analysis and optimization of container lifting … file_enr...this is to certify that the synopsis...

ANALYSIS AND OPTIMIZATION OF CONTAINER LIFTING DEVICE

USED FOR SOLID WASTE MANAGEMENT

A SYNOPSIS SUBMITTED

FOR THE AWARD OF DEGREE OF

DOCTOR OF PHILOSOPHY

IN

MECHANICAL ENGINEERING

Submitted by

Prof. UTPAL VINODCHANDRA SHAH

Enrollment No. 139997119018

Associate Professor, Mechanical Engineering Department,

Government Engineering College, Modasa, Gujarat

Under Guidance of

Dr. Prof. G.H.Upadhyay Professor& Head, Mechanical Engineering Department

L.D. College of Engineering, Ahmedabad, Gujarat

GUJARAT TECHNOLOGICAL UNIVERSITY

AHMEDABAD


AHMEDABAD

CERTIFICATE

This is to certify that the synopsis entitled ―ANALYSIS AND OPTIMIZATION OF CONTAINER

LIFTING DEVICE USED FORSOLID WASTE MANAGEMENT has been undertaken and written under

my supervision and it describes the original research work carried out by UTPAL VINODCHANDRA

SHAH registered at Gujarat Technological University under the Faculty of Engineering in subject

(specialization) of Mechanical Engineering for the Degree of Doctor of Philosophy. To the best of

my knowledge and belief, this work has not been submitted elsewhere for any degree of any other

institution in India or abroad.

Supervisor’s Signature Dr. (Prof.) G.H.Upadhyay Professor& Head, Mechanical Engineering Department

L.D. College of Engineering, Ahmedabad


AHMEDABAD

DECLARATION I hereby certify that I am the sole author of this thesis and that neither any part of this thesis

nor the whole of the thesis has been submitted for a degree to any other University or

Institution. I certify that, to the best of my knowledge, my thesis does not infringe upon

anyone’s copyright nor violate any proprietary rights and that any ideas, techniques,

quotations, or any other material from the work of other people included in my thesis,

published or otherwise, are fully acknowledged in accordance with the standard referencing

practices. Furthermore, to the extent that I have included copyrighted material that

surpasses the bounds of fair dealing within the meaning of the Indian Copyright Act, I certify

that I have obtained a written permission from the copyright owner(s) to include such

material(s) in my thesis and have included copies of such copyright clearances to my

appendix. I declare that this is a true copy of my thesis, including any final revisions, as

approved by my thesis review committee. I also, attest that this thesis is free of plagiarism

of any kind and that I am fully aware of the Plagiarism Prevention Policy of Gujarat

Technological University, Ahmedabad.

Signature of candidate UTPAL VINODCHANDRA SHAH Enrollment No.: 139997119018 Date: Place: Ahmedabad

TABLE OF CONTENT Chapter No. Title Page No.

List of Tables………………………………………………………………. I

List of Figures……………………………………………………………… II

List of Abbreviations……………………………………………………. IV

1. Abstract 1

2. Solid waste management in Indian scenario 2

2.1 Objectives of the study 2 (a)

2.2 Scope of the work 2 (a)

2.3 Description of the research work 3

3. Design Methodology and Calculations 3

3.1 Design of Anchor Pin 4

3.2 Design Calculation of Hydraulic Cylinder 6

3.3 Design for pin joint 7

3.4 Design Calculation of Cross-Rod 8

3.5 Selection of Hoisting Chain Link for Container Lifting 9

3.5.1 Materials for chain link 10

4. Modelling and analysis of container lifting device 13

4.1 Dynamic Analysis of Container Lifting Device 13

4.1.1 Rigid dynamic analysis of CLD model 15

4.1.2 Transient dynamic analysis of CLD model 18

5. FFT Analyzer used for vibration measurement of hydraulic cylinder 26

5.1 VIBXPERT – FFT data collector and signal analyzer 26

6. Optimization in Hydraulic Cylinder Design 30

6.1 Single Objective Optimization Problem – Nonlinear Constrained 31

Minimization

Chapter No. Title Page No.

6.2 Multi Objective Optimization using Genetic Algorithm 33

6.3 Conclusion of optimization 40

7. Conclusion of Research work 41

7.1 Future scope of research work 43

REFERENCES 44

LIST OF PUBLICATIONS 50

I

LIST OF TABLES

Table No. Title of Table Page No.

Table 3.1 Grade 80 alloy chain standard by national association of 12

chain manufacturer

Table 4.1 Material and its property for individual component of CLD 14

Table 4.2 Joint applied to different pair of CLD component 14

Table 4.3 Analysis setting in rigid dynamic analysis of CLD model 15

Table 4.4 Rigid dynamic analysis setup for CLD model 16

Table 4.5 Value of translation joint force with respect to time 18

Table 4.6 Transient dynamic analysis setting 19

Table 4.7 Transient dynamic analysis setup of CLD model 19

Table 5.1 Typical measurements of RMS values 28

Table 6.1 Value of each variable Internal diameter (d), Thickness of Cylinder (t) 35

and Internal Pressure (p) after each iteration

Table 6.2 Value of each variable Internal diameter (d), Stress of Cylinder (s) 37


Table 6.3 Value of each variable internal diameter (d), Thickness of Cylinder (t) 39


Table 7.1 Comparison of results with allowable value 41

II

LIST OF FIGURES

Figure No. Title of Figure Page No.

Fig. 2.1 Process of solid waste management 2

Fig. 2.2 Truck mounted container lifting device 2 (a)

Fig. 3.1 Drawing of 4.5 CuM container used for CLD 4

Fig. 3.2 Drawing of anchor pin used in 4.5 CuM Container 4

Fig. 3.3 Cylindrical pin joints 8

Fig. 3.4 Drawing of Cross-rod used in CLD 8

Fig. 3.5 Model of chain link 10

Fig. 4.1 SolidWorks 3-D model of container lifting device 13

Fig. 4.2 Joints between individual components of CLD model 14

Fig. 4.3 Remote force, constrain, joint velocity, acceleration shown in CLD model 16

Fig. 4.4 Force shown on translation joint probe 17

Fig. 4.5 Translation joint force change with time 17

Fig. 4.6 Fine meshing of CLD model 18

Fig. 4.7 Time varying force applied on piston 19

Fig. 4.8 Time varying reaction force applied on cylinder 20

Fig. 4.9 Remote force, constrain, joint velocity, acceleration shown in CLD 20 model for transient analysis

Fig. 4.10 Von-Mises stress contour generated in CLD model 21

Fig. 4.11 Maximum Von-Mises stress generate in CLD model 21

Fig. 4.12 Maximum value of Von-Mises stress change with time 21

Fig. 4.13 Equivalent elastic strain contour generated in CLD model 22

Fig. 4.14 Maximum value of Equivalent elastic strain change with time 22

Fig. 4.15 Total deformation of CLD model 22

Fig. 4.16 Total deformation of CLD model with respect to time 23

Fig. 4.17 Cylinder- base total revolute joint probe force 23

Fig. 4.18 Time varying total cylinder- base revolute joint force 23

Fig. 4.19 Big link- base total revolute joint probe force 24

Fig. 4.20 Time varying total big link- base revolute joint force 24

Fig. 4.21 Big link- piston rod total revolute joint probe force 24

Fig. 4.22 Time varying total big link- piston rod revolute joint force 25

III

Figure No. Title of Figure Page No.

