Production Yield Analysis Of An Automotive Component Using General Linear Model.
UNIVERSITI TEKNIKAL MALAYSIA MELAKA
PRODUCTION YIELD ANALYSIS OF AN AUTOMOTIVE
COMPONENT USING GENERAL LINEAR MODEL
This report submitted in accordance with requirement of the Universiti Teknikal
Malaysia Melaka (UTeM) for the Bachelor Degree of Manufacturing Engineering
(Manufacturing Management) with Honours.
by
MUHAIZAD BIN MUHIYDDIN
FACULTY OF MANUFACTURING ENGINEERING
2010
UNIVERSITI TEKNIKAL MALAYSIA MELAKA
BORANG PENGESAHAN STATUS LAPORAN PROJEK SARJANA MUDA
I
TAJUK: Production Yield Analysis of An Automotive Component Using General Linear
Model
SESI PENGAJIAN: Semester 2 2009/2010
Saya MUHAIZAD BIN MUHIYDDIN
mengaku membenarkan Laporan PSM ini disimpan di Perpustakaan Universiti Teknikal
Malaysia Melaka (UTeM) dengan syarat-syarat kegunaan seperti berikut:
1. Laporan PSM adalah hak milik Universiti Teknikal Malaysia Melaka dan penulis.
2. Perpustakaan Universiti Teknikal Malaysia Melaka dibenarkan membuat salinan untuk
tujuan pengajian sahaja dengan izin penulis.
3. Perpustakaan dibenarkan membuat salinan laporan PSM ini sebagai bahan pertukaran
antara institusi pengajian tinggi.
4. **Sila tandakan (/)
D
D
0
(Mengandungi maklumat yang berdarjah keselamatan atau
kepentingan Malaysia yang termaktub di dalam AKTA RAHSIA
SULIT
RASMI 19n)
(Mengandungi maklumat TERHAD yang telah ditentukan oleh
organisasi/badan di mana penyelidikan dijalankan)
TERHAD
TIDAK TERHAD
Disahkan oleh:
Ｈｲａｎ ｾ＠
(TANDATANGAN PENYELIA)
PENULIS)
Alamat Tetap:
NO. 93, JLN 10/21,
Cop Rasmi: AB RAH AN BIN AH 0 00
Pensyar•hKa"an
ｆｴｾ ｫｵｬｴｩ＠
Keiuruter'lan Pembuatan
Universiti Teknikal Malaysia Melaka
Perumahan Bakti 1,
81700 Pasir Gudang, Johor
Tarikh:
'lt;{ c; /20 lO
Tarikh:
r-.
ｲ ｪｲｊ
c.J./
ｾ＠
/ {()
----------------------------------------------
- Jika Laporan PSM ini SULIT atau TERHAD, sila lamplrkan surat darlpada pihak berkuasa/organisasi
berkenaan dengan menyatakan sekali sebab dan tempoh laporan PSM ini perlu dikelaskan sebagai
SUUT atau TERHAD.
DECLARATION
I hereby, declared this report entitled "PSM Title" is the results of my own research
except as cited in references.
Signature
ﾷｾ
ﾷ＠
Author's Name
MUHAIZAD BIN MUlllYDDIN
Date
'J..c; jr; I 'J-.o I D
.........................................
APPROVAL
This report is submitted to the Faculty of Manufacturing Engineering ofUTeM as a
partial fulfillment of the requirements for the degree of Bachelor of Manufacturing
Engineering (Manufacturing Management) with Honours. The member of the
supervisory committee is as follow:
(Signature of Supervisor)
(Official Stamp of Supervisor)
A8 RAHMAN .IN MAHMOOD
ｾｳｹ｡ｲｨ＠
K.n.,
ｾｮ
Fakulti Kejuruteraan Pe!nWatan
ｬ ｶｴｲｬｩ＠
Ttkniktl Mt!IYIIa ｾ＠
ABSTRACT
Every day the manufacturing company calculated the output and yield in order to
measure the capability of production line in certain time. This study used General Linear
Model (GLM) approach in order as a technique to make an analyzing of the possible
factors that contributes to the yield. The production output data was used to gathering
information about the situation that may happen on production line and to know the
possible factor that may effect to yield. The analyzing will be done by using the Minitab
software so that can know the significant of each factors that selected and what factors
and interaction of factor will give an effect for the yield.
i
ABSTRAK
Setiap hari syarikat pembuatan akan mengira jumlah keluaran dan kadar hasil untuk
mengukur prestasi pengeluaran berdasarkan masa tertentu. Di dalam penyelidikan ini,
pendekatan teknik ‘General Linear Model’ digunakan untuk menganalisis faktor-faktor
berkemungkinan yang memberikan kesan kepada kadar hasil. Data jumlah hasil
pengeluaran setiap hari syarikat digunakan untuk mengumpul maklumat supaya boleh
diketahui keadaan yang berlaku di dalam kilang dan untuk mengenalpasti faktor-faktor
yang menyumbang pengaruh kepada kadar hasil. Analisa dibuat dengan mengunakan
perisian Minitab dan signifikan setiap faktor yang dipilih dapat diketahui.
ii
DEDICATION
To my parent who gives me a support and remind me to always be strong in a life to
assault all the challenges in front.
iii
ACKNOWLEDGEMENT
This project and report writing has been culmination for my studies in Universiti
Teknikal Malaysia Melaka (UTeM). Many challengers have been faced during project
completion but at the same time it has been very interesting and rewarding.
