evaluation of granular fertilizer boom sprayer

i

EVALUATION OF GRANULAR FERTILIZER BOOM SPRAYER

PERFORMANCE VIA COMPUTATIONAL SIMULATION

AHMAD FARIQIN B. ABD MALEK

A thesis is submitted of the fulfillment of the requirements

For the award of the Degree of Master of Mechanical

Engineering

FACULTY OF MECHANICAL AND MANUFACTURING ENGINEERING

UNIVERSITY TUN HUSSIEN ONN MALAYSIA

JUNE 2015

v

ABSTRACT

Granular boom sprayer has been used by large scaled farmers for centuries. This

machine is used to repel or fertilize their crops. In MARDI, they used 3 types of

fertilizer that is Nitrogen, N, Phosphorus, P and Potassium, K. Those 3 types of particles

have been simulated by using Ansys software and the results show that potassium, K

fertilizer not scattered to the ground and the others 2 fertilizers are conversely. The

uniformity of the distribution of granular fertilizer was carried out with a reasonable

range of variables. Various methods have been used to study the efficiency of the spray

boom design on through simulation software and lab approach. In this work, the

simulation of the particles in the boom sprayer is performed from the boom sprayer

entering until the exit and distributed to the ground. The simulation is performed by

using ANSYS CFX based on the Taguchi method. Taguchi method have been used in

this study. For the orthogonal array, since this case study consists of 4 level and 5 factor,

L‟16 was used for the simulation process. This simulation utilize only one fertilizer that

contained all types of the basic NPK fertilizer. The parameters are involved the granular

diameter size, air velocity at the inlet, blow head distance, height of collecting plate and

width of collecting plate. Results shows that the air velocity must be kept higher when

the diameter of particle increases. Collecting plates with excessive height and width can

cause the velocity fertilizer to drop and the particles fail to distribute well. Furthermore,

furthers distance between the boom section can also cause the particles to scattered

unevenly onto the ground. The most desired simulation result was achieved with 1.5 mm

diameter particles, air velocity 8 m/s, distance between boom section is 200 mm and

height and width of collecting plate is 14 mm and 10 mm. Particle scattered well and the

average of the particle at the first exit until last exit of boom section were observed to be

evenly distributed.

vi

ABSTRAK

Penyembur bebutir bum telah digunakan oleh petani yang mempunyai ladang selama

berabad lamanya. Di MARDI, mereka menggunakan 3 jenis baja iaitu Nitrogen, N,

Fosforus, P dan Kalium, K. 3 jenis baja telah disimulasi dengan menggunakan perisian

ANSYS dan keputusan menunjukkan bahawa baja kalium, K tidak bertaburan ke tanah

dan baja yang lain adalah sebaliknya. Pelbagai kaedah telah digunakan untuk mengkaji

kecekapan ledakan semburan pada kaedah pembuatan, perisian simulasi dan pendekatan

makmal. Simulasi baja dalam penyembur bum dari bahagian masukan penyembur bum

sehingga bahagian keluaran dan disemburkan ke tanah. Kaedah Taguchi telah digunakan

dalam kajian ini. Untuk susunan ortogon, kajian ini terdiri daripada 4 tahap dan 5

faktor, L'16 telah digunakan untuk proses simulasi. Simulasi ini menggunakan hanya

satu baja yang mengandungi semua jenis baja asas NPK. Parameter yang terlibat ialah

diameter saiz berbutir, halaju udara di bahagian masukan, jarak bahagian bum keluaran,

ketinggian dan lebar plat pengumpul. Keputusan menunjukkan bahawa halaju udara

mesti lebih tinggi apabila diameter baja bertambah. Plat pengumpul dengan ketinggian

dan lebar yang berlebihan boleh menyebabkan halaju baja menurun dan baja gagal

berterabur dengan baik. Jarak antara bahagian keluaran bum juga boleh menyebabkan

baja bertabur tidak sekata ke atas tanah. Hasil simulasi yang paling diingini telah dicapai

dengan saiz diameter baja 1.5 mm, halaju udara 8 m/s, jarak antara bahagian keluaran

bum adalah 200 mm dan ketinggian dan lebar plat pengumpul adalah 14 mm dan 10

mm. Baja yang bertaburan dengan baik dan purata baja di bahagian keluaran yang

pertama sehingga keluaran terakhir diagihkan sama rata.

vii

CONTENTS

TITLE i

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

CONTENTS vii

LIST OF TABLES xi

LIST OF FIGURES xii

LIST OF SYMBOLS xvii

LIST OF APPENDICES xviii

CHAPTER 1 INTRODUCTION

1.1 Introduction 1

1.2 Problem Statement 3

1.3 Significant of study 3

1.4 Objective and scope of study 5

CHAPTER 2 LITERITURE REVIEW

2.1 Granular Fertilizer Boom Sprayer 5

2.2 Nozzle and Blow head 6

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2.3 Pipe selection for granular material 8

2.4 Particle size and shape 9

2.5 Computing Fluid Dynamics Software 10

2.6 Benefits of CFD software 11

2.6.1 CFD Process 12

2.6.1.1 Preprocessing 12

2.6.1.2 Solver 12

2.6.1.3 Post processing 13

2.7 Flow in pipe 13

2.8 Design of experiment 14

2.8.1 Full factorial method 15

2.8.2 Advantages and Disadvantages

Full factorial method 17

2.9 Design of experiment via Taguchi method 17

2.9.1 General step for taguchi method 19

2.9.2 Types of Orthogonal Array 19

2.9.3 Advantages and disadvantages Taguchi method 20

2.10 Determining Parameter Design Orthogonal Array 20

2.11 NPK Fertilizer 22

CHAPTER 3 METHODOLOGY

3.1 Introduction 24

3.2 Methodology Flow Chart 26

3.3 Computational Modeling Using Solid Works 27

3.4 Computational modeling of the pipe and

blow head using Solid works 27

3.5 Parameter of pipe and blow head 28

3.6 Simulation using ANSYS Software 30

3.6.1 Meshing 30

3.6.2 Preprocessor 32

ix

3.7 Parameter selection 35

3.6.4 Post processer 35

3.6.3 Solver 35

3.8 Orthogonal Array 36

3.9 Grid Independency test 39

CHAPTER 4 RESULT AND DISCUSSION

4.1 Introduction 40

4.2 Grid Independence Test 41

4.3 Simulation the actual situation at MARDI 42

4.3.1 Analysis of NPK Distribution 48

4.4 Simulation of particle distribution using

Taguchi Method 48

4.4.1 Simulation No 1 48
















4.5 Parameter Analysis 111

x

4.5.1 Size of Particles and Air velocity 111

4.5.2 Height and width of collecting plate 112

4.5.3 Blow head arrangement 115

CHAPTER 5 CONCLUSION AND RECOMENDATION

5.1 Conclusion 117

5.2 Simulation for NPK fertilizer 118

5.3 Simulation using Taguchi method 118

5.4 Recommendation 119

REFERENCES 120

APPENDICES 124

xi

LIST OF TABLE

Table 2.1 Parameter for example 16

Table 2.2 Test matrix 16

Table 2.3 Advantages and disadvantages of Full Factorial method 17

Table 2.4 Advantages and disadvantages of Taguchi method 20

Table 2.5 The Spindle Speed 21

Table 2.6 Selector Array 21

Table 2.7 L9 Array select 21

Table 2.8 L9 array table of experiment 22

Table 2.9 NPK specification 23

Table 3.1 Parameter for pipe and blow head 29

Table 3.2 Meshing parameter 30

Table 3.3 Setting the properties for the blow head and pipe. 34

Table 3.4 Parameter for Boom sprayer. 36

Table 3.5 Array selector 36

Table 3.6 Choose L27 from array selector 37

Table 3.7 Orthogonal array L‟16 37

Table 3.8 Number of experiment according Orthogonal Array 38

Table 4.1 Different grid size with number of elements and nodes. 41

xii

Table 4.2 Fertilizer properties 42

Table 4.3 Particle size and air velocity 111

xiii

LIST OF FIGURE

Figure 2.1 A prototype of granular boom sprayer. 6

Figure 2.2 Nozzle Manifold. 7

Figure 2.3 Blow Head with collecting plate 30º. 8

Figure 2.4 Circular PVC pipe. 9

Figure 2.5 Different size of particles. 9

Figure 2.6 Simulation of flow in pipe using CFD software. 11

Figure 2.7 Reynold Number. 13

Figure 2.8 Laminar and turbulent flow. 14

Figure 2.9 Example of Level and factor. 15

Figure 3.1 Flow chart of the process for this study. 26

Figure 3.1 Pipe and blow head design. 28

Figure 3.2 Dimension for pipe and blow head. 29

Figure 3.3 Before sizing the meshing. 31

Figure 3.4 After sizing the meshing. 32

Figure 3.5 Setting boundaries. 33

Figure 4.1 Drawing actual boom sprayer using Solid Work. 42

Figure 4.3 Nitrogen, N Particle Track Distribution. 43