Fig. 4.23 Safety factor contour generate in CLD model 25

Fig. 4.24 Minimum time varying safety factor 25

Fig. 5.1 FFT spectrum of Hydraulic cylinder 28

Fig. 5.2 Some Photographs of actual readings taken of CLD by FFT analyser 30

Fig. 6.1 Optimization using MATLAB for the function: Minimization of 32

force value (f) exerted on piston

Fig. 6.2 Optimization using MATLAB for the function: Minimization of 33

Cross-sectional area (A) of the Hydraulic Cylinder

Fig. 6.3 Set of Non-inferior Solutions 34

Fig. 6.4 Pareto optimization using Genetic Algorithm plot of Stress 36 generated (N/mm2) v/s Force on Piston (N)

Fig. 6.5 Pareto optimization using Genetic Algorithm plot of Force (N) 38 v/s Thickness of Cylinder (mm)

Fig. 6.6 Pareto optimization using Genetic Algorithm plot of Force (N) 40 v/s Cross-sectional area of Cylinder (mm2)

IV

LIST OF ABBREVIATIONS

Sr. No. Abbreviations Meaning

1. MSWM Municipal Solid Waste Management

2. CLD Container Lifting Device

3. GUDC Gujarat Urban Development Corporation

4. HCV Heavy Commercial vehicles

5. LCV Light Commercial Vehicles

6. ISO International Organisation for Standardization

7. ULB Urban Local Bodies

8. FEA Finite Element Analysis

9. MATLAB Matrix Laboratory

10. WLL Working Load Limit

11. FFT Fast Fourier Transform

12. CFD Computational Fluid Dynamics

13. SWC Safe Working Capacity

1

1 Abstract

In all mega cities and municipal corporations, HCV chassis are used for loading and unloading

the containers having size more than 5.5 cubic meters. But for all towns and nagarpalikas, these

may not be preferred due to space limitations and narrow size roads. So in the case of towns

and nagarpalikas, tractor driven container lifting device may be used, which will lift up to 4.5

cubic meter containers. They can use containers of up to 4 - 4.5 cubic meters capacity, which

will make optimum use of the tractors. Even for more space limitations small containers

mounted on LCVs chassis can also be used.

It had been observed that mostly all municipal corporations are using 5.5 and 6 cubic meter

containers operated by a truck as the main source of waste collection and transportation. But

at ULBs, small towns and villages, it is very difficult to operate truck operated containers

because of following reasons:

1) Quantity of Solid waste to be handled is less as compare to Municipal Corporation.

2) Cost of truck operated container lifting device is also very high.

3) Narrow size of the roads and space limitations are also not allowing to use such solid

waste handling systems.

In this work, small container having capacity of 4.5 CuM is fabricated so that it can be operated

by tractor operated container lifting device. The idea was to design and develop new container

lifting device that can be used to handle 4.5 Cubic meter container which is to be operated by

tractor. As tractor is used to operate container lifting device, in the spare time it can be used to

operate trolleys, water tanker etc. at the Nagarpalikas. In short, tractor can be used to perform

multiple activities at Nagarpalika/ULB level. This combination can be made at less than half of

cost in comparison to the truck operated container lifting device.

The main focus of the research work is design and development of container lifting device that

can handle 4.5 Cubic meter container with the help of tractor. Work had been carried out for

design, failure analysis, vibration and FEA of various components of CLD, i.e. hydraulic cylinder,

link chain, different joints, cross bars, mechanical jack, leaf springetc. Hydraulic cylinder is the

2

most critical components of CLD, which is further optimized considering single and multi-

objective optimization problem using MATLAB.

The optimized design and modifications suggested in this work related to the CLD are

successfully implemented by GUDC and it is used in all ULBs in the state of Gujarat for solid

waste management. This CLD system is used to handle 4.5 Cubic meter container with the help

tractor to collect and transport municipal solid waste by various Nagarpalikas in Gujarat State.

2 Solid waste management in Indian scenario

Municipal Solid Waste Management (MSWM) is one of the major environmental problems of

Indian megacities. The MSWM system comprises five activities, i.e. waste generation,

collection, transportation, processing/treatment and disposal.

Fig. 2.1 Process of solid waste management[16]

For transport of solid waste the concerned authority authorities need to decide the type of

vehicles to be procured and the system of transportation to be adopted. If they use a

containerized system the vehicles needed may be calculated according to the number of

containers that will become full each day and the number of containers each container lifting

device will be able to take to the transfer station, treatment plant or disposal site[16].

Normally, one vehicle will be able to lift seven or eight containers if the distances to be

travelled are within 5 kilometers. The number of trips may be reduced to five or six if the

distance is between 5 and 10 kilometers, and it may be further reduced depending on the

distance travelled. In addition, 25 to 30 percent additional spare vehicles will be needed to

maintain reliability of service during breakdowns and during preventive maintenance of

vehicles.

Possibly vehicles are to be utilized in two shifts to ensure maximum benefits, better results and

optimum use of investment made.

2 (a)

Fig. 2.2 Truck mounted container lifting device

2.1 Objectives of the study:

The main Objective of this study is to design the container lifting device operated with

tractors or LCVs used for small towns.

To determine the feasibility of improving performance of container lifting device for

solid waste management.

To identify the problems/difficulties faced with the existing design/specifications of the

container lifting device.

To identify significant parameters affecting performance of the container lifting device.

To review existing design/specifications of container lifting device.

To establish the improved design/specifications of the container lifting device that will

overcome most of the problems related the performance parameters.

2.2 Scope of the work:

Feasibility assessment through survey based on questionnaires from end users and

manufacturers of container lifting device.

Problem identifications based on survey conducted.

Identification of critical parameters will be assessed based on literatures available,

technical talk with experts and self-assessment of the actual operations cycle of the

existing systems.

Analysis tool will be used to finalize the most favorable design.

3

2.3 Description of the research work:

The detailed survey work for the different container lifting device will be done in the

first phase. It covers study and analysis of existing container lifting device used for the

solid waste management.

In second phase problems during operations and maintenance will be identified from

the all data collected.

Actual need base analysis will be done according to the requirement of solid waste

management.

Based on the above analysis new improved optimum utilization and convenient design

will be suggested for easy operation and less maintenance.

The same design will be checked using software as well as it will be checked

experimentally under AMC, AUDA and GUDC.

3 Design Methodology and Calculations

Selection of container to be used with tractor operated container lifting device is based

on volumetric capacity. Size of container is minimized based on operation and

performance criteria.

After detailed study and analysis 4.5 Cubic meter container is selected for the operation.

It is to be fabricate with Mild Steel sheets with four top openings and one rear lockable

tailgate with heavy-duty hinges as per below mentioned technical specifications and

drawing.

The lifting hooks/anchor pins shall be integrated within the frame and be capable of

taking the specified load.

