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REDUCING LEAKING PROBLEMS OF
MOTORCYCLE RADIATORS USING DMAIC IN PT.X
By
Ruben Arya
ID No. 004201100001
A Thesis presented to the
Faculty of Engineering President University in partial
fulfillment of the requirements of Bachelor Degree in
Engineering Major in Industrial Engineering
2015
i
THESIS ADVISOR
RECOMMENDATION LETTER
This thesis entitled “REDUCING LEAKING PROBLEMS OF
MOTORCYCLE RADIATORS USING DMAIC
IN PT.X” prepared and submitted by Ruben Arya in partial
fulfillment of the requirements for the degree of Bachelor Degree in
the Faculty of Engineering has been reviewed and found to have
satisfied the requirements for a thesis fit to be examined. I therefore
recommend this thesis for Oral Defense.
Cikarang, Indonesia, February 16th
, 2015
Anastasia Lidya Maukar, ST., MT.
ii
DECLARATION OF ORIGINALITY
I declare that this thesis, entitled “REDUCING LEAKING
PROBLEMS OF MOTORCYCLE RADIATORS USING DMAIC
IN PT.X” is, to the best of my knowledge and belief, an original piece
of work that has not been submitted, either in whole or in part, to
another university to obtain a degree.
Cikarang, Indonesia, February 16th
, 2015
Ruben Arya
iii
REDUCING LEAKING PROBLEMS OF
MOTORCYCLE RADIATORS USING DMAIC IN PT.X
By
Ruben Arya
NIM. 004201100001
Approved by
Anastasia Lidya Maukar, ST., MT. Ir. Andira, MT.
Thesis Advisor I Thesis Advisor II
Herwan Yusmira B.SC. MET. MTech
Head of Study Program for Industrial Engineering
iv
ABSTRACT
PT X. as a company that produces motorcycle radiator is having a quality issue.
The defective percentage of the product has exceeded the allowed percentage
which is 5%. Most of the defective radiator is leaking, so the company needs to
reduce the number of leaking radiator. To solve the problem, a research using Six
Sigma DMAIC is done. The first step of DMAIC is Define which in this step the
problem and the factors that are critical to quality are identified. Measure is the
second step in DMAIC where the current quality is measured. The third step is
Analyze, in this step; the causes of leaking are shown using Fishbone Diagram,
and FMEA the causes are the wrong flux concentration and the lack of inspection
of the parts. Improvement is the fourth step where the improvements that are
determined from the previous step are applied to the system. The last step of
DMAIC is control; this step will show the result of the improvement, the result is
the reduction of defective percentage from 5.63% to 3.77 %. From the result of
the DMAIC, it can be concluded that the DMAIC has successfully reduce the
number of leaking radiator.
Keywords: Six Sigma, DMAIC, radiator leaking, SIPOC Diagram, FMEA, Pareto
Chart, Fishbone Diagram
v
ACKNOWLEDGEMENT
This report is without a doubt almost impossible to be finished without any
support. Therefore, I would like to give my thanks to:
God, thank you for Your blessings that gave me strength to finish this thesis.
My Family, my father, mother and sister for all the love, support and care.
President University. Thank you for assisting me and giving me the
opportunity to learn and broaden my knowledge.
Ms. Anastasia Lidya Maukar and Ms. Andira, my thesis advisors who
supports guide me during the making of this thesis.
My Lecturers, thank for the guidance and knowledge you all have given to
me.
To my classmates Novando, Zevin, Adhi, Paul, Andreas, Jimmy, Ainul, Fajar,
Yudi, Mirwan, Ryan, Andy, Sun, June, Silvia, Bonnie, Veronika, Aldo, Ivan,
Kevin, Henry, Faizin, Nathalia, Tara, Feberyca, Crisselda, Dwito, Vena, Nia,
Riski, Lita, Yasti, Esti, Angga. My former classmates Sahlul, Apris, April,
Jack, Ramzie, Ingga, Raven, Color. My friends from another major Michael,
Yuda, Albert, Nico, Fadli, Daniel, Feri, Christian, Ricky, Aldo, Chandra,
Khawasi, Ani, Kevin, Zahid, Darren, Hendy, Fikri, Kristantho, Derry, Rayhan,
Adrian, Johnson, Zakharia, Yosua, Vincent, Anthony, Benaya, Andrew,
Herry, Rebecca, Riany, Ckendyh, Kriswanto, Dila, Devita, Dlya, Felix, Arbi,
Donny, Calvin, Melvin, Dimas, Joses, and My high school friends and other
colleagues whose names are too many to mention, thank you for the time and
kindness on every single day of my life. I wish all of you have a successful
future.
vi
TABLE OF CONTENTS
THESIS ADVISOR RECOMMENDATION LETTER ......................................... i
DECLARATION OF ORIGINALITY ................................................................... ii
APPROVAL PAGE .............................................................................................. .iii
ABSTRACT ........................................................................................................... iv
ACKNOWLEDGEMENT ...................................................................................... v
TABLE OF CONTENTS ....................................................................................... vi
LIST OF TABLES ................................................................................................. ix
LIST OF FIGURES ................................................................................................ x
LIST OF TERMINOLOGIES ................................................................................ xi
CHAPTER I INTRODUCTION ............................................................................ 1
1.1. Problem Background ................................................................................ 1
1.2. Problem Statement ................................................................................... 2
1.3. Objectives ................................................................................................. 2
1.4. Scope ........................................................................................................ 3
1.5. Assumption ............................................................................................... 3
1.6. Research Outline ...................................................................................... 3
CHAPTER II STUDY LITERATURE ................................................................... 5
2.1 Six Sigma ................................................................................................. 5
2.2 DMAIC .......................................................................................................... 6
2.2.1 Define...................................................................................................... 6
2.2.2 Measure ................................................................................................... 6
2.2.3 Analyze ................................................................................................... 6
2.2.4 Improve ................................................................................................... 7
2.2.5 Control .................................................................................................... 7
2.3 DMAIC Tools ................................................................................................ 7
2.3.1 SIPOC Diagram ...................................................................................... 7
2.3.2. Critical to Quality Analysis ................................................................... 8
2.3.3. Slovin’s Formula.................................................................................... 8
vii
2.3.4. DPMO .................................................................................................... 8
2.3.5. Sigma Level ........................................................................................... 9
2.3.6. Pareto Chart ........................................................................................... 9
2.3.7. Fishbone Diagram ................................................................................ 10
2.3.8. FMEA .................................................................................................. 10
CHAPTER III RESEARCH METHODOLOGY ................................................. 12
3.1. Framework .................................................................................................. 12
3.2. Framework Description .............................................................................. 13
3.2.1. Initial Observation ............................................................................... 13
3.2.3. Problem Identification ......................................................................... 13
3.2.2. Study Literature ................................................................................... 13
3.2.4. DMAIC ................................................................................................ 14
3.2.5. Result Analysis .................................................................................... 15
3.2.6. Conclusion ........................................................................................... 15
3.3 Detailed Framework Explanation ................................................................ 17
CHAPTER IV DATA COLLECTION AND ANALYSIS ................................... 19
4.1. Production Process ..................................................................................... 19
4.2. Data Collection ........................................................................................... 22
4.2.1 Historical Data ...................................................................................... 22
4.2.3 Sample Collection ................................................................................. 23
4.3. DMAIC Analysis ........................................................................................ 24
4.3.1. Define................................................................................................... 24