Figure 4.2 Air Velocity. 44

xiv

Figure 4.3 Phosphorus, P Particle Track Distribution. 45

Figure 4.4 Potassium, K Particle Track Distribution. 46

Figure 4.5 NPK Particle Track Distribution. 47

Figure 4.6 Particle Distribution Track for Simulation 1. 49

Figure 4.7 Air velocity and Particle Distribution Track

For simualtion no 1. 50



For simulation no 2. 53

Figure 4.10 Particle Distribution at the end of Boom Sprayer. 54















xv

























xvi
















Figure 4.50 Particle size versus Air velocity graph. 112

Figure 4.51 Height and width comparison 1. 113

Figure 4.52 Height and width comparison 2. 114

Figure 4.53 Comparison between distances of boom section. 115

xviii

LIST OF SYMBOL

CFD - Computational Fluid Dynamics

Re - Reynold Number

ρ - Ketumpatan, kg/m³

μ - Kelikatan dinamik, kg/(m*s)

ν - Kelikatan kinematik, m²/s

V - Halaju purata, m/s

D - Diameter, m

3D - 3 Dimensi

Mm - Milimeter

xviii

LIST OF APPENDICES

BOOM SPRAYER 1 125

BOOM SPRAYER 2 126

GANTT CHART PS 1 127

GANTT CHART PS 2 128

1

CHAPTER 1

INTRODUCTION

1.1 Introduction

In agriculture, the process of fertilizing and fumigating insects is one of the most

important processes. This can help farmers to harvest more quality crop. In the early

1800s, most of the pesticides and fertilizer applications are carried out manually [1].

This method requires number of workers if the agricultural area was spacious. As a

result, it would involve high costs.

2

In the mid-1800s, the group of researchers has succeeded in producing a

knapsack sprayer. Knapsack sprayer can help farmers with this tool just need to bear

filled with poison or steel. Farmers only need to pump and nozzle tip pointing in the

desired direction. Even so, the development of more advanced agricultural technologies.

In the late 1800s, the first spray machines have been introduced [1]. This

machine does not require human power, it depends on the machine but must be

controlled by farmers.Advances in agricultural technology is growing and today has

many machines and methods have been introduced by researchers to facilitate

agricultural work. Sprayers usually consist of basic parts such as tanks, delivery pipe,

pump, boom and nozzles [1].

Granular boom sprayer has been used by farmers who have a farm or a wide

area. This machine is used to repel or fertilize their crops. This machine has been studied

by researchers for several decades. They study in terms of the efficiency of the system to

reduce the error to be a problem to them. Many changes have been made, especially in

the design of the sprayer boom although the results show that the role of variable rate

plays an important role in influencing the rate of distribution of granular uniformity [2].

As a result, the uniformity of the distribution of granular fertilizer was carried

out with a reasonable range of variables. Various methods have been used to study the

efficiency of the spray boom design on manufacturing methods, simulation software and

lab approach.

In the modern world of technology, have a lot of software that can examine and

give an overview on the parts that have been studied. In addition, the results from these

experiments can be compared against variable rate difference. Some examples of

software that can be used as CFD software, AMIRA, mathlab, Lisa software, Tecplot,

and more. Calculations and experiments carried out using a computer to simulate

3

reaction or the reaction between granular particles and the air based on the specified

settings of boundary conditions.

Fluid dynamics is a field of science that studies the physical laws governing the

flow of fluid under various conditions. In this study, Computational Fluid Dynamics

software, better known as CFD has been used to study the air and particle flow in a pipe

and then at the exit blow head.