4

Fig. 3.1 Drawing of 4.5 Cubic meter container used for CLD

3.1 Design of Anchor Pin

Fig. 3.2 Drawing of anchor pin used in 4.5 Cubic meter Container

5

Bending moment equation in this case

........ . 3.1.1b

M YEq

I

,

b

Where

Bending stress

M Bending moment

Y Perpendicular distance between point of force and neutral axis

I Moment of inertia for circular cross section

2

250 /

2

yt

d Diameter of pin

S Yield strength of material N mm

FOS Factor of safety

Since there are four hook in the container for lifting purpose, so we divide the

maximum load of 5 ton by four to get the maximum load at single hook of container as

1.25 ton (12500 N).

Thus total force acting at single hook = 12500 N = 1.25 Ton

Using equation (3.1.1)

Where,

........ . 3.1.2yt

b

SEq

FOS

Using equation (3.1.1) and (3.1.2)

We get,

........ . 3.1.3yt

b

S M YEq

FOS I

Putting values in equation (3.1.3)

We get Diameter of pin, 39.39 40d mm mm

6

3.2 Design Calculation of Hydraulic Cylinder

ST52 is low carbon steel grade, excellent weldable, the most widely used steel grade

used for Hydraulic Cylinder Tubes. Normally supplied stressed relieved and

annealed or normalized. Hydraulic Cylinder Tubes ST52 and ST52.3 are found with excellent

machinability and weldability property. Supplied seamless, cold drawn & stress relieved

(BK+S), with yield strength over 520 MPa. The inside diameter is honed and oiled with the

tube ends capped for protection.[93]

ST52 Hydraulic Cylinder Tubes, applicable to machinery, hoists, automotive and transport

lifting equipment, waste disposal transport, food processing equipment, mechanical tools

and equipment, compressors and earth moving equipment etc. like hydraulic pressure,

pneumatic cylinder, oil pump barrel.

2

2 2

2

i

i

Pr essure RangeConsidered 160 to 200 kg / cm

200 9.81Pr essure,p N / mm 19.62 N / mm or MPa

100

Force,F Area,A Pr essure,p

5000 9.81 D 19.624

D 56.41mm 63mm

So, thediameter of piston rod is taken 63mmstandard.

The inside diameter is honed and oiled with the tube ends capped for protection.ISO

standard cylinder bore size is 32, 40, 50, 63, 80, and 100.

93

ult

ultt

For Hydrauliccylinder tube material issteel.

Hydraulic Cylinder Tube - ST52

Compressive/Tensile yieldstrength = 250MPa

Ultimate tensilestrength, = 520MPa

520104MPa

FOS 5

7

t ii

t i

O

i

O i

By Lame 's equation :

pD 63 104 19.62t 1 1

2 p 2 104 19.62

t 6.63 8 mm

By taking the ratioof externaldiameter of cylinder,D to

theint ernaldiameter of cylinder,D is1.75.

D 1.75 D 1.75 63 110 mm.

The piston rod size available with cylinder bore 110 mm is 63 mm.

2

cr 2

Buckling calculation for piston rod :

According to Euler 's equation,

n. .E.AP

L

K

cr

2

4

2

where, P Critical load (N) 5 ton 5000kg 49050 N

n end fixity coefficient

n 1 if both ends hinged

E 207000 N / mm

L 2900mm

.d

I d64K.dA 4

4

By putting all these values, weget d 45mm,

but in our caseint ernaldiameter is 63mm,henc

esafein buckling also.

3.3 Design for pin joint

Cylindrical pin joints are used in container lifting device mainly at three inter connection

between CLD base to hydraulic cylinders, hydraulic piston rod to big link and big link to

trailer base. Cylindrical pin joint are used to connect different component of CLD and help to

transmit motion between them. To sustain load and for proper functioning of CLD model it

is necessary to design cylindrical pin joint.

8

(A) (B) (C)

Fig. 3.3 Cylindrical pin joints

(A) base to hydraulic cylinders (B) hydraulic piston rod to big link (C) big link to trailer base.

For the design of the cylindrical pin, it can be fail in to double shear in loading condition.

Material selected for design of cylindrical pin is medium carbon steel.

P = 168000 N, y =400 MPa,

y = 400 * 0.58 = 232 MPa, F.O.S = 3

2

2

2

P P

A d

( A = )

2d = 2P

π y

FOS

d= 37.2 ≈ 40 mm

3.4 Design Calculation of Cross-Rod

Fig. 3.4 Drawing of Cross-rod used in CLD

9

3 4

32......

,

,

.(2.

4 1)1

.

bb

o

i

o

i

o

b

For hollow circular cross section

Where

Inside diameter of hollow shaft

Outside diameter of hollow shaft

MEq

d C

dC

d

d

d

M Bending moment

3.5 Selection of Hoisting Chain Link for Container Lifting

The chain is one of the most familiar for hoist as well as one of the most useful of

mechanical device. It is made up of a series of links fastened through each other. Each link is

made of a rod of wire bent into an oval shape and welded at one or two points. The weld

ordinarily causes a slight bulge on the side or end of the link. The chain size refers to the

diameter in millimetre (mm) of the rod used to make the link. Simple terms used with chain

are given below.

Working Load Limit (WLL)

The "Working Load Limit" (rated capacity) is the maximum load that shall be applied in

direct tension to an undamaged straight length of chain.

Proof Test

The "Proof Test" (manufacturing test force) is a term designating the minimum tensile force

which has been applied to a chain under a constantly increasing force in direct tension

24525 N

150 .

24525 150 24525 150 ( )

7357500 .

(

2

)

50

b

b

Assuming downward Load on pipe at a distance

of mm from fixed end from both side

We get force distance

M

N mm

Yield strength of mild steel MP and

M

a

...... .(4.1.5)

25083.3

,

33

4.1.4 4.1.5

0.8

115 =

yt

b

i o

Eq

After solving equation and we get

Outer diameter of hollow circular shaft is

Inner diameter of hollow circular shaf

SMPa

FOS

d Ct dis

115 mm

92mm

10

during the manufacturing process. These loads are manufacturing integrity tests and shall

not be used as criteria for service or design purposes.

Minimum Breaking Force

The "Minimum Breaking Force" is the minimum force at which the chain during

manufacture has been found by testing to break when a constantly increasing force is

applied in direct tension. This test is a manufacturer's attribute acceptance test and shall

not be used as a criterion for service or design purposes.

Overhead Lifting

That process of lifting that would elevate a freely suspended load to such a position that

dropping the load would present a possibility of bodily injury or property damage.

Overload

Any static or dynamic load is in excess of "Working Load Limit."

Fig.3.5 Model of chain link

3.5.1 Materials for chain link

Carbon chain

The selection of the base steel is left to the judgment of the individual chain

manufacturer provided the steel meets the following criteria: Carbon, 0.35% max.;

Phosphorous, 0.040% max.; and Sulphur, 0.050% max.