4.3.2. Measure ................................................................................................ 28
4.3.3. Analyze ................................................................................................ 29
4.3.4. Improve ................................................................................................ 42
4.3.5. Control ................................................................................................. 52
4.4. Result Analysis ........................................................................................... 54
4.4.1. Improvements ...................................................................................... 54
4.4.2. Implementation of Improvements ........................................................ 55
4.4.3. Comparison .......................................................................................... 56
CHAPTER V CONCLUSION AND RECOMMENDATION ............................. 59
5.1. Conclusion .................................................................................................. 59
viii
5.2. Recommendation ........................................................................................ 60
REFERENCES ...................................................................................................... 61
APPENDICES ...................................................................................................... 62
ix
LIST OF TABLES
Table 2.1 DPMO to Sigma Level ........................................................................... 9
Table 4.1 Number of Product and Defective Product per Day ............................. 22
Table 4.2 Defective Percentage............................................................................. 24
Table 4.3 Defect per Unit ...................................................................................... 24
Table 4.4 Defect Occurrences ............................................................................... 27
Table 4.5 Severity Ranking ................................................................................... 32
Table 4.6 Occurrence Ranking .............................................................................. 32
Table 4.7 Detection Ranking ................................................................................ 33
Table 4.8 FMEA Table RPN Ranking .................................................................. 35
Table 4.9 FMEA Table ......................................................................................... 38
Table 4.10 Flux Concentration Trial Result .......................................................... 45
Table 4.11 Defective Percentage after Improvement ............................................ 52
Table 4.12 Defects per Unit after Improvement ................................................... 53
Table 4.13 Current and Improved Performance .................................................... 54
x
LIST OF FIGURES
Figure 2.1 DMAIC .................................................................................................. 7
Figure 2.2 SIPOC Diagram Example ...................................................................... 8
Figure 2.3 Pareto Chart ........................................................................................... 9
Figure 2.4 Fishbone Diagram ................................................................................ 10
Figure 2.5 FMEA .................................................................................................. 11
Figure 3.1 Research Framework ........................................................................... 12
Figure 3.2 Detailed Research Framework ............................................................ 16
Figure 4.1 Radiator Production Flow Chart .......................................................... 20
Figure 4.2 Radiator................................................................................................ 21
Figure 4.3 Leaking Radiator ................................................................................. 21
Figure 4.4 SIPOC Diagram ................................................................................... 26
Figure 4.5 Pareto Chart ......................................................................................... 28
Figure 4.6 Radiator Leaking Fishbone Diagram .................................................. 30
Figure 4.7 Nocolok Flux Packaging ..................................................................... 43
Figure 4.8 Nocolok Flux Powder .......................................................................... 43
Figure 4.9 Nocolok Flux Being Mixed ................................................................. 44
Figure 4.10 Number of leaking radiators .............................................................. 46
Figure 4.11 Regression Summary Report ............................................................. 46
Figure 4.12 Residual vs. Fitted Value ................................................................... 47
Figure 4.13 Regression Analysis .......................................................................... 47
Figure 4.14 Parts Inspection before the Improvement .......................................... 49
Figure 4.15 Parts Inspection after the Improvement ............................................. 51
Figure 4.16 DPMO Comparisons Before and After Improvement ....................... 56
Figure 4.17 Sigma Level Comparisons Before and After Improvement .............. 56
Figure 4.18 Defect per unit Comparisons Before and After Improvement ........... 57
Figure 4.19 Defective Level Comparisons Before and After Improvement ......... 57
xi
LIST OF TERMINOLOGIES
Radiator : Heat transferor used to exchange thermal energy
from one instrument to another for the intention of
cooling and heating.
Defect : A flaw, error in the product or the system that is not
match with the specifications.
Defective : A faulty, imperfect product, a product that has
defects.
Six Sigma : An array of instruments and approach for improving
processes.
DMAIC : In short for Define, Measure, Analyze, Improve and
Control implies to an improvement cycle used for
enhancing, improving and steadying manufacturing
processes and designs.
Defect per Unit : The number of defects occurring in a single unit of
product.
iv
ABSTRACT
PT X. as a company that produces motorcycle radiator is having a quality issue.
The defective percentage of the product has exceeded the allowed percentage
which is 5%. Most of the defective radiator is leaking, so the company needs to
reduce the number of leaking radiator. To solve the problem, a research using Six
Sigma DMAIC is done. The first step of DMAIC is Define which in this step the
problem and the factors that are critical to quality are identified. Measure is the
second step in DMAIC where the current quality is measured. The third step is
Analyze, in this step; the causes of leaking are shown using Fishbone Diagram,
and FMEA the causes are the wrong flux concentration and the lack of inspection
of the parts. Improvement is the fourth step where the improvements that are
determined from the previous step are applied to the system. The last step of
DMAIC is control; this step will show the result of the improvement, the result is
the reduction of defective percentage from 5.63% to 3.77 %. From the result of
the DMAIC, it can be concluded that the DMAIC has successfully reduce the
number of leaking radiator.
Keywords: Six Sigma, DMAIC, radiator leaking, SIPOC Diagram, FMEA, Pareto
Chart, Fishbone Diagram
1
CHAPTER I
INTRODUCTION
1.1.Problem Background
Recently, quality became one of the most important things in the industry world;
companies compete with each other by showing the quality of their product to the
customers. Quality of a product became one of the important factors in buying a
product. For some company, quality is what defines them, if the quality of their
product or service is bad; then the company is bad also. Companies invest a lot
just to increase or even maintain the quality of their product or services.
Companies are facing harsh pressure from their competitors to be able to produce
product or service at the highest quality as possible. Thus, quality needs to be
maintained or even increased to a certain level. Most companies are having a hard
time in maintaining their quality because they are not aware of such methods to
maintain the quality of their products or services.
Six Sigma is one of the tools to improve the quality of process output; it uses
quality management methods to identify and remove the cause of defects and
maximizing uniformity in manufacturing and business process. DMAIC is used in
Six Sigma projects to improve existing process.
DMAIC is one of the project methodologies used in Six Sigma that aims in
improving processes in the manufacturing and business. By using DMAIC as the
project methodology in the Six Sigma project, the company can solve the
problems concerning their quality and also other problems occurring in the
company in a structural way.
The automotive industries are one of the biggest industries in Indonesia;
especially for the motorcycle industries since Indonesia is one of the biggest
motorcycle consumers the world. The number of motorcycle in Indonesia in the
year 2013 is 104 million units. This means the people of Indonesia rely on this
2
type of vehicle, because they are a lot cheaper than cars, and easier to use in the
bad traffic in Indonesia especially in Jakarta.
Motorcycle manufacturing consists of long and complicated process. The main
manufacturer will select suppliers to supply them with the motorcycle spare parts
that are requested by the manufacturer then the manufacturer will assemble the
parts that are sent by their suppliers into a unit of motorcycle.