CFD is a software that makes the prediction of fluid flow by means of

mathematical modeling (partial differential equations), numerical methods

(discretization and solution technique) and software tools, namely (preprocessing, solver

and post processing). Additionally, CFD can also help scientists and engineer for carry

out experiments in a „virtual flow laboratory‟.

Continuous research will improve the efficiency of the design in terms of the

geometry boom sprayer and air flow. Besides, using High Speed computer will affect the

the answers more precise.

1.2 Problem statement

Boom sprayer is used to distribute crop. In this study the focused, fertilizer used is

granular and pushed by high pressure air to scattered the fertilizer falls into place to be

fertilized. But the spray fertilizer uniformity is a problem to researchers because

fertilizer falls on the ground are not uniform. It causes the plant to grow irregular. This

study to examine the uniformity the spray granular fertilizer using a variety of high-

pressure air. In addition, in this study to modify the design boom sprayer to uniformity

spray fertilizer on the areas that have been sprayed. This studies have to go through three

stages which is pre-processing, solver and post-processing to achieve the result.

4

1.3 Significant of study

This study can be obtained as a result of various designs boom sprayer with an effective

and more efficient as well as cost effective research. The success of this study will be

beneficial to the agricultural sector to achieve uniformity in the distribution of granular

boom sprayer. In addition, it can help other researchers who study the granular flow in

the pipe. Besides, using software that has been developed, it can help or advice for the

best solution to achieved the goal of the experiment.

By using software, can simulated the result and also can cut the cost before go to

the actual part and its call Virtual Engineering. It can help to perform the experiment

without carry out the cost of the experiment and just using software can find the result.

Besides, it can help to reduce the time of the making the product. Futhermore, various

design of boom sprayer can be made and help the researcher to find the best and most

effective design.

1.4 Objective and scope of study

The objective of this study is to:

1. To evaluate the existing boom sprayer design for effectiveness of the granular

flow through and out the boom sprayer.

2. To design a new boom sprayer mechanism for optimum granular fertilizer

distribution.

3. To suggest and improve the boom sprayer design to achieve a better efficiency

levels for MARDI.

5

To avoid diverted research objectives, some scope of study was created to be guidelines

to achieve the above objectives:

1. Using ANSYS CFD CFX software

2. Analyzing the fertilizer particle movement from the inlet to the outlet of boom

sprayer section.

3. Blow head diameter is 32 mm.

4. Air velocity at 1 m/s, 3 m/s, 5 m/s and 8 m/s.

5. Diameter particle 1 mm, 1.5 mm, 2 mm and 2.5 mm.

6. Collecting plate angle 60º.

7. Height of collecting plate 10 mm, 14 mm, 18 mm and 22 mm.

8. Width of collecting plate 10 mm, 15 mm, 20 mm and 25 mm

9. Use cylinder boom shape.

6

CHAPTER 2

LITERATURE REVIEW

2.1 Granular Fertilizer Boom Sprayer

In agriculture, engineering may not be suitable to associate with. However engineering

in agriculture nowadays is very important. The results of combining engineering and

agriculture can increase productivity and can help and facilitate the farmers perform

their daily work. Bum granular fertilizer sprayer is one of the engineering innovations in

agriculture. Granular fertilizer boom sprayer works as a machine that helps farmers

apply fertilizers or to combat the pests.

The method used is to spray fertilizer or pesticides to the crops by using

machines. Prototype ofthe granular boom sprayer show as Figure 2.1.

7

Figure 2.1: A prototype of granular boom sprayer. [3]

The boom sprayer machinery usually contains the granular fertilizer in a storage

container called a hopper. Apart from storing granular fertilizer, shaft design also serves

to reduce energy consumption. Granular fertilizer will apply pressure so that it moves

through the pipe before it is released through the blow head and scattered on the ground.

2.2 Nozzle and Blow head

Nozzle and blow head are the most important part of the spray process regardless of the

situation of substances is in the form of a liquid or granular form. It depends on the

results requested by the user. Nozzle is a device designed to control or direction of fluid

flow characteristics particularly to increase the velocity when leaving or entering a

confined space or pipes. The nozzles are typically used on pipes or tubes of varying

cross-sectional area and it can be used to redirect or change the flow of liquid or gas.

The nozzles are often used to control the flow rate, speed, direction, shape, mass and

pressure flow out of it [4]. Example of the nozzle is shown in igure 2.2.