Now that I am finishing this project, I would like to express my gratitude especially to
my supervisor, Mr. Ab. Rahman bin Mahmood for his constructive comments, ideas,
supports and guidance for this project.
Besides that, I would like to give my warmest thanks to the various people in Hicom
Engineering Sdn. Bhd. who had contributed their cooperation. Without they valuable
and professional comments and criticism and outright support this would not have been
possible.
Last but not least, thanks to my family and my friends for their endless support and
energy they have given to me during this project and my studies.
iv
TABLE OF CONTENT
Abstract
i
Abstrak
ii
Dedication
iii
Acknowledgement
iv
Table of Content
v
List of Tables
viii
List of Figures
ix
List Abbreviations
x
1. INTRODUCTION
1
1.1
Background of Study
1
1.2
Problem Statement
2
1.3
Objectives
2
1.4
Scope
3
1.5
Background of Company
3
2. LITERATURE REVIEW
4
2.1
Manufacturing
4
2.2
Productivity in Manufacturing
5
2.3
Factor Effecting Productivity
7
2.4
Possible Factors
8
2.4.1
Human Factors
8
2.4.2
Psychological Factors
9
2.5
Statistical Approach
9
2.5.1
Statistical Model
10
2.5.2
Mathematical Model
10
2.5.3
Empirical Model
11
2.6
General Linear Model Overview
12
v
2.7
General Linear Model Core Equation
13
2.7.1
Additional Assumptions of General Linear Model
14
2.7.2
Least Square Estimate for The General Linear Model
14
2.7.3
Sum of Squares
15
2.7.4
Sampling Distributions of the Sum of Squares
16
2.8
Limitations of the General Linear Model
17
3.
METHODOLOGY
19
3.1
Introduction
19
3.2
Planning of Study
19
3.2.1
Process Flow Diagram (PFD)
20
3.2.2
Gantt Chart
22
3.3
Projek Sarjana Muda (PSM) Methodology
22
3.3.1
Methods
22
3.3.1.1 Observation
22
3.3.1.2 Archival Collection
23
3.3.2
26
Materials
3.3.2.1 Books
26
3.3.2.2 Historical Data
26
3.3.2.2 Minitab Software
26
3.3.3
Procedures
27
4.
RESULT AND DISCUSSION
29
4.1
Introduction
29
4.2
Data Collection
29
4.3
Minitab Result
36
4.4
Analysis on Result
37
4.4.1
Factor Table
37
4.4.2
Analysis of Variance Table
38
4.4.3
S, R-Sq and R-Sq(adj) Values
39
4.4.4
Unusual Observation Table
40
vi
4.4.5
Least Squares Means
41
4.4.6
Tukey Method
42
4.4.6.1 Confidence Interval
43
4.4.6.2 Hypothesis Test
48
4.4.7
Normplot of Residuals for Yield Graph
55
4.4.8
Residuals versus Fits for Yield Graph
57
4.4.9
Residuals Histogram for Yield Graph
59
4.4.10 Residuals versus Order for Yield Graph
61
4.4.11 Main Effects Plot (fitted means) for Yield Graph
63
4.4.12 Interaction Plot (fitted means) for Yield Graph
65
5.
CONCLUSION
67
5.1
Overview of the Study
67
5.2
Limitations
68
5.3
Recommendation
68
REFERENCES
69
APPENDICES
71
vii
LIST OF TABLES
3.1
Gantt chart for PSM I
24
3.2
Gantt chart for PSM II
25
4.1
Data need to be key-in at Minitab
32
4.2
Factor Table
37
4.3
Analysis of Variance Table
38
4.4
Result of S, R-Sq and R-Sq(adj) Values
40
4.5
Unusual Observation Table
40
4.6
Least Squares Means Table
41
4.7
Adjusted P-values table for Month
49
4.8
Adjusted P-values table for Week
51
4.9
Adjusted P-values table for Shift
51
4.10
Adjusted P-values table for Hour 1
52
4.11
Adjusted P-values table for Hour 2
52
4.12
Adjusted P-values table for Hour 3
53
4.13
Adjusted P-values table for Hour 4 until 9
53
viii
LIST OF FIGURES
3.1
Planning process flow chart
21
3.2
Correlation of methodology to achieved the objectives
28
4.1
Example of PSPC data from the company
30
4.2
New data converted from PSPC data
31
4.3
Step (i)
33
4.4
Step (ii)
33
4.5
Step (iii)
34
4.6
Step (iv)
34
4.7
Step (v)
35
4.8
Example of a General Linear Model’s result from Minitab
36
4.9
Confidence Interval for Month
43
4.10
Confidence Interval for Week
45
4.11
Confidence Interval for Shift
45
4.12
Confidence Interval for Hour
46
4.13
Example of normal probability plots patterns
55
4.14
Normal Probability Plot of the Residual Graph
56
4.15
Example of residuals versus fitted values plots patterns
57
4.16
Residuals versus the Fitted Values Graph
58
4.17
Example of Histogram patterns
60
4.18
Histogram of the Residuals
60
4.19
Example of residual versus order plots patterns
61
4.20
Residual versus Order for Yield Graph
62
4.21
Main Effect Plot for Yield
64
4.22
Interaction Plot for Yield Graph
66
ix
LIST OF ABBREVIATIONS
ANCOVA
-
Analysis of Covariance
ANOVA
-
Analysis of Variance
DOE
-
Design of Experiment
GLM
-
General Linear Model
ISO
-
International Organization of Standardization
PFD
-
Process Flow Diagram
PSM I
-
Projek Sarjana Muda 1
PSM II
-
Projek Sarjana Muda 2
PSPC
-
Production Shift Productivity Control
UPH
-
Unit per Hour
USD
-
United States Dollars
SPC
-
Statistical Process Control
x
CHAPTER 1
INTRODUCTION
This chapter presents the background of the project, problem statement, objective and
scopes of the project. Background of the project describes about the project. Problem
statement states the reason for execute the project. The objectives of the project are the
aim of the project and the scopes explains about the limitations of the project.