PT. X is one of the major motorcycle radiator distributors for one of the biggest
automotive company in Indonesia. The company sends the motorcycle parts that
they manufacture to the motorcycle manufacturer daily. Currently the company is
facing a problem, the quality of its products are decreasing to a certain level that it
concerns the management. There are lots of reports of leaking radiator. If a
radiator is leaking, it will lose its sole purpose of maintaining temperature and
become unusable.
The company has a policy of having minimum defective percentage of 5% for the
radiator and recently the percentage has exceeded to 6.43%. Since the defective
percentage has exceeded the maximum amount, the company has to do research to
reduce the defective percentage to the desired amount.
1.2. Problem Statement
The background of the problem leads to the statement below
What are the factors that cause the leaking in radiator the most?
What are the solutions to reduce the percentage of the defectives?
1.3. Objectives
The objectives of this research are to:
To determine the major cause of leaking in the radiators.
To determine the solution to reduce the defective radiators by reducing the
number of leaking radiator.
3
1.4. Scope
There is a limitation in this research, such as:
1. The data collection is held on 23rd
of April until 4th
of June 2014 and 14th
of
June until 25th
of July 2014.
2. The data were only taken from one type of radiator.
1.5. Assumption
There are some assumptions that had to be made to support this research, such as:
The motorcycle radiators are inspected in the final inspection station.
The company only produces one product, which is the radiator used in the
research.
1.6. Research Outline
Chapter I Introduction
This chapter consists of the problem background, problem
statement, objectives, scope, assumptions, and the research outline.
Chapter II Literature Study
This chapter focuses on the literatures and theories that are related
to the research that will help the writer to conduct the research.
Chapter III Research Methodology
Research methodology explains about the steps and the methods
used to finish the research.
Chapter IV Data Collection and Analysis
This chapter provides the data, calculation, and the analysis that
will be used to find the solution of the problems. The literatures in
chapter 2 will be used to build this chapter. The Analysis in this
chapter will be done according to the five steps in DMAIC.
4
Chapter V Conclusion and Recommendation
The last chapter explains the conclusion of this research, the result
from data analysis and the problem background will be shown to
determine whether the research has solve the problem or not, this
chapter also mentions some recommendations needed for future
research.
The Introduction of the research has that consists of problem background,
problem statement, objectives, scopes, assumptions, and research outline has been
discussed above, the next chapter will discuss about the literature study that will
support the research.
5
CHAPTER II
STUDY LITERATURE
2.1 Six Sigma
Six Sigma is an array of instruments and approach for improving processes. Six
Sigma was acquired by Motorola in 1986.
Six Sigma’s purpose is to improve the quality of the output of the process; it could
be product or service, by identifying and eliminating sources of defects and
maximizes uniformity of processes in business and manufacturing. It uses a
arranged of quality management techniques, mainly experimental, statistical
methods, and builds a foundation of people who are experienced in these
methodologies. Each Six Sigma project done in an organization follows a
described order of steps and has calculated value targets. (Tennant, 2001)
The term Six Sigma originates from jargon related with manufacturing, terms
linked with statistical demonstrations of manufacturing processes. A
manufacturing process can be described by a sigma rating showing its percentage
of non-defect products the process makes. A six sigma process with 99.99966% of
all occasions to produce defect free parts and products, this level of defect
resembles to 4.5 sigma levels only.
Six Sigma doctrines stated that:
Non-stopping attempts to obtain steady and predictable process results are
very important to business success.
Manufacturing and business processes have characteristics that can be
measured, analyzed, controlled and improved.
Obtaining maintained quality improvement needs dedication from the
entire company, especially from high level management.
Originally, Six Sigma referred to the capability of manufacturing processes to
manufacture products with very low defect opportunities. Processes that run with
six sigma quality are hoped to produce defectives lower than 3.4 defects per
million opportunities (DPMO) in the long term. Six Sigma's goal is to improve all
6
processes in the manufacturing and business, but not necessarily to the 3.4 DPMO
level.
2.2 DMAIC
DMAIC in short for Define, Measure, Analyze, Improve and Control implies to
an improvement cycle used for enhancing, improving and steadying
manufacturing processes and designs. To run Six Sigma projects, the DMAIC
cycle is a fundamental tool. But, DMAIC is not only for the use of Six Sigma and
can be used as the guides for other improvement of processes and designs.
DMAIC is an acronym of the five steps that consists: Define, Measure, Analyze,
Improve and Control. All of the DMAIC process steps are needed and always
progresses in the designated sequence. (Rusli, 2011)
2.2.1 Define
This step will define the business problem, mission, potential resources, scope and
timeline. This information is obtained within project charter document. How to
define is to note what currently known and obvious. Process the facts, set
objectives and assemble the project group.
2.2.2 Measure
The purpose of this step is to measure the current condition of the system. This
step’s purpose to identify the capability of the process in the company before the
improvement is applied in the system. The calculation in this step is done so in the
Improve step, there are data to be compared to find out how much the system has
been improved by the DMAIC Cycle.
2.2.3 Analyze
The third step in the DMAIC Cycle is the Analyze. This step is done to determine
and identify the root causes of the problems in the system. The tools that are
usually used in this step are Pareto Chart, and Fishbone Diagram.
7
2.2.4 Improve
The fourth step in the DMAIC Cycle is the Improve step where in this step the
improvements to increase the quality if the process is going to be applied. The
steps to implement the improvements will also be mentioned in this part.
2.2.5 Control
In the DMAIC quality improvement program, the fifth and the final step is
Control. In the control step, the measurements of the quality capability of the
system after the improvement are applied in the system. The performance before
and after the implementation will be compared to determine whether the
DMAICC is successful or not, and also to know how much the system has been
improve by implementing DMAIC into the system.
Figure 2.1 DMAIC
2.3 DMAIC Tools
2.3.1 SIPOC Diagram
SIPOC is an abbreviation of suppliers-inputs-process-outputs. A SIPOC diagram
shows broad view of key elements of a process. SIPOC diagram is used at the
beginning of the project to define the key elements in the project (Juran, 1989).
8
Figure 2.2 SIPOC Diagram Example
2.3.2. Critical to Quality Analysis
CTQ or Critical to Quality Analysis is a method of studying a process flowchart to
determine quality features that are important to the item and the customers and to
find the problems that will emerge. The CTQ analysis analyzes the inputs and
outputs and determines the steps that affects the inputs and outputs the most.