8

Figure 2.2: Nozzle Manifold [5].

Unlike the blow head, blow head used for granular materials. Blow head is to

standardize the use of spray which isspattered all over the place. In Figure 2.2, blow

head is attached to the pipe. Previous studies have been carried out by connecting the

delivery pipe and angled the blow head at 120º and 185 mm long. The size of the boom

at the input section is 35 mm X 35 mm.

To produce a uniform spray, researchers have been collecting plate placed on the

inlet and collecting plate height can be changed. Collecting angled plate 30º [3]. Figure

2.3 shows the blow head.

9

Figure 2.3: Blow Head with collecting plate 30º[3].

2.3 Pipe selection for granular material

The pipe is used to channel the fluid from one place to another place. Pipe design is very

important because it will affect the flow therein. There are several types of pipes which

are circular pipe and non-circular pipe. A cicular pipe is used to transport fluid because

circular pipe can withstand the pressure difference between the inside and the outside of

the pipe without significantly disturbing the flow [6]. Non circular pipes are used for

applications in the cooling or heating system for the building. This type of non-circular

pipe commonly used for low-pressure fluid. In addition, the inside of the pipe also play

an important role. It will help to smooth the movement of fluid in a pipe even it can

improve efficiency at the output. Moreover, the choice of the pipe depends on the type

of materials used for distribution through pipelines. Figure 2.4 show the example of

circular pipe.

10

Figure 2.4 : Circular PVC pipe [7].

2.4 Particle size and shape

Fertilizer distribution pattern consistency and effectiveness is a key requirement in this

study. Therefore, particle size plays an important role in order to spread the fertilizer

evenly. Particle size is used to facilitate the work of farmers when spreading the

fertilizerat a distance. However, it requires a lot of energy to push granular fertilizer to

distant places. In addition, the large particle size cannot drain properly and causes

stunted spreading fertilizer. Normally the particle size measuring 2-4 mm can help

spread the fertilizer uniformly. [8]. Figure 2.5 shows the different size of particles.

Figure 2.5 : Different size of particles [9].

11

Shape also plays an important role in spreading fertilizer. Normally, fertilizer is a

spherical shape and can flow in pipe when high-pressured air is applied and helps to

spread the fertilizer evenly and uniformly.

2.5 Computational Fluid Dynamics Software

Computational Fluid Dynamics (CFD) is computer-based software to simulate the

behavior of a system such as fluid flow, heat transfer and other related physical

processes. It works by solving the equations of fluid flow (in a special form) to the

desired areaand prescribed conditions (known) at the boundary of the area are required.

Computers have been used to solve problems of fluid over the years in which

CFD solvers have been developed since the mid-1970s. The latest developments in the

field of computing power, together with the manipulation of 3-D graphics and

interactive effectively means the process of making a CFD model and analyse the results

is much less labour intensive, saving time and costs. Advanced CFD solver contains

algorithms that enable robust solutions in the field of flow in a fast time. As a result of

these factors, CFD is now a robust industrial design software, helps to reduce design

timescales and improve processes worldwide engineering.

CFD provides a cost-effective alternative and appropriate for the testing of scale

models, with changes in the simulations carried out quickly, which offers significant

advantages. By using CFD software, virtual prototyping system or device can be

designed to be analysed, then the real-world physics and chemistry is for use on the

model and the software will generate the images and data to predict the performance of

the design [10]. Figure 2.6 shows the results of using Ansys software-CFD.

12

Figure 2.6: Simulation of flow in pipe using CFD software [11].

2.6 Benefits of CFD software

There are three compelling reasons to use CFD software which are visionary, far-sighted

and have high efficiency. If any device or system that is difficult to build prototype or

tested experimentally, CFD analysis is able sneak into the design and show how it is

implemented. There are many phenomena that can be seen through the CFD, which

cannot be seen by any other means. CFD provides a deeper insight for each design. CFD

is a tool to predict what will happen under certain circumstances.

If there is one set of boundaries, the software will deliver results. Moreover, in a

short time, the software can predict how a particular design will be implemented and can

tested with variety for optimal results. All this can be done prior to physical prototyping

and testing. The results obtained from CFD helps improve the design, save money, meet

environmental regulations and ensure industry requirements. CFD analysis leads to

shorter design cycle and help to market more quickly. CFD software is also able to

shorten the development cycle and enables the design to make a quick prototype [12].