1.1
Background of Study
This study is to analyze an optimum performance of machining line productivity when
running mass production. However, the factors such as working shift or any relevant
factor was identified that can influence the production performance like efficiency and
product quality. Using the General Linear Model (GLM), the factors can be manipulated
intentionally so that can access and understand the impact based on historical data of
production.
1
1.2
Problem Statement
The design and setting up of production is normally done based on predetermined
parameter which is extracted from theoretical information on the process sequence or
flow. The assumption is done as a result of the study on part drawing supplied by
customers.
Once the production line was commissioned, it will be tested to verify its capacity and
performance especially on Unit per Hour (UPH) and the consistency of the dimension.
This finding is discovered after performing test run and pre-production simulation. From
the result also can validate whether the actual result example capacity and quality is in
accordance with design assumption.
Adjustment on workspace design or man-machine chart is reviewed if the production
line doesn‟t meet the requirement of predetermined design, for example UPH and
minimum reject rate. However, the adjustment of production line it seems impossible
and can influence the output per day of company and also lead to company loss.
1.3
Objectives
The objectives of this study are:
1. To understand the General Linear Model theory and apply it into problem
statement
2. To study which possible factors that can affect the production yield
3. To do analyze the possible factors and production yield by using Minitab
software
2
1.4
Scope
The focus of this study is to analyze the possible factors and production yield to
measuring the performance one of selected production line. The others production line
not include in this study. The analyzing will be done using the GLM function on Minitab
software.
1.5
Background of Company
This study is done at Hicom Engineering Sdn. Bhd. machining area of production line.
Hicom Engineering is a member of DRB-HICOM group of companies, offering state-of
art manufacturing capabilities to customers. This company is do manufacture, machine
precision castings, and assemble components for automotive and general engineering
purposes. Located in Shah Alam, Selangor, Malaysia, Hicom Engineering was
commissioned in 1991 with a total paid-up capital of USD 8.07 million and a total
investment of over USD 18.4. As one of Malaysian leading manufacturers of cast-iron
automotive components, they have a strong commitment to constantly improve the
quality of our products. The MS ISO 9002 certification enhanced their spirit with utilize
the latest technological to provide the highest quality in castings.
Hicom Engineering employs a diverse group of dedicated individuals with extensive
experience in foundry and machining. Our employees are committed to the growth of
the company and to achieving consistent quality for every product. Everyone at Hicom
Engineering is responsible to contribute for total quality approach at providing products
that meet and exceed customer satisfactions.
3
CHAPTER 2
LITERATURE REVIEW
This chapter describes about literature review of the study which relates to the scope of
the study. Mostly, it covering elements of factors where contribute to manufacturing
productivity and efficiency. Sources of information were obtained from journals, books,
case studies, reports and also electronic-media sources are collected and compiled
together.
2.1
Manufacturing
Manufacturing has been practiced for several thousand years, beginning with the
production of stone, ceramic, and metallic articles. Much of manufacturing remained for
centuries as essentially individual activity, practiced by artisan and their apprentices.
The ingenuity of successive generations of artisan led to the development of many
process and great variety of product, but the scale of production is limited by the
available power (Schey, 2000). Manufacturing is an industrial activity that changes the
form of raw materials to create products by adding value. To be profitable, an enterprise
establishes and nurtures a manufacturing system that facilities the flow of information to
coordinate inputs, process and output. Development of modern manufacturing, for
example, is dependent on research I materials that may require a variety of new
production processes (Ostwald, 1997).
4
According to Quirk (1999) in manufacturing, there have four basic elements that
represent the manufacturing resources required to produce a product. They are:
i.
Labour
ii.
Methods
iii.
Machines
iv.
Materials
These elements are the building blocks of a process ant together create an infrastructure
that supports manufacturing both directly and indirectly. On one hand, understanding
these different element can help simplify the manufacturing concept. The elements
represent the specific aspects of manufacturing that should be used efficiency: fewer
labor, less equipment, less time and material required. This efficiency increases the
value in the product, which helps meet the goal for competitive manufacturing. In this
study, it focuses on the effectiveness labor utilization in order to improve current
productivity.
2.2
Productivity in Manufacturing
Most organizations would like to find the recipe for the ultimate productivity
improvement strategy. However, those same organizations that are searching for this are
likely to have found them unable to take full advantage of the methodologies and
techniques so far tried. Part of this is because many of them simply do not understand
what productivity really means. Productivity can be defined as the application of the
various resources (inputs) of an organization, industry or country, in order to achieve
certain planned and desired results (outputs). Productivity measurement entails a
comparison of outputs to inputs normally by calculation of a productivity index
(output/input ratio). Productivity improvement thus becomes the establishment of
approaches to improve this productivity index (Baines, 1997).