(Brown, 2002)
2.3.3. Slovin’s Formula
Slovin’s Formula is a formula to calculate a sample size of a calculation. The
formula is presented below. (Altares, 2003)
) ) (2-1)
2.3.4. DPMO
In the projects of process improvement efforts, DPMO or Defect Per Million
Opportunities is a measurement of process performance. DPMO implies for the
number of defect that happen in a product on a million chances. The calculation of
DPMO is presented in the equation below:
(2-2)
9
2.3.5. Sigma Level
Sigma level is the error rate of a process in the manufacture or business, it is
obtained through DPMO. The Sigma Level is a future approximation of a process,
including a 1.5 sigma shift that would happen over a longer period of time. The
1.5 sigma shift is an estimate of Sigma level of a process that is industrially
standardized. Table 2.1 will show give long term DPMO to short term Sigma
Level. (El-Haik, 2005)
Table 2.1 DPMO to Sigma Level
Sigma level Sigma (with
1.5σ shift) DPMO
Percent
defective
Percentage
yield
1 -0.5 691,462 69% 31%
2 0.5 308,538 31% 69%
3 1.5 66,807 6.7% 93.3%
4 2.5 6,210 0.62% 99.38%
5 3.5 233 0.023% 99.977%
6 4.5 3.4 0.00034% 99.99966%
7 5.5 0.019 0.0000019% 99.9999981%
2.3.6. Pareto Chart
Pareto Chart is a bar graph that the length of the bar symbolizes cost or frequency,
and arranged in order from longest to shortest from left to right. Thus it shows the
factors that are more significant to the less significant one. (Burr, 1990)
Figure 2.3 Pareto Chart
10
2.3.7. Fishbone Diagram
The Fishbone diagram or Cause-and-Effect diagram or Herringbone diagram or
Ishikawa diagram is a diagram that is usually used to solve problems; it can also
build a brainstorming session. The common uses of fishbone diagram are for
product design and preventing defects. The Fishbone diagram is used when
determining causes of a problem. (Ishikawa, 1990)
Figure 2.4 Fishbone Diagram
2.3.8. FMEA
FMEA or Failure Mode and Effect Analysis is a way to determining the failures in
a process, product, or service. Failure modes mean the ways object will fail. The
failures are any defects or errors occurred in the object, especially the errors that
affects the customer and are potential. Potential effects of failure explain about the
effects of the failure modes. (Stamatis, 2003)
The failure modes are ordered on how serious their magnitudes are (Severity),
how often they happen (Occurrence), and how detectable are the failure modes
(Detection). The goal of FMEA is to do activities to reduce or eliminate the failure
modes, starting with the ones with the highest RPN or Risk Priority Number,
which is calculated by multiplying the values of severity, occurrence, and
detection.
11
Figure 2.5 FMEA
FMEA is used to prevent failures, and later it is used for controlling the system
before and during the operation of the process. FMEA is ideally used when a
product, process, or service is being made or revised, when a product, process, or
service is being run in a new way, and before making control plans for a process
that has been improved.
The second chapter which is the study literature; which consists of literatures that
will support has finished. The next chapter will discuss about the research
methodology, the framework that will explain about the flow of the research.
12
CHAPTER III
RESEARCH METHODOLOGY
3.1. Framework
The figure below will explain about the procedure of the research
Figure 3.1 Research Framework
Problem
Identification
Identifying the problem
Finding the research materials, objectives, scopes, and
assumptions
Study
literature Six Sigma
DMAIC
DMAIC Tools
Data
Collection
Conclusion
Analysis
Collecting the necessary data for Define and Measure
data for DMAIC
Collecting production and defective data
Collecting samples for control charts
Analyze the data collected, define the process in the
company, measure the current condition, analyze the
problems, find the solution and control the improvement
using DMAIC.
Analyzing the result of DMAIC
Compare the result of analysis with the objectives of the
research
Summarize the results of analysis
Conclude the research
Give recommendations
Initial
Observation Historical data
Production Process
Product and defective product
13
3.2. Framework Description
3.2.1. Initial Observation
The data that will be mainly collected are the data for Define and Measure step of
the DMAIC, the number of product and the number of defective products. The
data will be collected by taking samples, the sample size it determined by using
Slovin’s formula, after the sample size is known, the data for measurement and
control can be collected, the data are the defective percentage and the defect per
unit. Also the product example and the process flowchart will be also shown is
this step.
3.2.3. Problem Identification
The research is initiated from the wish to improve the quality of the motorcycle
radiator in PT.X. It is important to know the problem so the research can be done
with a purpose. The problem background is obtained by doing observation in the
field, asking operators and managers about the issues in the plant. It is known that
from the reports from the operators that there are reports of radiator leaking and
other reports of defective radiator, a leaking radiator means that the radiator will
be unusable, the occurrence of the defect are quite frequent that it makes the
defective percentage of the radiators exceeded its maximum, the company is
concerned about this problem so that it is decided to do research to reduce the
defective percentage of the radiator, especially reducing the number of leaking
radiator. This chapter also includes the research objectives, scopes, assumptions
and research outline.
3.2.2. Study Literature
The purpose of this chapter is to collect theoretical base from books, journal, and
other sources that will support the research. Several literatures are used in the
research in order to conduct the research properly.
14
3.2.4. DMAIC
3.2.4.1. Define
This step will explain about the process where the cycle is being implemented at,
it explains the process of how the product is made, other factors that influences
the product, and the critical factors for the quality of the product. Using SIPOC
Diagram, the production process and the other factors that coexist with it can be
identified, and using CTQ, the factors that are critical to the quality of the
motorcycle radiator can be determined, and then the pareto chart is made to
determine the defectives with most frequent occurrence.
3.2.4.2. Measure
The second step is Measure where in this step the current condition of the product
is measured by control charts and defect percentage. The data collected earlier
will be used to, calculate the DPMO (Defect Per Million Opportunities), Sigma
Level, and defective percentage will be measured to determine the current
system’s output quality. DPMO and Sigma level are used as the basic scoring in
Six Sigma, so it is used to support the condition.
3.2.4.3. Analyze
The third step is the Analysis phase where the measurements and calculations that
are done in the past step are analyzed to obtain the solutions. The first tool that is
used in this chapter is the fishbone diagram which will identify the root causes of
the defectives on the motorcycle radiators, the third is the FMEA where the root
problems are analyzed and ranked based on the rankings of RPN or rank priority
number to determine which root cause needs to be eliminated the most, then the
recommended actions will be applied and the recalculated rank priority number
will be shown to determine if the root cause has been successfully minimized.
After the analysis is done, the next step in the DMAIC is Improve.
3.2.4.4. Improve
Improve is the step where the solutions that have been collected from the precious
steps are implemented in the system to improve the current system. There are also
15
improvements that not have implemented in the company yet, due to resource
limitation of the company.
3.2.4.5. Control
The last step in the DMAIC method is Control, where the improved condition is
checked and compared to the condition before the improvement using the same
tools from Measure step which are P chart and U chart to determine whether the
process is in control or not; DPMO, Sigma Level, and defective percentage to
present the quality of the product produced by the system after the improvements
are implemented. From that comparison it can be determined whether the
implementation of DMAIC in the system is successful or not.
3.2.5. Result Analysis
After the result from DMAIC has been obtained and the improvement has been
implemented in the system, it will be analyzed. The quality of the system before
and after the DMAIC has been implemented is compared. A graph will be used of
compare the result of quality level.
3.2.6. Conclusion
After the data have been analyzed, and the results have been found. The results of
the research are compared with the objectives of the research then the conclusions
can be made in order to finish the research. Recommendations for the company
that will assist the company regarding quality issues will also be mentioned in this
chapter.
16
Fig
ure
3.2
D
etail
ed R
esearc
h F
ram
ewo
rk
17
3.3 Detailed Framework Explanation
After the initial data are obtained, the analysis to improve the system and lower
the number of leaking radiator is begun. The research started with the reports from
the production line that the radiators are leaking it will influence the company.
The fact that the radiator leaking is a concern is also supported by the historical
data of the defective radiators, the company regulation that does not allow the
defective percentage to exceed 5 % of the radiators produced, and also by
interviewing the operators, line supervisors, and managers. After that the data is
taken to prove that the leaking radiators are occurring often by taking samples and
field observation.