11

Alloy chain

The selection and amounts of the alloying elements in the steel are left to the judgment

of the individual chain manufacturer provided the steel meets the following criteria:

Carbon, 0.35% max.; Phosphorous, 0.035% max.; Sulphur, 0.040% max. Nickel must be

present in an alloying amount (0.40% min.), and at least one of the following elements

must be present in an alloying amount: Chromium (0.40% min.) or Molybdenum (0.15%

min.).

Stainless steel chain

The material shall be a 300 series austenitic stainless steel.

Now, selection of an open-link chain by using the following rule of thumb,

SWC = 28 D

SWC = Safe working capacity in tons

D = chain link diameter/thickness in inches

For a 5/8 “diameter chain link by using above equation,

SWC = 8× (5/8)2 = 3.125 tons

12

Table 3.1 Grade 80 alloy chain standard by national association of chain manufacturer [100]

Now according to loading situation of container while operation, chain link size should be

selected within working load limit of 8200 kg. So, as per the standard of National association

of chain manufactures for welded steel chain

Inside length (max) L = 51 mm

Inside width (min) E = 24 mm

Material diameter D = 16 mm = 5/8”

Working load limit (max) = 8200 kg

Min breaking force = 322 kN = 32834.86 kg

So we select the chain link from above table 4.1 for grade 80 alloy materials with 16 mm

diameter, inside width 24 mm and inside length of 51.2 mm.

4 Modelling and analysis of container lifting device

13

4.1 Dynamic Analysis of Container Lifting Device

Step 1) 3-D model of existing container lifting device build and assemble in SolidWorks 14.0

Fig. 4.1 SolidWorks 3-D model of container lifting device

Step 2)For perform Ansys dynamic analysis convert SolidWorks assembly file .SLDASM in to

Ansys .STEP file.

Step 3) Assign material property to each and every individual parts of container lifting

device.

Material and it’s property

Component of CLD modal

Hydraulic

cylinder

Piston

rod

Cross-rod Big link Base

Material ST 52 SAE 1045 S 355

Density (Kg/m3) 7800 7872 7800

Tensile Yield stress(Pa) 520 310 355

Compressive yield stress (Pa) 520 310 355

Ultimate stress (Pa) 900 565 470 - 630

Young’s Modulus (GPa) 200 200 210

Poisson's Ratio 0.3 0.29 0.3

14

Bulk Modulus (GPa) 167 158 175

Shear Modulus (GPa) 77 77.5 80.7

Table 4.1 Material and its property for individual component of CLD

Step 4) Generate geometry in ansys and give adequate connection between parts to

allowed motion like body to body or body to ground. In CLD model connection or joint

applied between parts are as follows…

Object name Type of joint Type of connection

Ground to base Fixed Body to ground

base to cylinder Revolute Body to body

cylinder to piston Translation Body to body

piston to big link Revolute Body to body

big link to base Revolute Body to body

cross rod to big link Fixed Body to body

Table 4.2 Joint applied to different pair of CLD component

Fig. 4.2 Joints between individual components of CLD model

15

4.1.1 Rigid dynamic analysis of CLD model

For rigid parts, the following conditions apply:

Line bodies cannot be set to rigid.

Multibody parts must have all bodies set to rigid.

Density is the only material property needed to calculate mass properties. All other

material specifications will be ignored.

An “Inertial Coordinate System” will automatically be defined at the centroid of the

part

Rigid bodies are rigid, so no stresses, strains, or relative deformation is calculated.

Hence, no mesh is required

Step 5) In Analysis setting number of step taken is one with end time is 60s.

Number Of Steps 1

Current Step Number 1

Step End Time 60. s

Auto Time Stepping on

Initial Time Step 1.e-002 s

Minimum Time Step 1.e-007 s

Maximum Time Step 5.e-002 s

Time Integration Type Runge-Kutta 4

Relative Assembly Tolerance on

Store Results At All Time Points

Table 4.3 Analysis setting in rigid dynamic analysis of CLD model

Step 6) In Rigid dynamic analysis CLD model setup like load, velocity, displacement etc.are

given below.

16

Table 4.4 Rigid dynamic analysis setup for CLD model

Fig. 4.3 Remote force, constrain, joint velocity, acceleration shown in CLD model

Step7) Aim to perform rigid dynamic analysis is to find out force generate at different joint

probe and working behaviour of model in 3-D space. After completion of solution result are

found are as follows.

Analysis setup Object name Value

Acceleration All body 9.8 m/s2 in global C. S. +y axis

Remote force Cross- rod 25000 N in global C. S. –y axis

Joint velocity Cylinder- piston pair 20 mm/s in reference C. S. +x axis

Remote

displacement

Cylinder, piston, big link 1) x displacement is 0 mm

2) rotation in y and z axis is 00

17

Fig. 4.4 Force shown on translation joint probe

Fig. 4.5 Translation joint force change with time

-2.00E+05

-1.50E+05

-1.00E+05

-5.00E+04

0.00E+00

5.00E+04

1.00E+05

1.50E+05

0 10 20 30 40 50 60 70

Forc

e (N

)

Time (Sec.)

18

Second Force(N) Second Force(N) Second Force(N)

0 1.12E+05 21 -7547.7 41 -60160

1 90991 22 -10081 42 -63323

2 76687 23 -12589 43 -66595

3 65865 24 -15079 44 -69992

4 57219 25 -17557 45 -73526

5 50034 26 -20029 46 -77218

6 43884 27 -22625 47 -81088

7 38497 28 -24978 48 -85161

8 33688 29 -27467 49 -89467

9 29330 30 -29971 50 -94043

10 25327 31 -32496 51 -98932

11 21611 32 -35047 52 -1.04E+05

12 18128 33 -37630 53 -1.10E+05

13 14837 34 -40250 54 -1.16E+05

14 11704 35 -42913 55 -1.23E+05

15 8703 36 -45624 56 -1.31E+05

16 5811.6 37 -48391 57 -1.39E+05

17 3011.7 38 -51220 58 -1.50E+05

18 288.1 39 -54118 59 -1.61E+05

19 -2372.4 40 -57095 60 -1.76E+05

20 -4981

Table 4.5 Value of translation joint force with respect to time

4.1.2 Transient dynamic analysis of

CLD model

Step5) Meshing is to be done by

automatic generate mesh option with

element shape used was tetrahedral.

Total numbers of element is 33790

with numbers of node is 69041.

Fig. 4.6 Fine meshing of CLD model

19

Step 6) In Analysis setting number of step taken is one with end time is 60s.

Number Of Steps 1

Current Step Number 1

Step End Time 60. s

Auto Time Stepping on

Initial Time Step 0.1 s

Minimum Time Step 0.1 s

Maximum Time Step 0.1 s

Time Integration on

Newton Raphson option Program control

Store Results At All Time Points

Table 4.6 Transient dynamic analysis setting

Step 7)In transient dynamic analysis CLD model setup like load, velocity, displacement etc.

are given below.