5
According to Stenevson (2007), productivity is an index that measures output (good and
services) relative to the input (labour, materials, energy, and other resources)
used to produce them. It is usually expressed as the ratio of output to input:
Productivity = Output
Input
A productivity ratio can be computed for a single operation, a department, an
organization, or an entire country. In business organization, productivity ratios are used
for planning workforce requirements, scheduling equipment, financial analysis and other
important task.
In the same way, Mukherjee (2006) stated that productivity is defined as the ratio of
output to input within a defined time period with due consideration for quality.
Productivity = Output (within a defined time and quality)
Input
Based on above formula, it can be elaborated as follows:
i.
Both output and input should be quantified in tangible monetary terms for correct
assessment.
ii.
Productivity implies effectiveness and efficiency in individual and organizational
performance. Here, the „effectiveness‟ means the achievement of the set
individual and the organization target or the objective whereas „efficiency‟ input
ratio is the output input ratio or the value addition to input resources minus the
cost of value addition.
iii.
Managers should clearly know their goals and those of the organization to
ascertain whether they are productive or not.
Besides, productivity also defined as a ratio of output to input which a process of
continuous improvement in the production/supply of quality output/service through
efficient, effective use of inputs, with emphasis on teamwork for the betterment of all.
6
Productivity is the belief in human progress. It is an attitude that seeks the continuous
improvement of what exists. It is a conviction that one can do better today than
yesterday, and that tomorrow will be better than today. Furthermore, it requires constant
efforts to adapt economic activities to ever-changing conditions, and the application of
new theories and new methods. It is a firm belief in the progress of humanity (NPCC,
2008)
2.3
Factor Effecting Productivity
Productivity is outcome of several interrelated factors, which can broadly be divided into
two main categories where human factors and technological factors. Human factors are a
human nature and human behavior is the most significant determinants of productivity.
Human factors include both their ability as well as their willingness to work. Ability to
work means a productivity of an organization depends upon the competence and caliber
of its people-both workers and managers. Ability to work is governed by education,
training, experience, attitude, etc. of the employees. For the willingness to work explain
on motivation and morale of people are very important factors that determine
productivity. These are affected by wage incentive schemes, labour participation in
management, communication systems, informal group relations, promotion policy,
union management relations, quality of leadership, working hours, sanitation,
ventilation, subsidized canteen, company transport, etc. While, technology factors are
the factors exert significant influence on the level of productivity. These include the
following:
i.
Size and capacity of plant
ii.
Product design and standardization
iii.
Timely supply of materials and fuel
iv.
Rationalization and automation measures
v.
Repairs and maintenance
7
vi.
Production planning and control
vii.
Plant layout and location
viii.
Materials handling system
ix.
Inspection and quality control
x.
Machinery and equipment used
xi.
Research and development
xii.
Inventory control
There also another factor that contributes the efficiency of productivity is
managerial, natural environment, sociological, political and also economic (Abha,
2007).
2.4
Possible Factors
From the factor that effecting of productivity explanation, this study can take the human
factors, technical factors, and sociological factors as possible factors that can affect the
production line output quality and productivity.
2.4.1
Human Factors
Abha (2007) stated human nature and human behavior are the most significant
determinants of productivity include both their ability as well as their willingness to
work. Motivation and morale of people are very important factors that determine
productivity. From the small issues like subsidized canteen, company transport, or
working hours until big issues like wage incentive schemes, promotion policy, or union
management relations can affect their working quality and productivity. In this study,
the working hours are taken as possible factor for worker in production line. Either day
shift or night shift can give the best output in term of high productivity and efficiency.
8
2.4.2
Psychological Factors
What is wanted to explain here is about the concentration of workers during early month
and end of month. All knows it is time for workers received their wage on end of month.
Logically of human being, on that time, the workers are feel happy because they can
settle all credits like personnel loan, house loan, or education loan, prepare of groceries
and children education fees. Maybe that time, the do their work and affect of high
productivity compare with early or middle of month. On that time, they had a money
problem occurs insufficient wage and have to loan from friends or relatives. If the minds
not concentrate on works, maybe the quality output decreases same as the productivity.
This is the subject that can take as reliable factors to analyze how much it can influence.
2.5
Statistical Approach
In a book by Arce R.G (2005) part of statistical branch revolves around deriving
information about the properties of random processes from sets of observed samples. A
general objective for statistical study is to investigate causality especially to correlate the
effect of changes in the parametric values to the responses. As mentioned by Chatfield
C. (1995), it is most helpful to construct a model which provides a mathematical
representation of the given situation for the most of the statistical based investigation.
The model should provide an adequate description of the given data in order to enable
prediction and other inferences to be made. In general, the statistical approach can be
divided into three categories:
a) Statistical model
b) Empirical model
c) Mathematical model
9
2.5.1
Statistical Model
Chatfield C. (1995) described that a statistical model normally contains one or more
systematic components as well as a random or stochastic element. The random element
is sometimes referred to as noise. This element arises for various reasons and it is
sometimes helpful to differentiate between:
a) Measurement error
b) Natural random variability
The natural random variability occurs due to the difference between experimental units
and from changes in experimental circumstances that cannot be controlled. As for the
systematic components, it is sometimes refers to as signal. In the engineering point of
view, statistical analysis can be regarded as extracting information about the signal in
the presence of noise.