First, the method to analyze have to be decided, the option is whether to use
PDCA or DMAIC, but in the end DMAIC is used because DMAIC is better to be
used at an existing process and system, since it provides more thorough analysis
of the current system and the other factors that influences the production of the
radiator.
The DMAIC Analysis begins with Define, the first step where in this step, SIPOC
Diagram, CTQ, and Pareto Chart will be used. Using SIPOC Diagram, the
production process and the other factors that coexist with it can be identified, and
using CTQ, the factors that are critical to the quality of the motorcycle radiator
can be determined, and then the pareto chart is made to determine the defectives
with most frequent occurrence.
Then the second step of DMAIC is Measure, where in this step the current quality
level of the system is measured by calculating the DPMO, Sigma Level, and
Defective percentage.
The third step is Analysis, in this step, the root causes of the leaking will be
determined by using Fishbone Diagram, and the causes that have to be prioritized
to be eliminated will be obtained using FMEA Analysis. Then the selected
recommended actions obtained from the FMEA will be will be applied and
measured in the next step, which is Improve.
Improve is the fourth step in DMAIC, in this step, the improvement actions found
in the previous step, which is Analyze will be applied in the system. The first
improvement is to change the concentration of the radiator flux, to find the right
18
concentration, brazing trials using different flux concentration is used and the
result will be analyzed using Quadratic Regression to find the most suitable
concentration. The second improvement is to add parts inspection station before
the parts are sent to the production line and in the production line to prevent
defective parts to be used for the radiator assembly, and to reduce the number of
leaking radiators.
The fifth and the last step of DMAIC is Control, in this step, the system after the
improvements are implemented are measured again to determine how much the
system has improved, and to know whether the problems in the system have been
solved or not. The measurements used in this step are the same as the
measurements used in the Measure step; the measurements are DPMO, Sigma
Level, and Defective Percentage. After the measurements are known and
compared to the measurements of the system before the actions are implemented,
it is determined that the current system has improved, the leaking in the radiators
are reduced, and the problem in the system has been solved.
The research methodology has been explained above, for the next chapter the data
collection and analysis will be explained.
19
CHAPTER IV
DATA COLLECTION AND ANALYSIS
4.1. Production Process
The radiator production is started from the radiator core. The core assembly is
started with the formation of radiator fin from aluminum fin. The aluminum
sheets are formed into a zigzag form using the fin forming machine.
The next step is to assemble the radiator core, the radiator fins and tubes are
assembled on top of a radiator plate, starting with fin, then tube, and then fin again,
the process is repeated until 20 fins and 19 tubes are laid on top the plate, then it
will be topped with another plate, then the reinforce plates will be inserted on both
side.
Since the reinforce will only hold the end parts of the radiators, the middle part of
the radiator will be held by steel bars, to prevent the fins to slide out of the core
during transfers.
After that the radiator is sent to the oil dry oven machine where the oils on the
radiator core from the core assembly machine process are dried in the oven for the
next step in the radiator assembly. After the oils on the radiator are dried out, the
radiators are coated with aluminum flux; aluminum flux is aluminum mixture that
will solidify under high temperature.
After the radiator cores are coated with flux thoroughly, it is sent to the brazing
machine where the flux will become solid and strengthen the bond between the
radiator parts. After the cores are out of the brazing machine, the excess flux will
be scraped, and then cores are sent to the clenching machine.
In the clenching machine, the radiator, the upper and lower tanks are assembled
to the core. Then drain cock is inserted to the lower tank, after that the radiators
are sent to the air leak and water leak test, after the radiators are tested, they are
dried and then sent to the next station for base and cover assembly.
20
The radiators are completely assembled and then they are sent to the final
inspection station. The radiators that passed the final inspection will be packed
and sent to the outgoing storage waiting to be delivered to the customer.
Figure 4.1 Radiator Production Flow Chart
21
The radiator is shown in figure 4.1 below.
Figure 4.2 Radiator
But among the radiator produced, there are defective radiators, most of the
defective radiators are leaking radiators, the leaking radiator is presented in figure
4.3 below
Figure 4.3 Leaking Radiator
22
Radiator is a heat transferor that is used for cooling and heating. The motorcycle
radiator is used to cool down the engine; a coolant is passed through the engine,
where the coolant absorbs heat from the engine. The heated is sent to the tank of
the radiator, and then it is sent across the radiator tubes to the tank on the opposite
end of the radiator. As the hot coolant passes through the tubes, it transfers heat to
the tubes and radiator fins, and then the fins release heat into the air. Lastly the
cooled coolant is sent back to the machine. The radiator prevents the machine
from overheating.
If a radiator is leaking, coolant will drop out of the radiator, then the machine
won’t be supplied with the cooled coolant and the machine will overheat. So, if
the radiator is leaking, it will lose its sole purpose and is unusable. That is why
leaking radiator is a concern in producing radiators.
4.2. Data Collection
4.2.1 Historical Data
To find out the existence of the problem, initial observation is done. The initial
observation is started with the number of defective data of the last two month of
the radiator making process. From the data of the radiator produced and the
number of defective in the last two months, it is determined that the current
system has a quality problem. The full data is shown in appendix 1 while the
partial data is shown in table 4.1
Table 4.1 Number of Product and Defective Product per Day
Day Number of
Product
Defective
Product
1 537 21
2 523 15
3 563 35
4 602 52
5 532 41
6 521 16
7 585 54
8 572 51
9 616 31
10 542 27
23
By dividing the number of radiator produced and the number of defective product,
the defective percentage is determined and the result is 6.43%, the defective
percentage of the current system, is higher than the maximum defective
percentage allowed by the company which is 5%, the company is concerned about
that problem and has decided to do a project to reduce the number of defective
radiators. The operators and the production supervisors in the company also stated
that the number of leaking radiators has increased in the past two months. Since
there are too many reports of defective followed by reports of leaking radiators, a
research to reduce the number of leaking radiators has to be made.
4.2.3 Sample Collection
The data collection is done by taking samples of the radiator being inspected, how
many defects are there in one sample and the number of defects on the sample.
The number of occurring defects is also collected for the pareto chart later.
The population is the number of radiators produced in the last two months. Hence,
the population is 22722. The full data is shown in appendix 1.
The sample size is determined by Slovin’s Equation, the equation is shown in
equation 2-1:
Minimum sample size =
= 393.
Therefore the sample size taken for the research is rounded up to 400 and the
number of sample is 30.
The defectives and the number of defects per units are presented in appendix 2
and 3. The partial data is presented in table 4.2 and 4.3.
The sample size is 400, how to calculate the defective percentage is by dividing
the number defective by the sample size and multiply it by 100, and then the
defective percentage is obtained. For example, how to calculate the defective
percentage of sample number 7 is by dividing 20 by 400 and multiply the result
with 100, and then the result of defective percentage of 5 percent is obtained.
24
The equation is shown below:
Table 4.2 Defective Percentage Sample
No.
number
of
defectives
Defective
Percentage
1 8 (8/400)*100 =2
2 20 5
3 16 4
4 16 4
5 24 6
6 40 1
7 20 5
8 28 7
9 36 9
How to calculate defect per unit is by dividing the sum of all the occurrences by
the sample size. For example to calculate defect per unit of sample number 6 is by
dividing 72 by 400, and then the result of defect per unit 0.18 is obtained.