Table

4.7Transient dynamic analysis setup of CLD model

-200000

-150000

-100000

-50000

0

50000

100000

150000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61

Analysis setup Object name value

Acceleration All body 9.8 m/s2 in global C. S. +y

Remote force Cross- rod 25000 N in global C. S. -y

Joint velocity Cylinder- piston pair 20 mm/s in reference C. S. +x

20

Fig. 4.7 Time varying force applied on piston

Fig. 4.8 Time varying reaction force applied on cylinder

Fig. 4.9 Remote force, constrain, joint velocity, acceleration shown in CLD model for

transient analysis

Step 8) Aim to perform transient dynamic analysis is to find out time-history charts to

understand the transient response of the system. Like time varying stress, strain,

acceleration, joint force and moment etc. After completion of solution result are found are

as follows.

-150000

-100000

-50000

0

50000

100000

150000

200000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61

21

Fig. 4.10 Von-Mises stress contour generated in CLD model

Fig. 4.11 Maximum Von-Mises stress generate in CLD model

Fig. 4.12 Maximum value of Von-Mises stress change with time

0.00E+00

2.00E+07

4.00E+07

6.00E+07

8.00E+07

1.00E+08

1.20E+08

1.40E+08

1.60E+08

1.80E+08

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0

VO

N-

MIS

ES S

TRES

S (P

A)

TIME (SEC.)

22

Fig. 4.13 Equivalent elastic strain contour generated in CLD model

Fig. 4.14 Maximum value of Equivalent elastic strain change with time

Fig. 4.15 Total deformation of CLD model

0.00E+00

1.00E-04

2.00E-04

3.00E-04

4.00E-04

5.00E-04

6.00E-04

7.00E-04

8.00E-04

9.00E-04

1.00E-03

0 10 20 30 40 50 60 70

Vo

n-

mis

es S

trai

n (

m/m

)

Time (Sec.)

23

Fig. 4.16 Total deformation of CLD model with respect to time

Fig. 4.17 Cylinder- base total revolute joint probe force

Fig. 4.18 Time varying total cylinder- base revolute joint force

0.00E+00

5.00E-01

1.00E+00

1.50E+00

2.00E+00

2.50E+00

3.00E+00

3.50E+00

4.00E+00

4.50E+00

0 10 20 30 40 50 60 70

DIS

PLA

CEM

ENT

(M)

TIME (SEC.)

0.00E+00

2.00E+04

4.00E+04

6.00E+04

8.00E+04

1.00E+05

1.20E+05

1.40E+05

1.60E+05

1.80E+05

0 10 20 30 40 50 60 70

Tota

l Fo

rce

on

Jo

int

(N)

Time (Sec.)

24

Fig. 4.19 Big link- base total revolute joint probe force

Fig. 4.20 Time varying total big link- base revolute joint force

Fig. 4.21 Big link- piston rod total revolute joint probe force

0.00E+00

2.00E+04

4.00E+04

6.00E+04

8.00E+04

1.00E+05

1.20E+05

1.40E+05

1.60E+05

1.80E+05

0 10 20 30 40 50 60 70

Tota

l Fo

rce

on

Jo

int

(N)

Time (Sec.)

25

Fig. 4.22 Time varying total big link- piston rod revolute joint force

Fig. 4.23 Safety factor contour generate in CLD model

Fig. 4.24 Minimum time varying safety factor

0.00E+00

2.00E+04

4.00E+04

6.00E+04

8.00E+04

1.00E+05

1.20E+05

1.40E+05

1.60E+05

1.80E+05

0 10 20 30 40 50 60 70

Tota

l Fo

rce

on

Jo

int

(N)

Time (Sec.)

0

1

2

3

4

5

6

0 10 20 30 40 50 60 70

Saft

ey F

acto

r

Time (Sec.)

26

Static Analysis of Leaf Spring and mechanical jack had been carried out with help of

SolidWorks 14.0. Stress analysis and FEA results in both cases are found satisfactory.

5 FFT Analyzer used for vibration measurement of hydraulic cylinder:

Hydraulic cylinders are one of the most important components of the hydraulic systems

used in a different industrial application. Design of a hydraulic cylinder consists of a different

loading and boundary conditions. Vibration of the cylinder during working condition is one

of the most crucial elements of the failure criterion. In the container lifting device operated

by tractor, the most critical part is two hydraulic cylinders of 5 ton capacity. It would be very

important to optimize the dynamic characteristics of hydraulic cylinders, because on the

case of they will have to carry out the operation with huge weight inertia. During the

analysis, the dynamic characteristics of hydraulic cylinders are obtained by using the Time

Capture Analysis and Real-time FFT, which is equipped on the container lifting device with

tractor used for solid waste management.

5.1 VIBXPERT – FFT (Fast Fourier Transform) data collector and signal analyzer:

• As the double acting hydraulic cylinder is most important element for container

lifting device.

• Actual run for measurement of vibrations for the same element at different 14

stages of lifting and lowering the empty and loaded 4.5 Cubic meter container with

container lifting device.

• Thus the vibrations of double acting hydraulic cylinder were measured taking the

different 14 stages readings. Out of that four samples are shown as under:

27

1) Empty container lifting acceleration spectrum

2) Loaded container lifting position 3 acceleration spectrum

3) Loaded container lifting position 4 displacement spectrum

28

4) Loaded container emptying position 8 velocity spectrum

Fig. 5.1 FFT spectrum of Hydraulic cylinder

Table 5.1 Typical measurements of RMS values

RMS Values

Sr. No.

Description Displacement (µm)

Velocity (mm/sec)

Acceleration (m/sec2)

1 Empty container lowering rest 10.05 1.01 0.193

2 Empty container lowering Vertical

24.38 2.42 0.271

3 Empty container lowering down 54.74 5.86 0.581

4 Empty container lifting 31.31 3.18 0.298

5 Loaded container lifting 1 26.15 3.20 0.349




9 Loaded Container Emptying 5 41.04 4.43 0.476






29

During actual working on CLD with FFT analyzer, vibration analysis of the hydraulic cylinder

under variable loading application and different boundary conditions is obtained. The main

cause of the vibration in hydraulic cylinder is stick-slip phenomenon between piston and

cylinder which is also responsible for the failure of a sealing material and reduces the fatigue

life as well the performance of the hydraulic system. Vibration analysis can be done by

static, dynamic and transient way. The Mode Superposition Method of a transient dynamic

analysis is one of the most important methods to predict mode shapes. All readings taken

were checked with the standard given and they are all falls within the limit hence it is

proved that hydraulic cylinders performance is safe in vibration.

30

Fig. 5.2 Some Photographs of actual readings taken of CLD by FFT analyser

6 Optimization in Hydraulic Cylinder Design

Monotonicity and dominance were used to find general principles for designing hydraulic

cylinders optimal for a wide class of objective functions and stress conditions. The design

method, although guaranteed to give the optimum design.

Optimal cylinders should be designed for minimum force. Only two designs can be

optimal—one with maximum pressure and minimum wall thickness; the other with

maximum stress.[102]

In the former case, the design is retained if and only if the stress is less than allowable.

Otherwise, a one-variable search in a restricted interval is needed. The results suggest the

potential importance of monotonicity and dominance in identifying the critical constraints in

a design.