2.5.2
Mathematical Model
A mathematical model can be described as theoretical model that uses mathematical
language to explain the behavior of a system. Among the forms of a mathematical model
are theory model, differential equation and dynamic system. However, mathematical
model are not just limited his alone. Mathematical model is able to overlap with other
models involving an array of abstract structure. In mathematical model, there are six
basic groups of variables:
a) Decision variables
b) Input variables
c) State variables
10
PRODUCTION YIELD ANALYSIS OF AN AUTOMOTIVE
COMPONENT USING GENERAL LINEAR MODEL
This report submitted in accordance with requirement of the Universiti Teknikal
Malaysia Melaka (UTeM) for the Bachelor Degree of Manufacturing Engineering
(Manufacturing Management) with Honours.
by
MUHAIZAD BIN MUHIYDDIN
FACULTY OF MANUFACTURING ENGINEERING
2010
UNIVERSITI TEKNIKAL MALAYSIA MELAKA
BORANG PENGESAHAN STATUS LAPORAN PROJEK SARJANA MUDA
I
TAJUK: Production Yield Analysis of An Automotive Component Using General Linear
Model
SESI PENGAJIAN: Semester 2 2009/2010
Saya MUHAIZAD BIN MUHIYDDIN
mengaku membenarkan Laporan PSM ini disimpan di Perpustakaan Universiti Teknikal
Malaysia Melaka (UTeM) dengan syarat-syarat kegunaan seperti berikut:
1. Laporan PSM adalah hak milik Universiti Teknikal Malaysia Melaka dan penulis.
2. Perpustakaan Universiti Teknikal Malaysia Melaka dibenarkan membuat salinan untuk
tujuan pengajian sahaja dengan izin penulis.
3. Perpustakaan dibenarkan membuat salinan laporan PSM ini sebagai bahan pertukaran
antara institusi pengajian tinggi.
4. **Sila tandakan (/)
D
D
0
(Mengandungi maklumat yang berdarjah keselamatan atau
kepentingan Malaysia yang termaktub di dalam AKTA RAHSIA
SULIT
RASMI 19n)
(Mengandungi maklumat TERHAD yang telah ditentukan oleh
organisasi/badan di mana penyelidikan dijalankan)
TERHAD
TIDAK TERHAD
Disahkan oleh:
Ｈｲａｎ ｾ＠
(TANDATANGAN PENYELIA)
PENULIS)
Alamat Tetap:
NO. 93, JLN 10/21,
Cop Rasmi: AB RAH AN BIN AH 0 00
Pensyar•hKa"an
ｆｴｾ ｫｵｬｴｩ＠
Keiuruter'lan Pembuatan
Universiti Teknikal Malaysia Melaka
Perumahan Bakti 1,
81700 Pasir Gudang, Johor
Tarikh:
'lt;{ c; /20 lO
Tarikh:
r-.
ｲ ｪｲｊ
c.J./
ｾ＠
/ {()
----------------------------------------------
- Jika Laporan PSM ini SULIT atau TERHAD, sila lamplrkan surat darlpada pihak berkuasa/organisasi
berkenaan dengan menyatakan sekali sebab dan tempoh laporan PSM ini perlu dikelaskan sebagai
SUUT atau TERHAD.
DECLARATION
I hereby, declared this report entitled "PSM Title" is the results of my own research
except as cited in references.
Signature
ﾷｾ
ﾷ＠
Author's Name
MUHAIZAD BIN MUlllYDDIN
Date
'J..c; jr; I 'J-.o I D
.........................................
APPROVAL
This report is submitted to the Faculty of Manufacturing Engineering ofUTeM as a
partial fulfillment of the requirements for the degree of Bachelor of Manufacturing
Engineering (Manufacturing Management) with Honours. The member of the
supervisory committee is as follow:
(Signature of Supervisor)
(Official Stamp of Supervisor)
A8 RAHMAN .IN MAHMOOD
ｾｳｹ｡ｲｨ＠
K.n.,
ｾｮ
Fakulti Kejuruteraan Pe!nWatan
ｬ ｶｴｲｬｩ＠
Ttkniktl Mt!IYIIa ｾ＠
ABSTRACT
Every day the manufacturing company calculated the output and yield in order to
measure the capability of production line in certain time. This study used General Linear
Model (GLM) approach in order as a technique to make an analyzing of the possible
factors that contributes to the yield. The production output data was used to gathering
information about the situation that may happen on production line and to know the
possible factor that may effect to yield. The analyzing will be done by using the Minitab
software so that can know the significant of each factors that selected and what factors
and interaction of factor will give an effect for the yield.
i
ABSTRAK
Setiap hari syarikat pembuatan akan mengira jumlah keluaran dan kadar hasil untuk
mengukur prestasi pengeluaran berdasarkan masa tertentu. Di dalam penyelidikan ini,
pendekatan teknik ‘General Linear Model’ digunakan untuk menganalisis faktor-faktor
berkemungkinan yang memberikan kesan kepada kadar hasil. Data jumlah hasil
pengeluaran setiap hari syarikat digunakan untuk mengumpul maklumat supaya boleh
diketahui keadaan yang berlaku di dalam kilang dan untuk mengenalpasti faktor-faktor
yang menyumbang pengaruh kepada kadar hasil. Analisa dibuat dengan mengunakan
perisian Minitab dan signifikan setiap faktor yang dipilih dapat diketahui.
ii
DEDICATION
To my parent who gives me a support and remind me to always be strong in a life to
assault all the challenges in front.
iii
ACKNOWLEDGEMENT
This project and report writing has been culmination for my studies in Universiti
Teknikal Malaysia Melaka (UTeM). Many challengers have been faced during project
completion but at the same time it has been very interesting and rewarding.