Table 4.3 Defect per Unit
Sample Defects
per Unit
1 0.03
2 0.1
3 0.08
4 0.09
5 0.15
6 0.18
7 0.12
8 0.16
9 0.17
10 0.07
4.3. DMAIC Analysis
4.3.1. Define
In this step there are several things to describe, such as: the product and the
process in making a motorcycle radiator, making SIPOC diagram to describe the
25
sequence of the processes, defining the Critical to Quality (CTQ) factors for the
motorcycle radiator assembly, and making pareto chart based to know which
Critical to Quality causes the most case of defective product,.
In the automotive industry, especially the motorcycle assembly, not all of the
motorcycle parts are assembled in one plant, some motorcycle producers would
have supplier for assemble motorcycle parts, for example the radiator.
There are several processes in making motorcycle radiators, the first step is to
assemble the radiator core, the radiator fins and tubes are assembled on top of a
radiator plate, starting with fin, then tube, and then fin again , the process is
repeated until 20 fins and 19 tubes are laid on top the plate, then it will be topped
with another plate, then the reinforce plates will be inserted on both side, since the
reinforce will only hold the end parts of the radiators, the middle part of the
radiator will be held by steel bars, to prevent the fins to slide out of the core
during transfers.
After the cores are assembled, they will undergo brazing to solidify their assembly,
but before that, the cores will go through the oil dry oven to remove the excess
oils from previous processes.
Before the cores are put into the brazing machine, they are covered with nocolok
flux, nocolok flux are liquid mixture that will react with aluminum under high
heat, nocolok flux will solidify if exposed to high heat and will strengthen the
bond between the radiator core parts.
After the cores are out of the brazing machine, they are sent to the next station
where the tank upper, tank lower, and the drain cock are inserted to the core. Next
the radiators will undergo two leak tests, the first is the air leak test, and the
second one is the water leak test.
If the radiator failed the air leak test, it will be sent to the water leak station to
determine the point of leaking; the same goes to the radiators that passed the air
leaking test, just to make sure that the radiator is not leaking.
26
After the radiators have passed the two leaking tests, the plastic base and the steel
cover are assembled to the radiator. The radiators that have been fully assembled
will go to the final inspection station before packed for delivery.
How to obtain these steps in making the radiator is by observation, asking the
operators and managers about the radiator making, and reading the SOP in the
stations.
After the steps to make the product are known, the next step is to identify what
other factors that coexist with the radiator assembly, to determine that, SIPOC
diagram will be used.
The SIPOC Diagram is presented in figure 4.4.
Figure 4.4 SIPOC Diagram
The SIPOC diagram in figure 4.4 shows the correlation and the interaction
between processes. First the suppliers which are Aluminum supplier, plastic parts
suppliers, and steel parts supplier, the suppliers sent the items bought by the
company which will be used as the inputs.
The inputs are the materials that will be used to assemble the radiators, the inputs
are radiator fins, radiator plate, radiator reinforce, upper and lower plastic tanks,
plastic bases, aluminum covers, drain cocks, seal packs, and O – Rings.
The inputs will be put into the radiator making process which consists of core
assembly, brazing process, tank upper and lower insertion, air and water leak tests,
27
base and cover insertion, and final inspection and thus the radiator was fully
assembled and ready for delivery as the outputs.
The customers that are receiving the radiators from the company are motorcycle
producers and motorcycle producers that have selected PT. TSI as the radiator
supplier for their motorcycles.
The requirements that the customers demand are excellent quality that will satisfy
them and also punctuality on the product delivery.
Critical to Quality factors that have been identified for radiator products are: the
uniformity of the fins, the dents on the radiator tubes, the leaking in the radiator,
and the scratches on the plastic tanks. These factors will be used for determining
defectives, making pareto chart.
Pareto chart is used to compare the number of occurring defectives and
determining which defect has the highest number of occurrence so the
improvement can be focused on eliminating that defect. Figure 4.5 is the pareto
chart of the defectives found on the defectives. Table 4.4 represents the number of
occurring defectives that is inserted to the pareto chart.
Table 4.4 Defect Occurrences
Defect Total
Occurrences
Leaking 824
Dents 464
Scratches 256
Fin defect 172
From table 4.4 above, it is shown that the leaking has the highest number of
occurrences of defect occurring in the radiators produced in the company
compared to dents, scratches, and fin defects. To see how much does leaking
occurred compared to the other, pareto chart is used.
28
Figure 4.5 Pareto Chart
From the figure 4.5, it is known that most of the defectives in the radiator is the
leaking in the radiator, followed by dents, scratches, and fin defect, since 48% of
the defects are leaking; the cause of that defectives has to be known in order to be
able to find the right solution to reduce the number of leaking radiators.
4.3.2. Measure
In the second step of DMAIC, which is Measure there are several things to be
done such as, collecting the defective product data, and calculating the quality
level before improvement which is determined using Defect Per Million
Opportunities (DPMO) or Part Per Million (PPM), sigma level, and defective
product percentage. The data used for the equation in this step is the number of
defective product, and the number of items taken for sample, the data is shown in
appendix 2, while the partial data is shown in table 4.2.
How to calculate DPMO is by multiplying one million with the number of
defective product, and then divide it with the number of samples times the defect
opportunities per unit, since there 4 CTQ factor in the radiator, it is counted as an
opportunity. The calculation of DPMO based on equation (2-2) is shown below:
48%
75%
90%
100%
0%
20%
40%
60%
80%
100%
120%
0
100
200
300
400
500
600
700
800
900
Leaking Dents Scratches Fin defect
29
To calculate the sigma level, the DPMO will be divided with one million and then
use NORMSINV function in Microsoft Excel to return the value to the inverse of
the standard cumulative, and then add the value with 1.5 sigma shift. From that
calculation, the result sigma level of 3.69 is obtained.
To calculate the defective percentage is to divide the number of defects with the
total sample taken. The calculation is shown below:
After the calculation, it is known that the DPMO is 14083.33, compared to the
ideal Six Sigma DPMO value which is 3.688; the current DPMO value is still
very high. The current sigma level is 3.695, which is low compared to the ideal
level which is six. The percentage of defective is 5.63% while the company only
allows 5% of defective, so the current percentage is quite high. The DPMO, sigma
level, and the defective percentage will later be compared with the data after
improvement to determine whether the improvement is successful or not.
4.3.3. Analyze
The third step in DMAIC program which is analyze is done to discover and
identify the source of the defectives. In this step the activities that will be done are
making fishbone diagram to help knowing the cause of defectives, and filling the
Failure Mode Effect and Analysis table to help prioritize
4.3.3.1. Determining the Root Cause Using Fishbone Diagram
The method to find the root causes of each defect is by using fishbone diagram.
The first fishbone diagram describes the root causes of the leaking in the radiator,
there are no root cause from method and material factor. The fishbone diagram is
presented in figure 4.6.
30
Fig
ure
4.6
R
ad
iato
r L
eak
ing F
ish
bon
e D
iag
ram
31
The Fishbone diagram presented in figure 4.6 describes the root causes of the
defect that causes half of the defects in the radiator, which is leaking radiator.