Here we have taken six design variables,

(1) Inside diameter, d x(1) (2) Wall thickness, t x(2) (3) Material Stress, s (4) Force, f (5) Oil Pressure, p x(3) (6) Cross-sectional area of hydraulic cylinder, A

31

First Optimum design will be with maximum pressure and minimum wall thickness, second with maximum stress. Subject to

2 2

, 7

, 5 5000 49050

, 200 / 19.62 /

Wall thickness t mm

Force f ton so kg N

Pressure p kg cm say N mm

There are three physical relations: First relates force, pressure and area.

2

4f d p

The second gives the wall stress,

2

p ds

t

Also to find Cross-sectional area of hydraulic cylinder:

Cross-sectional area,

2

2

. . .

.

A d t t

A d t t

6.1 Single Objective Optimization Problem – Nonlinear Constrained Minimization

Optimization Toolbox provides widely used algorithms for standard and large-scale

optimization. These algorithms solve constrained and unconstrained continuous and

discrete problems. The toolbox includes functions for linear programming, quadratic

programming, binary integer programming, nonlinear optimization, nonlinear least squares,

systems of nonlinear equations, and multi-objective optimization. These can be used to find

optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and

incorporate optimization methods into algorithms and models.

Using MATLAB 2012 following eight examples were created and solved related to

optimization and design hydraulic cylinder to be used for container lifting device, out of

these results for two examples are shown below:

32

Example 6.1 app2 -- Minimize the force, f

The iteration table in the command window shows how MATLAB searched for the minimum

value of force function in the unit disk. This table is the same whether to be used as

Optimization Tool or the command line. MATLAB reports the value of three variables (i.e.

internal diameter (d), cylinder wall thickness (t), pressure (p) and minimization of force, (f)

as below:

Output

x = 57.0000 7.0000 19.6200

fval = 5.0040e+04

Fig.6.1 Optimization using MATLAB for the function : Minimization of force value (f)

exerted on piston

Example 6.2

app16 – Minimization of cross-sectional area

Again the iteration table in the command window shows how MATLAB searched for the

minimum value of cross-sectional area function in the unit disk. This table is the same

whether to be used as Optimization Tool or the command line. MATLAB reports the value of

three variables (i.e. internal diameter (d), cylinder wall thickness (t), pressure (p) and

minimization of cross-sectional area, (A) as below:

Output

x = 50.0000 7.0000 16.0707

fval = 1.2529e+03

33

Fig.6.2 Optimization using MATLAB for the function : Minimization of Cross-sectional area

(A) of the Hydraulic Cylinder

6.2 Multi Objective Optimization using Genetic Algorithm

In many engineering disciplines we need to find solutions in the presence of conflicting

objectives. In such cases, solutions are chosen such that there are reasonable trade-offs

among different objectives. In certain problems, it may not be obvious that the objectives

are not conflicting to each other. In such combinations of objectives, the resulting Pareto-

optimal set will contain only one optimal solution. Pareto search is an approach for handling

such situations. Instead of generating a single optimal solution, many solutions are

generated that satisfy Pareto Optimality Criterion. According to this criterion, a solution

point P is accepted only if there are no solutions better than P with respect to all the

objectives. For example, even if P is worse than another solution P1 with respect to one

objective, P is accepted provided that it is better than P1 in at least one objective. Thus each

Pareto optimal solution is good in some respect. The set of all Pareto optimal solutions form

a surface known as a Pareto front. The Pareto front helps engineers understand the nature

of trade-offs that need to be made in order to select good solutions. Visualizing the front

helps engineers make good decisions.[62]

Definition: Point x is a non-inferior solution if for some neighbourhood of x there

does not exist a x such that x x and

, 1,...., ,

.

i i

j j

F x x F x i m and

F x x F x for at least one j

In the two-dimensional representation of Figure 4 the set of noninferior solutions lies on the

curve between C and D. Points A and B represent specific noninferior points.

34

Fig.6.3 Set of Non-inferior Solutions

A and B are clearly noninferior solution points because an improvement in one objective, F1,

requires a degradation in the other objective, F2, i.e. , 1 1 2 2, .B A B AF F F F

Since any point in that is an inferior point in which improvement can be attained in all

the objectives, it is clear that such a point is of no value.

Multi-objective optimization is, therefore, concerned with the generation and selection of

noninferior solution points.

Noninferior solutions are also called Pareto optima. A general goal in multi-objective

optimization is constructing the Pareto optima.

Using MATLAB 2012 ten different examples were created and solved related to multi-

objective optimization and design hydraulic cylinder to be used for container lifting device,

out of these results for following three examples are shown.

Example 6.3 app9 -- Multi objective Optimization, Pareto Optimization, Maximize the stress, s & Minimization of force, f linked with mymulti4.m. [d = x(1), t = x(2) and p = x(3)] App9

options = gaoptimset('PopulationSize',60,... 'ParetoFraction',0.7,'PlotFcns',@gaplotpareto); [xfval flag output population] = gamultiobj(@mymulti4,3,... [],[],[],[],[55,7,15.696],[70,15,19.62],options)

mymulti4.m function f = mymulti4(x)

35

f(1) = -x(3)*x(1)/(2.0*x(2)); f(2) = 0.785*x(1)^2*x(3);

Sr. No.

Internal Diameter, d, x(1) in

mm

Thickness of

Cylinder, t, x(2) in mm

Internal Pressure, p,

x(3) in N/mm2

Sr. No.

Internal Diameter, d, x(1) in mm

Thickness of Cylinder, t, x(2) in mm


x(3) in N/mm2

1 55.0000 7.0000 15.6960

31 55.0000 7.0000 15.6960

2 66.2678 7.0059 19.5723

32 58.3710 7.0075 19.4684

3 55.0000 7.0000 15.6960

33 55.8222 7.0116 19.4376

4 55.0000 7.0000 15.6960

34 64.7664 7.0126 19.4935

5 62.4450 7.0580 19.4929

35 62.5167 7.0069 19.5045

6 60.4970 7.0069 19.5850

36 55.7202 7.0073 18.6119

7 60.1910 7.0055 19.4753

37 63.0392 7.0155 19.5742

8 64.0234 7.0124 19.5256

38 65.2111 7.0204 19.5760

9 55.0613 7.0047 18.4560

39 64.4622 7.0227 19.5644

10 55.1285 7.0795 16.5295

40 59.3725 7.0063 19.4064

11 55.1080 7.0361 16.1410

41 66.3172 7.0970 19.4580

12 61.5908 7.0063 19.4276

42 60.1721 7.0188 19.1510

13 55.5851 7.0042 17.1733

43 56.3911 7.0056 19.4793

14 58.2347 7.0028 19.5183

44 59.6663 7.0058 19.0352

15 55.1813 7.0154 18.4295

45 55.1911 7.0041 16.6825

16 57.9182 7.0066 19.5054

46 61.1807 7.0069 19.5383

17 64.9375 7.0077 19.5621

47 61.8250 7.0066 19.5524

18 66.0774 7.0193 19.4926

48 65.9791 7.0154 19.5238

19 65.4093 7.0061 19.5791

49 56.3966 7.0052 19.5736

20 55.3754 7.0041 18.4095

50 55.0618 7.0129 18.2643

21 58.5363 7.0245 19.5747

51 55.4177 7.0050 19.1041

22 62.7189 7.0064 19.5771

52 57.7819 7.0059 19.4920

23 57.4923 7.0119 19.4306

53 55.0702 7.0042 16.4860

24 63.2921 7.0069 19.4777

54 66.2678 7.0059 19.5723

25 55.7036 7.0036 16.5999

55 55.1476 7.0629 17.2362

26 56.2273 7.0055 19.4126

56 55.1774 7.0132 17.7655

27 61.5269 7.0458 19.3891

57 55.0156 7.0000 15.6960

28 55.7098 7.0088 19.3550

58 55.0963 7.0109 19.4399

29 63.4252 7.0314 19.5727

59 61.5894 7.1083 19.5141

30 55.3446 7.0098 17.8110

60 60.5595 7.1319 19.5850

Table 6.1 Value of each variable Internal diameter (d), Thickness of Cylinder (t) and Internal