Now that I am finishing this project, I would like to express my gratitude especially to
my supervisor, Mr. Ab. Rahman bin Mahmood for his constructive comments, ideas,
supports and guidance for this project.
Besides that, I would like to give my warmest thanks to the various people in Hicom
Engineering Sdn. Bhd. who had contributed their cooperation. Without they valuable
and professional comments and criticism and outright support this would not have been
possible.
Last but not least, thanks to my family and my friends for their endless support and
energy they have given to me during this project and my studies.
iv
TABLE OF CONTENT
Abstract
i
Abstrak
ii
Dedication
iii
Acknowledgement
iv
Table of Content
v
List of Tables
viii
List of Figures
ix
List Abbreviations
x
1. INTRODUCTION
1
1.1
Background of Study
1
1.2
Problem Statement
2
1.3
Objectives
2
1.4
Scope
3
1.5
Background of Company
3
2. LITERATURE REVIEW
4
2.1
Manufacturing
4
2.2
Productivity in Manufacturing
5
2.3
Factor Effecting Productivity
7
2.4
Possible Factors
8
2.4.1
Human Factors
8
2.4.2
Psychological Factors
9
2.5
Statistical Approach
9
2.5.1
Statistical Model
10
2.5.2
Mathematical Model
10
2.5.3
Empirical Model
11
2.6
General Linear Model Overview
12
v
2.7
General Linear Model Core Equation
13
2.7.1
Additional Assumptions of General Linear Model
14
2.7.2
Least Square Estimate for The General Linear Model
14
2.7.3
Sum of Squares
15
2.7.4
Sampling Distributions of the Sum of Squares
16
2.8
Limitations of the General Linear Model
17
3.
METHODOLOGY
19
3.1
Introduction
19
3.2
Planning of Study
19
3.2.1
Process Flow Diagram (PFD)
20
3.2.2
Gantt Chart
22
3.3
Projek Sarjana Muda (PSM) Methodology
22
3.3.1
Methods
22
3.3.1.1 Observation
22
3.3.1.2 Archival Collection
23
3.3.2
26
Materials
3.3.2.1 Books
26
3.3.2.2 Historical Data
26
3.3.2.2 Minitab Software
26
3.3.3
Procedures
27
4.
RESULT AND DISCUSSION
29
4.1
Introduction
29
4.2
Data Collection
29
4.3
Minitab Result
36
4.4
Analysis on Result
37
4.4.1
Factor Table
37
4.4.2
Analysis of Variance Table
38
4.4.3
S, R-Sq and R-Sq(adj) Values
39
4.4.4
Unusual Observation Table
40
vi
4.4.5
Least Squares Means
41
4.4.6
Tukey Method
42
4.4.6.1 Confidence Interval
43
4.4.6.2 Hypothesis Test
48
4.4.7
Normplot of Residuals for Yield Graph
55
4.4.8
Residuals versus Fits for Yield Graph
57
4.4.9
Residuals Histogram for Yield Graph
59
4.4.10 Residuals versus Order for Yield Graph
61
4.4.11 Main Effects Plot (fitted means) for Yield Graph
63
4.4.12 Interaction Plot (fitted means) for Yield Graph
65
5.
CONCLUSION
67
5.1
Overview of the Study
67
5.2
Limitations
68
5.3
Recommendation
68
REFERENCES
69
APPENDICES
71
vii
LIST OF TABLES
3.1
Gantt chart for PSM I
24
3.2
Gantt chart for PSM II
25
4.1
Data need to be key-in at Minitab
32
4.2
Factor Table
37
4.3
Analysis of Variance Table
38
4.4
Result of S, R-Sq and R-Sq(adj) Values
40
4.5
Unusual Observation Table
40
4.6
Least Squares Means Table
41
4.7
Adjusted P-values table for Month
49
4.8
Adjusted P-values table for Week
51
4.9
Adjusted P-values table for Shift
51
4.10
Adjusted P-values table for Hour 1
52
4.11
Adjusted P-values table for Hour 2
52
4.12
Adjusted P-values table for Hour 3
53
4.13
Adjusted P-values table for Hour 4 until 9
53
viii
LIST OF FIGURES
3.1
Planning process flow chart
21
3.2
Correlation of methodology to achieved the objectives
28
4.1
Example of PSPC data from the company
30
4.2
New data converted from PSPC data
31
4.3
Step (i)
33
4.4
Step (ii)
33
4.5
Step (iii)
34
4.6
Step (iv)
34
4.7
Step (v)
35
4.8
Example of a General Linear Model’s result from Minitab
36
4.9
Confidence Interval for Month
43
4.10
Confidence Interval for Week
45
4.11
Confidence Interval for Shift
45
4.12
Confidence Interval for Hour
46
4.13
Example of normal probability plots patterns
55
4.14
Normal Probability Plot of the Residual Graph
56
4.15
Example of residuals versus fitted values plots patterns
57
4.16
Residuals versus the Fitted Values Graph
58
4.17
Example of Histogram patterns
60
4.18
Histogram of the Residuals
60
4.19
Example of residual versus order plots patterns
61
4.20
Residual versus Order for Yield Graph
62
4.21
Main Effect Plot for Yield
64
4.22
Interaction Plot for Yield Graph
66
ix
LIST OF ABBREVIATIONS
ANCOVA
-
Analysis of Covariance
ANOVA
-
Analysis of Variance
DOE
-
Design of Experiment
GLM
-
General Linear Model
ISO
-
International Organization of Standardization
PFD
-
Process Flow Diagram
PSM I
-
Projek Sarjana Muda 1
PSM II
-
Projek Sarjana Muda 2
PSPC
-
Production Shift Productivity Control
UPH
-
Unit per Hour
USD
-
United States Dollars
SPC
-
Statistical Process Control
x
CHAPTER 1
INTRODUCTION
This chapter presents the background of the project, problem statement, objective and
scopes of the project. Background of the project describes about the project. Problem
statement states the reason for execute the project. The objectives of the project are the
aim of the project and the scopes explains about the limitations of the project.