Human factors contribute in the cause of the leaking in radiator. The operators
may use defective tubes in the core assembly; the operators with improper training
do not understand the parts measurements table and may use a tube with false
specification in the assembly core. The same thing also happens when an operator
with lack of training and understanding of the Standard Operation Procedure
forgot to insert the O – ring on the drain cock, it will cause the radiator to leak in
the drain cock. When an operator was too exhausted that person may have
knocked the radiator off the table where the radiator is being operated and will
break the radiator causing it to have dents and leaks.
From the measurement factor, the causes of defect is from the size of the tube and
the reinforce, if the size of the tube is too small or the size of the reinforce hole is
too large, it will make a small hole in-between the joint of the reinforce and tube,
thus the radiator will be leaking.
The root cause of the defect coming from the management size is by not checking
the tubes before the tubes are sent to the production plant, so the broken tubes are
used by the operators and the radiator will leak.
From the machine factor, the root cause of defect is from the flux spray machine
and the radiator core assembly machine. In the flux spray machine, the defect is
caused by the wrong concentration of the flux, and the flux blower. The wrong
concentration of flux, if the flux is too thick will make the flux not coat the
corners of the core thoroughly and will make holes on the corners of the radiators
where the flux is not applied. The radiator may also be leaking because of the flux
blower has too much power so it will blow too much flux and when there is not
much flux applied on the radiator, the brazing process won’t be effective and the
radiator will have small holes and will leak.
4.3.3.2. Identifying the Prioritized Causes Using FMEA
After the root causes are identified, the next move is to make the FMEA table. By
making the FMEA table, the failure mode causes can be analyzed and it will help
32
deciding the correct response and decrease the number of occurring failures.
FMEA also shows the RPN and will help prioritize which causes of defectives
that should be lessen first.
Before the FMEA table is made, rating thresholds needed to be identified, below
is the rating rankings of the three factors that affects the RPN of the FMEA, the
factors are Severity, Occurrence, and Detection. The ratings are presented in table
4.5, 4.6, and 4.7.
Table 4.5 Severity Ranking
Rating Meaning
1 Very Minor, no damage
2 Noticed by average customer, low
damage
3 Moderate damage
4 Critical, loss of primary function
How to determine the severity is by knowing how much the potential cause will
affect the product the cause is not eliminated. Low rating such as 1 means that the
potential cause will not affect the product much, it may not give any effect at all to
the end product; high rating such as 4 means that the end product may not work if
the failure is happening, the product will lose its purpose and become useless.
Table 4.6 Occurrence Ranking
Rating Meaning
1 Extremely unlikely
2 - 3 Rare
4 -5 Occasionally
6 - 7 Usually
8 - 9 Often
10 Certain
To determine the Occurrence rating is by identifying of often does the potential
cause occurs in the defective cases of the product. Low rating means the potential
cause occurs rarely or even very unlikely to happen, if the rating is high, that
means that the potential cause is often occurs, it may be certain to cause the
failure mode.
33
Table 4.7 Detection Ranking
Rating Meaning
1 Certain
2 - 3 Almost certain
4 -5 Easy
6 - 7 Moderate
8 - 9 Difficult
10 Undetected
Detection rating is identified by knowing how easy it is to detect the potential
cause, if it is easy to detect or certain to detect the cause, the rating will be low, if
the rating is high, it means the cause if difficult to detect or it may be undetected.
The FMEA table is made and assessed by the researcher and the colleagues and
the managers from the company where the researcher is doing his internship. First
the potential causes are sorted based on the RPN.
Table 4.8 sorts the potential causes from the causes from the cause with the
highest RPN to the lowest RPN to determine which causes needed to be
eliminated.
The severity ratings of the causes are all the same because the potential causes all
leads to the same failure mode, which is leaking radiator, the severity of a leaking
radiator is 4, the highest score because when a radiator is leaking, the radiator lost
its primary function to cool down the coolant for the machine and its rendered
useless.
The occurrence ratings are determined by how often do the causes occur in the
leaking of the radiator, the causes with the occurrence of 6 means that the causes
usually occurs if there is a leaking in the radiator, for example the causes “flux too
thick” and “broken pressure gauge” usually become the cause of leaking radiators.
The causes with 4 to 5 are causes that occasionally occur when there is a leaking;
the causes are “parts are not checked before sent to the production plant”, “flux
blower too strong”, and “the O-ring is not inserted to the drain cock”.
34
The causes with 2 to 3 are causes that rarely occur when there is a leaking; the
causes are “improper training of product knowledge”, “operator dropped the
radiator”, and “reinforce hole size too big”.
How to determine the detection rating of a potential cause is by knowing how
detectable the causes are. The causes with detection rating of 6 to 7 is the causes
with a moderate difficulty of detection, it needs a thorough checking to detect the
problem, the causes are “flux too thick”, and “parts are not checked before sent to
the production plant”.
Detection rating of 4 to 5 means the causes can be detected by an observation, the
causes that are easy to detect are, “broken pressure gauge”, and “the O-ring is not
inserted to the drain cock”.
While the causes with the detection rate of 2 to 3 are the ones that can be detected
just by looking, the causes are “flux blower too strong”, “improper training of
product knowledge”, “operator dropped the radiator”, “tube size too small” and
“reinforce hole size too big”.
After all the severity, occurrence, and detection are all obtained, the values of the
three rating are multiplied and then the RPN or the Risk Priority Number are
obtained, RPN shows which potential causes needs to be prioritized to be
eliminated first, the higher the RPN the number the more influential the potential
cause to the leaking in the radiators. How to calculate RPN is by multiplying the
value of Severity, Occurrence, and Detection of a potential cause, for example to
calculate the RPN of the cause Flux too thick is by multiplying 4, 6 , and 7, then
the result is known by PRN = 168.
From the sorting of RPN value, the causes can be sorted on three categories based
on the value of RPN. The causes with RPN value from 1 to 50 is considered as
minor cause, causes with RPN value from 51 to 100 will be considered as
moderate cause, and the causes with more than 100 RPN will be determined as
major cause.
35
Table 4.8 FMEA Table RPN Ranking
Process
Step/Input
Potential
Failure Mode
Potential Failure
Effects
SE
VE
RIT
Y
Potential Causes
OC
CU
RE
NC
E
Current Controls
DE
TE
CT
ION
RP
N
Radiator
assembly
Radiator
leaking
Customer very
dissatisfied
4 Flux too thick, the flux cannot cover all
the small holes on the radiator, so the
radiator will leak. The company still uses
the old concentration for the new
product.
6 Flux content indicator 7 168
Radiator cannot be
used
4 Parts are not checked before sent to the
production plant that causes the defective
product to be sent to the production plant
and used by the operators to assemble the
radiator, if defective parts are used in the
assembly, the finished goods will also
defective.
5 Standard Operational
Procedure
6 120
Company loses money 4 Broken pressure gauge makes the
pressure of the core assembly machine is
too low, which makes the reinforce do
not attached to the tubes properly,
causing the radiator to have holes in the
joint between the reinforce and the tubes.