Pressure (p) after each iteration

36

Fig.6.4 Pareto optimization using Genetic Algorithm plot of Stress generated (N/mm2) v/s

Force on Piston (N)

Example 6.4

app6 -- Multiobjective Optimization, Pareto Optimization, Maximize the force, f& Minimization of thickness, t linked with mymulti1.m. [d = x(1), s = x(2) and p = x(3)]

App6

options = gaoptimset('PopulationSize',60,... 'ParetoFraction',0.7,'PlotFcns',@gaplotpareto); [xfval flag output population] = gamultiobj(@mymulti1,3,... [],[],[],[],[55,80,15],[80,92,19.62],options)

mymulti1.m

function f = mymulti1(x) f(1) = -0.785*x(1)^2*x(3); f(2) = x(3)*x(1)/(2.0*x(2));

37

Sr. No.


mm

Stress of Cylinder, s,

x(2) in N/mm2


x(3) in N/mm2

Sr. No.


Stress of Cylinder, s,

x(2) in N/mm2


x(3) in N/mm2

1 55.0078 91.6168 15.0018

31 69.1143 91.7195 15.1666

2 79.9919 91.7703 19.6176

32 59.2841 91.8107 15.5315

3 79.9919 91.7547 19.6176

33 79.7091 91.7845 16.0754

4 79.2017 91.7932 16.5609

34 79.8247 91.7922 17.2598

5 55.0078 91.6480 15.0018

35 65.0814 91.7806 15.2036

6 55.0078 91.6793 15.0018

36 79.6472 91.7693 16.2253

7 79.9694 91.8333 19.3448

37 57.2698 91.7542 15.1802

8 79.8608 91.7727 15.8229

38 79.6972 91.7660 18.5507

9 66.3763 91.7202 15.1005

39 61.4632 91.7095 15.1355

10 76.0792 91.7928 15.0875

40 62.8751 91.6910 15.1317

11 79.4116 91.7394 17.0860

41 55.0078 91.6793 15.0018

12 79.8643 91.8274 19.0110

42 57.5984 91.7088 15.0473

13 63.2734 91.7015 15.0096

43 78.8803 91.7897 15.8159

14 79.8288 91.7790 17.8853

44 68.5697 91.7179 15.2937

15 65.0628 91.7493 15.2036

45 79.1919 91.7576 17.0069

16 64.9417 91.6681 15.0416

46 59.2251 91.6635 15.1759

17 77.6260 91.7956 15.2363

47 78.6092 91.7721 17.4948

18 67.0868 91.7160 15.3411

48 73.1853 91.7286 15.5022

19 70.5506 91.6568 15.0636

49 76.8068 91.7216 15.4737

20 75.3182 91.7606 15.3205

50 75.4550 91.8006 15.3853

21 67.3269 91.7229 15.0905

51 68.5267 91.7862 15.0148

22 79.3568 91.7997 16.7358

52 78.1924 91.7886 15.5452

23 79.6428 91.7405 18.5703

53 79.9295 91.7737 19.3981

24 79.9240 91.8879 17.5826

54 72.4331 91.7462 15.4561

25 79.9256 91.8502 18.3170

55 79.7663 91.7790 17.8853

26 77.3328 91.8284 15.1115

56 70.4219 91.7718 15.4908

27 72.7814 91.7847 15.0560

57 79.9240 91.8254 17.5826

28 79.8332 91.8116 18.7950

58 63.2734 91.6390 15.0643

29 59.9086 91.7026 15.4638

59 55.0586 91.7418 15.0018

30 56.6810 91.7107 15.0201

60 79.5994 91.7578 15.6826

Table 6.2 Value of each variable Internal diameter (d), Stress of Cylinder (s) and Internal


38

Fig.6.5 Pareto optimization using Genetic Algorithm plot of Force (N) v/s Thickness of

Cylinder (mm)

Example 6.5

app17 -- Multiobjective Optimization, Pareto Optimization, Maximize the force, f& Minimization of cross-sectional area,Alinkedwith mymulti17.m. [d = x(1), t = x(2) and p = x(3)] options = gaoptimset('PopulationSize',60,... 'ParetoFraction',0.7,'PlotFcns',@gaplotpareto); [xfval flag output population] = gamultiobj(@mymulti17,3,... [],[],[],[],[55,07,15.696],[70,16,19.62],options)

mymulti17.m

function f = mymulti17(x) f(1) = -0.785*x(1)^2*x(3); f(2) = 3.14*((x(1)*x(2)+x(2)^2));

39

Sr. No.


mm

Thickness of

Cylinder, t, x(2) in mm


x(3) in N/mm2

Sr. No.