13

2.6.1 CFD Process

In the CFD process, there are basically three levels for each CFD simulation process

prior to pre-processing, solving and post-processing process.

2.6.1.1 Pre processing

This is the first step in constructing and analysing flow model. It includes building a

model in Solid work, create and use appropriate calculation network, and enter the

boundary flow conditions and fluid properties. Solid work simple geometry are imported

and adapted for CFD solutions in GAMBIT.

3D model selection in GAMBIT allows construction, simple geometry and

geometry translation of high quality. GAMBIT is a unique curvature and distance based

„functional size‟ to produce the right type of CFD and fine mesh around the model.

Along with the boundary layer technology, some schemes produce a volume mesh

correction for the application. Parameter differences also exist in the process [12].

2.6.1.2 Solver

CFD flow solver calculations and produce results. FLUENT CFD code has an extensive

interactive, so it can make changes to the analysis at any point during the process. This

saves time and allows you to refine a more efficient design. Graphical user interface

(GUI) is intuitive, which helps to shorten the learning time, and made the process faster

model. It is also easy to adjust physical condition and function interfaces to specific

needs. In addition, adaptive and dynamic network capability is unique among the

FLUENT CFD provider and works with various physical models. This capability makes

it possible and easy to create complex model moving objects in relation to the flow [12].

14

2.6.1.3 Post processing

This is the final step in CFD analysis, and it involves the organization and interpretation

of the data flow and earnings forecasts CFD images and animations. In addition,

FLUENT CFD solution easily added to the code structure as ABAQUS, ANSYS and

MSC, as well as simulation software engineering process to another.

2.7 Flow in pipe

Air flow has two types of movement which are laminar flow and turbulent flow Laminar

flow occurs when the fluid layer adjacent to move at the same speed and liquid particles

do not cross paths with each other. Laminar flow occurs at low velocity and high

viscosity. Is laminar flow in a pipe when Re = 2300. Turbulent flow occurs when the

current cross each other and mixing liquid flow occurs. This flow occurs at high speed

and low viscosity. A turbulent flow in pipes when Re = 4000. In fluid mechanics, the

Reynolds number (Re) is a dimensionless number which gives a measure of the ratio of

inertial forces to viscous forces and thus the quantity of the relative importance of the

two types of forces for given flow conditions [12]. Reynolds number can be calculated

using the following formula.

.................... (1)

Figure 2.7 : Reynold Number [6].

Where; ρ = Density, kg / m

μ = dynamic viscosity, kg / (m^ s)

ν = Kinematic viscosity, m / s

V = average velocity, m / s

D = Diameter, m

At Re ≤ 2300, flow is laminar,

At Re ≥ 4000, flow is turbulent,

Between 2000 < Re < 4000, flow is in the transition between laminar and turbulent

15

Air flow has 3 types of flow which are laminar flow, turbulent flow and

midstream. The diagram below shows the velocity profile of the three types of flow [6].

Figure 2.8 : Laminar and turbulent flow [13].

2.8 Design of experiment

In industry, designed experiments can be used to systematically investigate the process

or product variables that influence product quality. After you identify the process

conditions and product components that influence product quality, you can direct

improvement efforts to enhance a product's manufacturability, reliability, quality, and

field performance

For example, we may want to investigate the influence of coating type and

furnace temperature on the corrosion resistance of steel bars. We could design an

experiment that allows you to collect data at combinations of coatings/temperature,

measure corrosion resistance, and then use the findings to adjust manufacturing

conditions. Because resources are limited, it is very important to get the most

information from each experiment performed. Well‐designed experiments can produce

significantly more information and often require fewer runs than haphazard or

unplanned experiments [14].

16

In addition, a well‐designed experiment will ensure that we can evaluate the

effects that we have identified as important. For example, if we believe that there is an

interaction between two input variables, be sure to include both variables in your design

rather than doing a "one factor at a time" experiment. An interaction occurs when the

effect of one input variable is influenced by the level of another input variable. Designed

experiments are often carried out in four phases which are planning, screening also

called process characterization, optimization, and verification [15]. There are many

types of design of experiment such as one factorial designs, 2 factorial design consist

Taguchi method, response surface method design and reliability design of experiment

[16].