1.1
Background of Study
This study is to analyze an optimum performance of machining line productivity when
running mass production. However, the factors such as working shift or any relevant
factor was identified that can influence the production performance like efficiency and
product quality. Using the General Linear Model (GLM), the factors can be manipulated
intentionally so that can access and understand the impact based on historical data of
production.
1
1.2
Problem Statement
The design and setting up of production is normally done based on predetermined
parameter which is extracted from theoretical information on the process sequence or
flow. The assumption is done as a result of the study on part drawing supplied by
customers.
Once the production line was commissioned, it will be tested to verify its capacity and
performance especially on Unit per Hour (UPH) and the consistency of the dimension.
This finding is discovered after performing test run and pre-production simulation. From
the result also can validate whether the actual result example capacity and quality is in
accordance with design assumption.
Adjustment on workspace design or man-machine chart is reviewed if the production
line doesn‟t meet the requirement of predetermined design, for example UPH and
minimum reject rate. However, the adjustment of production line it seems impossible
and can influence the output per day of company and also lead to company loss.
1.3
Objectives
The objectives of this study are:
1. To understand the General Linear Model theory and apply it into problem
statement
2. To study which possible factors that can affect the production yield
3. To do analyze the possible factors and production yield by using Minitab
software
2
1.4
Scope
The focus of this study is to analyze the possible factors and production yield to
measuring the performance one of selected production line. The others production line
not include in this study. The analyzing will be done using the GLM function on Minitab
software.
1.5
Background of Company
This study is done at Hicom Engineering Sdn. Bhd. machining area of production line.
Hicom Engineering is a member of DRB-HICOM group of companies, offering state-of
art manufacturing capabilities to customers. This company is do manufacture, machine
precision castings, and assemble components for automotive and general engineering
purposes. Located in Shah Alam, Selangor, Malaysia, Hicom Engineering was
commissioned in 1991 with a total paid-up capital of USD 8.07 million and a total
investment of over USD 18.4. As one of Malaysian leading manufacturers of cast-iron
automotive components, they have a strong commitment to constantly improve the
quality of our products. The MS ISO 9002 certification enhanced their spirit with utilize
the latest technological to provide the highest quality in castings.
Hicom Engineering employs a diverse group of dedicated individuals with extensive
experience in foundry and machining. Our employees are committed to the growth of
the company and to achieving consistent quality for every product. Everyone at Hicom
Engineering is responsible to contribute for total quality approach at providing products
that meet and exceed customer satisfactions.
3
CHAPTER 2
LITERATURE REVIEW
This chapter describes about literature review of the study which relates to the scope of
the study. Mostly, it covering elements of factors where contribute to manufacturing
productivity and efficiency. Sources of information were obtained from journals, books,
case studies, reports and also electronic-media sources are collected and compiled
together.
2.1
Manufacturing
Manufacturing has been practiced for several thousand years, beginning with the
production of stone, ceramic, and metallic articles. Much of manufacturing remained for
centuries as essentially individual activity, practiced by artisan and their apprentices.
The ingenuity of successive generations of artisan led to the development of many
process and great variety of product, but the scale of production is limited by the
available power (Schey, 2000). Manufacturing is an industrial activity that changes the
form of raw materials to create products by adding value. To be profitable, an enterprise
establishes and nurtures a manufacturing system that facilities the flow of information to
coordinate inputs, process and output. Development of modern manufacturing, for
example, is dependent on research I materials that may require a variety of new
production processes (Ostwald, 1997).
4
According to Quirk (1999) in manufacturing, there have four basic elements that
represent the manufacturing resources required to produce a product. They are:
i.
Labour
ii.
Methods
iii.
Machines
iv.
Materials
These elements are the building blocks of a process ant together create an infrastructure
that supports manufacturing both directly and indirectly. On one hand, understanding
these different element can help simplify the manufacturing concept. The elements
represent the specific aspects of manufacturing that should be used efficiency: fewer
labor, less equipment, less time and material required. This efficiency increases the
value in the product, which helps meet the goal for competitive manufacturing. In this
study, it focuses on the effectiveness labor utilization in order to improve current
productivity.
2.2
Productivity in Manufacturing
Most organizations would like to find the recipe for the ultimate productivity
improvement strategy. However, those same organizations that are searching for this are
likely to have found them unable to take full advantage of the methodologies and
techniques so far tried. Part of this is because many of them simply do not understand
what productivity really means. Productivity can be defined as the application of the
various resources (inputs) of an organization, industry or country, in order to achieve
certain planned and desired results (outputs). Productivity measurement entails a
comparison of outputs to inputs normally by calculation of a productivity index
(output/input ratio). Productivity improvement thus becomes the establishment of
approaches to improve this productivity index (Baines, 1997).
5
According to Stenevson (2007), productivity is an index that measures output (good and
services) relative to the input (labour, materials, energy, and other resources)
used to produce them. It is usually expressed as the ratio of output to input:
Productivity = Output
Input
A productivity ratio can be computed for a single operation, a department, an
organization, or an entire country. In business organization, productivity ratios are used
for planning workforce requirements, scheduling equipment, financial analysis and other
important task.