Thickness of Cylinder, t, x(2) in mm


x(3) in N/mm2

1 55.0000 7.0000 16.0085

31 55.4372 7.0396 19.2665

2 69.9987 7.0283 19.6200

32 65.5574 7.0109 19.6028

3 69.9987 7.0127 19.6200

33 55.9352 7.0152 19.5074

4 57.6986 7.0018 19.5913

34 55.3623 7.0012 18.9455

5 55.0031 7.0002 18.8725

35 63.8330 7.0108 19.3648

6 63.5562 7.0312 19.5854

36 69.6822 7.0121 19.6186

7 55.0000 7.0000 17.5416

37 64.9928 7.0043 19.5858

8 55.0000 7.0000 16.0085

38 65.8195 7.0137 19.6042

9 55.0000 7.0000 16.0241

39 60.3892 7.0092 19.5858

10 55.0000 7.0000 16.9024

40 59.5785 7.0034 19.2825

11 55.0031 7.0012 18.8725

41 61.5670 7.0146 19.6042

12 56.7591 7.0100 19.6194

42 57.3518 7.0055 19.4248

13 69.2413 7.0112 19.6099

43 65.6511 7.1359 19.6028

14 68.5541 7.0106 19.5913

44 55.1262 7.0001 18.3711

15 56.3311 7.0160 19.5552

45 59.4147 7.0100 19.4629

16 55.0000 7.0000 16.3537

46 58.3674 7.0041 19.2737

17 69.9987 7.0225 19.6200

47 55.2397 7.0133 19.3382

18 61.9767 7.0049 19.6109

48 62.2097 7.0236 19.4095

19 69.9987 7.0127 19.6200

49 63.2301 7.0185 19.6084

20 66.5631 7.0163 19.6021

50 60.8089 7.0126 19.6011

21 59.7798 7.0104 19.6011

51 57.7745 7.0087 19.3398

22 55.0012 7.0001 18.3711

52 59.3529 7.0099 19.3541

23 62.3718 7.0077 19.4629

53 68.9767 7.0144 19.5854

24 63.9051 7.0162 19.6023

54 56.8451 7.0144 19.5399

25 67.5167 7.0110 19.4657

55 67.1126 7.0062 19.5764

26 60.9584 7.0099 19.3632

56 67.1009 7.0032 19.5319

27 55.0000 7.0000 17.0923

57 55.7167 7.0280 19.4999

28 67.5035 7.0199 19.6129

58 62.8502 7.0158 19.6097

29 68.0485 7.0104 19.6050

59 57.6018 7.0055 19.4248

30 58.8005 7.0098 19.2952

60 66.5631 7.0163 19.3521

Table 6.3 Value of each variable internal diameter (d), Thickness of Cylinder (t) and Internal


40

Fig. 6.6 Pareto optimization using Genetic Algorithm plot of Force (N) v/s Cross-sectional

area of Cylinder (mm2)

6.3 Conclusion of optimization

Most real-world search and optimization problems are naturally posed as multi-objective

optimization problems. However, due to the complexities involved in solving multi-objective

optimization problems and due to the lack of suitable and efficient solution techniques, they

have been transformed and solved as single objective optimization problems. Moreover,

because of the presence of conflicting multiple objectives, a multi-objective optimization

problem results in a number of optimal solutions, known as Pareto-optimal solutions. One

major drawback in of developing Pareto-optimal plots is the extensive calculation required

to obtain the complete curve. Hence MATLAB is used to overcome such problems.

Pareto optimization is a methodology for solving multicriteria decision problems. This

methodology provides a systematic approach towards design problems with multiple

conflicting objectives. In Pareto optimal design situations, the designer has more than one

performance measure of interest. An optimal solution is generally defined as the best

41

solution. However, with multicriteria problems, the "best" is often dependent upon a

designer's preferences. The Pareto optimization methodology usually generates a large

number of alternatives which the designer evaluates in order to arrive at his best solution

often termed the best compromise solution.

7 Conclusion of Research work

Container lifting device for maximum load carrying capacity about 5000 Kg and that can

handle container about 4 to 4.5 m3 is designed. To find its behavior in dynamic environment

rigid and transient structure dynamic analysis has been carried out. Results of analysis are

discussed and suggested modifications in CLD to eliminate operational issues and improving

its performance. From the above work final conclusions are derived asunder:

1) As per the dynamic analysis of CLD model, results of Von-Mises stress and strain, safety

factor etc. are found much below then allowable values. Comparison is given below.

Component Result Maximum value

generated

Allowable

value

Safety factor

during design

Safety factor

in Ansys result

Piston rod Stress 64.5 MPa 310 MPa 3 4.7

Cross- rod Stress 52 MPa 355 MPa 3 6.8

Big link Stress 169 MPa 355 MPa - 2.2

Base Stress 129 MPa 355 MPa - 2.8

Piston Stress 30 MPa 310 MPa 3 10

All body Strain 0.00086 0.002

Table 7.1 Comparison of results with allowable value

So, from the table it is found that maximum stress and strain generated during operation

of CLD model at maximum load is within prescribed limit.

2) As per the static analysis of leaf spring, simulated in Ansys 15, at design load maximum

stress generated is found 813 MPa, which is less than 1800 MPa (yield stress) with safety

factor of 2 considered in design. That indicate design is safe under working condition.

3) As per the static analysis of mechanical jack, simulated in Ansys 15, at design load

maximum stress generated is found nearly 90 MPa which is less than 170 MPa (yield

stress) with safety factor of 3 considered in design. That indicate design is safe under

working condition.

42

4) In single objective optimization problem, objective function is minimizing the force or

cross-sectional area or thickness of cylinder, in which inside diameter (d) is the only

variable. The objective function is monotonic with respect to its variable (i.e. inside

diameter, d). Hence single objective optimization is not much suitable in this case, in

addition to the variable inside diameter (d, pressure (p) and thickness (t) are also active,

so multi-objective optimization is carried out.

Multi-objective optimization problem results in a number of optimal solutions, known as

Pareto-optimal solutions. The Pareto-optimal curves of (a) Maximization of stress &

minimization of force (variables are d, t, p) (b) Maximization of force & minimization of

thickness (design variables are d, s, p) and (c) maximization of force & minimization of

cross sectional area of cylinder (variables are d, t, p) are obtained. These Pareto-optimal

curves are useful to obtain different values of design variables for different cross

sectional area of cylinder, force on piston and stress generated.

5) After review of existing design/specifications of container lifting device, significant

parameters affecting performance of the container lifting device were identified.

Following modifications are also suggested on existing device which can eliminate major

difficulties faced during operation.

Two front support added to container lifting device for proper positioning and

placing of container and remains at its position while transportation.

Four side supports is provided to prevent the damage of hydraulic cylinder and oil

pipes.

Two rear mechanical jacks added to container lifting device for proper support and

stabilized the vehicle.

Side wall added to container lifting device to prevent the fall of waste directly from

container to ground.

Proper positioning and placing of hydraulic pipes.

43

7.1 Future scope of research work

After doing this research work there are also some future work may possible for

improvement in performance of container lifting device.

Further performance investigation of CLD model by changing different hydraulic fluid

during operation.

Computational fluid dynamic (CFD) analysis of double acting hydraulic cylinder to

analyse the performance of CLD model at different hydraulic fluid.

Effects of Vibration on fatigue life of hydraulic cylinders and seals can be evaluated.

Optimization of Cycle time by providing external hydraulic power pack may be

evaluated.

44

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50

LIST OF PUBLICATIONS

1 Prof. U. V. Shah, HimanshuRaiyani, Vijay Mistry "Municipal solid waste management in Indian cities – A review" in 2nd national conference on emerging trends in engineering technology & management at Indus institute of technology & engineering

2 Prof. U. V. Shah, HimanshuRaiyani, Vijay Mistry "Scenario of Municipal Solid Waste Management in India – A Review" in National Conference on ‘Transportation and Water resource Engineering” (NCTWE – 2015) at L. D. College of Engineering, Ahmedabad

3 Prof. U. V. Shah, Himanshu D. Raiyani, Prof. G. H. Upadhyay "Design and Dynamic analysis of existing container lifting device used for Solid Waste Management" in International Journal for Scientific Research and Development (IJSRD),Vol. 3, Issue 03, 2015, ISSN: 2321-0613

4 Prof.U.V.Shah, Dr. G. H. Upadhyay, "Optimization of Hydraulic Cylinder Design used for container lifting device using Genetic Algorithm" in International Journal of Engineering and Techniques (IJET), ISSN: 2395-1303, Volume 4 Issue 1 – 2018.

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