2.8.1 Full factorial method

This method was a traditional method which means all researchers used this method to

solve their problem. This method has level and factor which means level powered by

factor. The example of level and factor is shown below.

Figure 2.9 : Example of Level and factor[17].

Full factorial designs are the most conservative of all design types. There is little

scope for ambiguity when you are willing to try all combinations of the factor settings.

Unfortunately, the sample size grows exponentially in the number of factors, so full

factorial designs are too expensive to run for most practical purposes

For example, the experiment has 2 levels and 2 factors so it can write as 2². The

level is a velocity, temperature and pressure in the intake manifold. For the factor there

are „low‟ and „high‟ value for every levels. Velocity is 5m/s and 10m/s and pressure is

10kPa and 50kpa. This levels and factors can write in table such as table 2.1.

17

Table 2.1 : Example of parameters.

Level Low ( - ) High ( + )

Velocity, m/s 5 10

Pressure, kPa 10 50

Calculation for the experiment test is 2 X 2 is equal to 4 run for this experiment.

So, it can be write in the table such below.

Table 2.2 : Matrix Test [17].

Run number Factor Level

Low ( - ) High ( + ) Velocity, m/s Pressure, kPa

1 - - 5 10

2 + - 10 50

3 - + 5 10

4 + + 10 50

After matrix test iscompleted, the experiment can be performed according to the

table. The result can conclude which combination is the best and the worse.

18

2.8.2 Advantages and Disadvantages Full factorial method

This method have several advantages and limitation that researcher must know

before used this method. Table shown below are the advantages and disadvantages of

the full factorial method.

Table 2.3 : The Advantages and disadvantages of Full Factorial method [17].

No Advantages Disadvantages

1 This method is more precision on each

factor than with single factor

experiment.

When number of factor and level increase,

number of experiment will increase.

2 Broadening the scope of the

experiment.

Need more time for experiment when number

of factor and level more than 2.

3 Possible to estimate the interaction

effect.

Can be more complicated when the number of

interaction increase.

4 This method can lead to more

powerful test by reducing the error

variance.

Very high cost to do all experimental work.

5 Good for exploratory work that we

wish to find the most important factor.

Need more time to compare the result if those

experiment have many level and factor.

2.9 Design of experiment via Taguchi method

Dr. Genichi Taguchi is regarded as the foremost proponent of robust parameter design,

which isan engineering method for product or process design that focuses on minimizing

variation or sensitivity to noise. When used properly, Taguchi designs provide a

powerful and efficient method for designing products that operate consistently and

optimally over a variety of conditions.

19

In robust parameter design, the primary goal is to find factor settings that

minimize response variation, while adjusting the process on target. After we determine

which factors affect variation, we can try to find settings for controllable factors that will

either reduce the variation, make the product insensitive to changes in uncontrollable

noise factors, or both. A process designed with this goal will produce more consistent

output. A product designed with this goal will deliver more consistent performance

regardless of the environment in which it is used [18].

Engineering knowledge should guide the selection of factors and responses.

Robust parameter design is particularly suited for energy transfer processes, for

example, a car's steering wheel is designed to transfer energy from the steering wheel to

the wheels of the car. We should also scale control factors and responses so that

interactions are unlikely. When interactions among control factors are likely or not well

understood, we should choose a design that is capable of estimating those interactions.

Noise factors for the outer array should also be carefully selected and may

require preliminary experimentation. The noise levels selected should reflect the range

of conditions under which the response variable should remain robust. Robust parameter

design uses Taguchi designs (orthogonal arrays), which allow to analyse many factors

with few runs. Taguchi designs are balanced, that is, no factor is weighted more or less

in an experiment, thus allowing factors to be analysed independently of each other.

20

2.9.1 General step for Taguchi method

Taguchi method has the steps or procedures that have been designed by Dr.Genichi

Taguchi let users know how to use this method [19]. The steps are as following:

1 Identify objectives or more specific, target value for a performance

measure of the process.

2 Identify design parameters that will affect the experiment

3 Orthogonal array for the design parameters have been selected. It shows

the number and variations of each trial.

