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ABSTRACT
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ABSTRAK
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DEDICATION
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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.
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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
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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
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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
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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
4.13 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
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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
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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
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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
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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.
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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
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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
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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.
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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
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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
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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
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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:
