primarily driven by legislation and the legal

requirements which must be met in order to sell vehicles in a particular market. These are

also complemented by the OEM internal company standards, and external factors such as

consumer group and insurance testing, competitor vehicles, etc.

6. BENEFITS OF CAE

The benefits of CAE are:

Reduced product development cost and time, with improved product quality and

durability.

Designs can be evaluated and refined using computer simulations

CAE helps engineering teams manage risk and understand the performance implications

of their designs


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7. APPLICATION OF CAE

In area of piping plant design in civil engineering

In roadway design, most surveying function

Used in many specialized analysis, for circuit design, VLSI device design, and

simulation

Used in Mechanical event simulation (MES)

Control systems analysis

Simulation of manufacturing processes like casting, molding and die press forming

Optimization of the product or process

8. MEMS

MEMS is micro electro mechanical system. Micro Electro Mechanical

Systems (MEMS) are micromachines the size of a grain of salt or the eye of a needle that

integrate mechanical elements, sensors, actuators and electronics on a common silicon

substrate. These devices can replace bulky actuators and sensors with micro scale

equivalents that can be produced in large quantities by fabrication process used in integrated

circuit photolithography. This reduces cost, bulk weight and power consumption while

increasing performance, production volume and functionality by orders of magnitude. The

applications of MEMS are:

optical switches within telecommunication and networking systems,

accelerometers in automotive airbags, inkjets in desktop printers and

sensors in medical testing equipment.

9. CONCLUSION

CAE is an analysis entirely done on computer using CAD systems. Its purpose

is to analyze different materials, products, their performance and quality such as durability,

stability, endurance and/or reactivity to any possible factor that can affect the performance of

the material, part, and/or the product A typical CAE process comprises of pre-processing,


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solving, and post-processing steps. In the pre-processing phase, engineers model the

geometry and the physical properties of the design, as well as the environment in the form of

applied loads or constraints. Next, the model is solved using an appropriate mathematical

formulation of the underlying physics. In the post-processing phase, the results are presented

to the engineer for review. The analysis of CAE consists of mainly 4 methods like finite

element analysis, computational fluid dynamics, boundary element analysis, kinematic and

dynamic analysis. It has many advantages like its cost saving and ensures customer

satisfaction and improves the speed, efficiency and the quality of many products ranging

from simple parts to vehicles, airplanes etc. Designs can be evaluated and refined using

computer simulations. Its applications include control systems analysis, simulation of

manufacturing processes like casting, moulding and die press forming, Optimization of the

product or process and mems.

REFERENCES

CAD/CAM/CIMby P.Radhakrishnan, 3rdedition, New Age International publications

Fundamentals of computer aided engineering, by B.Raphael and I.F.C. Smith, Wiley

publishers

http://www.roushind.com/html/cae.html

http://www.computeraidedengineering.com

http://www.fea-online.com

http://www.marc.com

http://www.optem.com

http://www.ece.curtin.edu.au

http://kernow.curtin.edu.au/cae.html

www.stadco.co.in
http://www.roushind.com/html/cae.htmlhttp://www.computeraidedengineering.com/http://www.fea-online.com/http://www.marc.com/http://www.optem.com/http://www.ece.curtin.edu.au/http://kernow.curtin.edu.au/cae.htmlhttp://www.stadco.co.in/http://www.stadco.co.in/http://kernow.curtin.edu.au/cae.htmlhttp://www.ece.curtin.edu.au/http://www.optem.com/http://www.marc.com/http://www.fea-online.com/http://www.computeraidedengineering.com/http://www.roushind.com/html/cae.html


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