4 Run experiments according orthogonal array that have been made.

5 Analyse the data from the experiments that have been conducted

2.9.2 Types of Orthogonal Array

Taguchi has introduced several kinds of orthogonal arrays that can be used in

accordance with the parameters and the level required by the Researcher. Among the

types of orthogonal array is shown below:

L4 L8

L9 L12

L16 L‟16

L18 L25

L27 L32

L‟32 L36

L50

While many introduced by Taguchi orthogonal array, this study uses orthogonal

array L27. Parameters and levels is an important role in determining the appropriate

orthogonal array for the experiment to be carried out.

21

2.9.3 Advantages and disadvantages Taguchi method

There have several benefits and limitation of Taguchi method that user must know

before using this method for experimental work. Table below shows the benefits and

limitations of Taguchi method.

Table 2.4 : Advantages and disadvantages of Taguchi method[17]

No Advantages Disadvantages

1 Suitable for many levels and

factors

Do not test all variable combination

2 Time saving Difficulty accounting interactions between

parameter

3 Cost saving Do not exactly indicate what parameter has

the highest effect on the performance

characteristic value

4 Easy to complement Results obtained the relative

2.10 Determining Parameter Design Orthogonal Array

Taguchi has introduced a method that can help researchers utilize orthogonal array. The

parameter is a variable that will change and affect the experiment when diversified.

When the parameters affecting the experiment, the level where these parameters need to

be changed must be determined. To determine the level of variables requires a deep

understanding of the process, including minimum, maximum and current parameter

value. For example, there are six speed gear spindle, three in front and three on the rear

gear like the table below.

22

Table 2.5: The Spindle speed[20].

From the table above, there are 3 levels and 3 parameters. Parameter is the

spindle speed, feed rate and depth of cut. While the level is the number of parameters is

three. Referring to the selector array that has been introduced by Taguchi, Table selector

array is shown below.

Table 2.6 : Selector Array [19].

Table 2.7 : L9 Array select [19].

23

L9 array is an array of numbers that help researchers to facilitate the course of

the experiment. In addition, it can provide a guide to researchers in conducting

experiments. Table L9 is shown below.

Table 2.8 : L9 array table of experiment [19].

2.11 NPK Fertilizer

In agriculture fertilizer or seed is most important part or others name likes “vitamin” to

the plants. Like human, plants also need Carbohydrates, Protein and fat but for plant also

have three main "food groups", or rather "macro nutrients", the three main elements that

make up the bulk of a fertilizer is NPK[21].

NPK is short name of Nitrogen (N), Phosphorus (P) and Potassium (K) or in

other name „Kalium‟ hence the chemical symbol K. All elements have their own

characteristic of shape, density and molar mass. Nitrogen, N helps the plant to grow

strong and if too high nitrogen fertilizers will make for quick growth but weaker plants

that are more susceptible to attacks by diseases and pests. This chemical fertilizer is a

component of chlorophyll and aid to photosynthesis. Phosphorus, P is important in the

photosynthesis process.

24

This chemical fertilizer supports the component such as oils, sugar and starches

to the plant. In addition, phosphorus helps the growth of root and flower development.

The last content is Potassium, K, besides help the photosynthesis process, this „vitamin‟

help to support protein to the plant. Most importantly, this chemical fertilizer controls

the fruit‟s quality and to make the plant healthy [21]. These 3 elements have their own

specification as shown table 2.5 below.

Table 2.9 : The NPK specifications [22].

Fertilizer

element

Density, g/cm³ Molar mass,

g/mol Particle Shape Size, mm

Nitrogen, N 1.026 14.0067 Granular/ Fluid 1 - 5

Phosphorus, P 1.823 30.9737620 Granular/Fluid 2 - 6

Potassium, K 0.862 39.0983 Granular/Fluid/Powder 0.1 - 1

There have ratio between NPK elements for example 10-10-10 that means

Nitrogen 10%, Phosphorus 10% and Potassium 10%. This ratio has their purpose for the

growth of the plant. For example 10-10-10 fertilizer has a 1-1-1 ratio, 10-20-10 fertilizer

has a 1-2-1 ratio and 30-15-15 fertilizer has a 2-1-1 ratio. Basically, gardener use 1-2-1

ratio for the rooting, 1-1-2 or 1-2-2 or 2-1-2 ratio for the flowering and fruiting, for leafy

growth the ratio is 2-1-1 or 3-1-1 and for all purpose the ratio is 1-1-1 [22].

121

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