In the same way, Mukherjee (2006) stated that productivity is defined as the ratio of
output to input within a defined time period with due consideration for quality.
Productivity = Output (within a defined time and quality)
Input
Based on above formula, it can be elaborated as follows:
i.
Both output and input should be quantified in tangible monetary terms for correct
assessment.
ii.
Productivity implies effectiveness and efficiency in individual and organizational
performance. Here, the „effectiveness‟ means the achievement of the set
individual and the organization target or the objective whereas „efficiency‟ input
ratio is the output input ratio or the value addition to input resources minus the
cost of value addition.
iii.
Managers should clearly know their goals and those of the organization to
ascertain whether they are productive or not.
Besides, productivity also defined as a ratio of output to input which a process of
continuous improvement in the production/supply of quality output/service through
efficient, effective use of inputs, with emphasis on teamwork for the betterment of all.
6
Productivity is the belief in human progress. It is an attitude that seeks the continuous
improvement of what exists. It is a conviction that one can do better today than
yesterday, and that tomorrow will be better than today. Furthermore, it requires constant
efforts to adapt economic activities to ever-changing conditions, and the application of
new theories and new methods. It is a firm belief in the progress of humanity (NPCC,
2008)
2.3
Factor Effecting Productivity
Productivity is outcome of several interrelated factors, which can broadly be divided into
two main categories where human factors and technological factors. Human factors are a
human nature and human behavior is the most significant determinants of productivity.
Human factors include both their ability as well as their willingness to work. Ability to
work means a productivity of an organization depends upon the competence and caliber
of its people-both workers and managers. Ability to work is governed by education,
training, experience, attitude, etc. of the employees. For the willingness to work explain
on motivation and morale of people are very important factors that determine
productivity. These are affected by wage incentive schemes, labour participation in
management, communication systems, informal group relations, promotion policy,
union management relations, quality of leadership, working hours, sanitation,
ventilation, subsidized canteen, company transport, etc. While, technology factors are
the factors exert significant influence on the level of productivity. These include the
following:
i.
Size and capacity of plant
ii.
Product design and standardization
iii.
Timely supply of materials and fuel
iv.
Rationalization and automation measures
v.
Repairs and maintenance
7
vi.
Production planning and control
vii.
Plant layout and location
viii.
Materials handling system
ix.
Inspection and quality control
x.
Machinery and equipment used
xi.
Research and development
xii.
Inventory control
There also another factor that contributes the efficiency of productivity is
managerial, natural environment, sociological, political and also economic (Abha,
2007).
2.4
Possible Factors
From the factor that effecting of productivity explanation, this study can take the human
factors, technical factors, and sociological factors as possible factors that can affect the
production line output quality and productivity.
2.4.1
Human Factors
Abha (2007) stated human nature and human behavior are the most significant
determinants of productivity include both their ability as well as their willingness to
work. Motivation and morale of people are very important factors that determine
productivity. From the small issues like subsidized canteen, company transport, or
working hours until big issues like wage incentive schemes, promotion policy, or union
management relations can affect their working quality and productivity. In this study,
the working hours are taken as possible factor for worker in production line. Either day
shift or night shift can give the best output in term of high productivity and efficiency.
8
2.4.2
Psychological Factors
What is wanted to explain here is about the concentration of workers during early month
and end of month. All knows it is time for workers received their wage on end of month.
Logically of human being, on that time, the workers are feel happy because they can
settle all credits like personnel loan, house loan, or education loan, prepare of groceries
and children education fees. Maybe that time, the do their work and affect of high
productivity compare with early or middle of month. On that time, they had a money
problem occurs insufficient wage and have to loan from friends or relatives. If the minds
not concentrate on works, maybe the quality output decreases same as the productivity.
This is the subject that can take as reliable factors to analyze how much it can influence.
2.5
Statistical Approach
In a book by Arce R.G (2005) part of statistical branch revolves around deriving
information about the properties of random processes from sets of observed samples. A
general objective for statistical study is to investigate causality especially to correlate the
effect of changes in the parametric values to the responses. As mentioned by Chatfield
C. (1995), it is most helpful to construct a model which provides a mathematical
representation of the given situation for the most of the statistical based investigation.
The model should provide an adequate description of the given data in order to enable
prediction and other inferences to be made. In general, the statistical approach can be
divided into three categories:
a) Statistical model
b) Empirical model
c) Mathematical model
9
2.5.1
Statistical Model
Chatfield C. (1995) described that a statistical model normally contains one or more
systematic components as well as a random or stochastic element. The random element
is sometimes referred to as noise. This element arises for various reasons and it is
sometimes helpful to differentiate between:
a) Measurement error
b) Natural random variability
The natural random variability occurs due to the difference between experimental units
and from changes in experimental circumstances that cannot be controlled. As for the
systematic components, it is sometimes refers to as signal. In the engineering point of
view, statistical analysis can be regarded as extracting information about the signal in
the presence of noise.
2.5.2
Mathematical Model
A mathematical model can be described as theoretical model that uses mathematical
language to explain the behavior of a system. Among the forms of a mathematical model
are theory model, differential equation and dynamic system. However, mathematical
model are not just limited his alone. Mathematical model is able to overlap with other
models involving an array of abstract structure. In mathematical model, there are six
basic groups of variables:
a) Decision variables
b) Input variables
c) State variables
10