6 None 4 96
4 The O-ring is not inserted to the drain
cock before the drain cock is inserted to
the radiator, so the air can get into the
radiator through the drain cock and
causes the radiator to leak
4 Briefing every Monday 4 64
35
36
Table 4.8 FMEA Table RPN Ranking (Continued)
Process
Step/Input
Potential
Failure Mode
Potential Failure
Effects
SE
VE
RIT
Y
Potential Causes
OC
CU
RE
NC
E
Current Controls
DE
TE
CT
ION
RP
N
4 Flux blower too strong, it blows the flux
too much, so there is not much flux on
the radiator for the brazing process
5 None 2 40
4 Improper training of product knowledge,
that causes the operator cannot
distinguish which parts that is good or
defective
3 None 2 24
4 Reinforce hole size too big, resulting in
holes in the radiator
2 Sending staff to the
supplier
3 24
4 Tube size too small, resulting in holes in
the radiator
2 Sending staff to the
supplier
3 24
4 Operator dropped the radiator that caused
by fatigue because of dehydration
3 None 1 12
36
37
After the RPN of the causes are identified, the causes are sorted by the categories
based on the RPN. The minor causes are “flux blower too strong”, “improper
training of product knowledge”, “operator dropped the radiator”, “tube size too
small” and “reinforce hole size too big” presented with the yellow color, although
the “flux blower too strong” occasionally occurs, since the detection of the
potential cause is rated as easy, the cause is assigned as minor cause because the
RPN is less than 50.
The moderate causes are “broken pressure gauge”, and “the O-ring is not inserted
to the drain cock” presented by the orange color.
The major causes, the causes that highly influences the leaking in the radiators are
“flux too thick”, and “parts are not checked before sent to the production plant”
presented by the red color.
By sorting the causes into categories based on their RPN, the potential causes with
the most influence in causing leaking radiator can be known so it can be
eliminated.
After the potential causes are determined, categorized, and sorted based on the
Risk Priority Number, the recommended actions for each potential causes. How to
obtain the recommended actions is by observations, brainstorming, and consulting
with the managers and the supervisors. The recommended actions then are going
to be implemented in the company to reduce the number of leaking radiators.
The recommended actions given may give significant results in short time after
the actions are done or maybe after a long time after the improvements have been
repeatedly done.
The actions mentioned in the FMEA table shown in table 4.8 are the actions that
are agreed to be done by the supervisors and managers of the company.
38
Table 4.9 FMEA Table
Process
Step/Input
Potential
Failure
Mode
Potential
Failure
Effects
SE
VE
RIT
Y
Potential Causes
OC
CU
RE
NC
E
Current
Controls
DE
TE
CT
ION
RP
N
Action Recommended
Radiator
assembly
Radiator
leaking
Customer
very
dissatisfied
4 Flux too thick, the flux
cannot cover all the
small holes on the
radiator, so the
radiator will leak. The
company still uses the
old concentration for
the new product.
6 Flux content
indicator
7 168 change the flux concentration to the correct
concentration that is suitable and determine
the correct concentration for the product for
future use
Radiator
cannot be
used
4 Parts are not checked
before sent to the
production plant that
causes the defective
product to be sent to
the production plant
and used by the
operators to assemble
the radiator, if
defective parts are
used in the assembly,
the finished goods will
also defective.
5 Standard
Operational
Procedure
6 120 Take samples from outgoing parts to be
measured the day before. Before the parts
are sent to the plant, there are samples taken
from the parts to be visually examined by
the quality staffs to make sure the parts are
fit to be used in the radiator assembly. If the
samples fail the quality test, the new batch
of parts that has passed the quality test will
be sent to the plant while the batch of parts
that failed the test will be sorted out first
before sending them to the plant
38
39
Table 4.9 FMEA Table (Continued)
Process
Step/Input
Potential
Failure
Mode
Potential
Failure
Effects
SE
VE
RIT
Y
Potential Causes
OC
CU
RE
NC
E
Current
Controls
DE
TE
CT
ION
RP
N
Action Recommended
Company
loses money
4 Broken pressure gauge
makes the pressure of
the core assembly
machine is too low,
which makes the
reinforce do not
attached to the tubes
properly, causing the
radiator to have holes
in the joint between
the reinforce and the
tubes.
6 None 4 96 Change the pressure gauge of the core
assembly machine, buy a new pressure
gauge, and check the pressure of the core
assembly machine more often. Do a
maintenance check on all the core assembly
machines.
4 The O-ring is not
inserted to the drain
cock before the drain
cock is inserted to the
radiator, so the air can
get into the radiator
through the drain cock
and causes the radiator
to leak
4 Briefing every
Monday
4 64 Ensure that all of the operators understand
the SOP, train and supervise new operators
regularly. Brief the operators on Monday
and Thursday
39
40
Table 4.9 FMEA Table (Continued)
Process
Step/Input
Potential
Failure
Mode
Potential
Failure
Effects
SE
VE
RIT
Y
Potential Causes
OC
CU
RE
NC
E
Current
Controls
DE
TE
CT
ION
RP
N
Action Recommended
4 Flux blower too
strong, it blows the
flux too much, so there
is not much flux on the
radiator for the brazing
process. The blower is
then known to be
broken
5 None 2 40 Change the flux blower pipe, since it was
broken. While waiting for the new pipe to
come, the old pipe is widened so the air
coming out of it has less power
4 Improper training of
product knowledge,
causes the operator
cannot distinguish
which parts that is
good or defective
3 None 2 24 Brief the operators more often, give
trainings to operators on how to handle the
radiator better, train and supervise new
operators regularly.
4 Reinforce hole size too
big, resulting in holes
in the radiator
2 Sending staff
to the supplier
3 24 send staffs to suppliers to oversee the items
more often so the items that are going to be
sent to the company have better quality
40
41
Table 4.9 FMEA Table (Continued)
Process
Step/Input
Potential
Failure
Mode
Potential
Failure
Effects
SE
VE
RIT
Y
Potential Causes
OC
CU
RE
NC
E
Current
Controls
DE
TE
CT
ION
RP
N
Action Recommended
4 Tube size too small,
resulting in holes in
the radiator
2 Sending staff
to the supplier
3 24 send staffs to suppliers to oversee the items
more often so the items that are going to be
sent to the company have better quality
4 Operator dropped the
radiator that caused by
fatigue because of
dehydration
2 None 1 8 Adding water dispensers in the plant to the
places that the operators can reach easier,
encourage operators to drink more and keep
hydrated.
41
42
The improvements done in the moderate and minor causes are long term actions
that will give results after the improvements are implemented for a long time for
example: the recommended action for operator forgot to put the O – ring in the
drain cock is by training the new operator and tightened the supervision, the
recommended action for fixing the parts with false measurements is by sending
staffs to the suppliers regularly so they can check the quality of the items before
the items are sent to the company, also the solution for broken pressure gauge is
by buying a new one, those actions cannot give results directly after they are
implemented so they will not be analyzed in the next step, thus, the improvements
that are going to be analyzed are the ones that can give results in a short time after
the recommended action is done.
The improvements that are going to be analyzed are the improvements of the
major causes, because the major causes are the prioritized causes that are going to
be eliminated by the company and the actions done to eliminate the causes can
give results in a short time.
4.3.4. Improve
Improve is the fourth step in DMAIC, where in this step the improvements for the
system is implemented in the system. The RPN result from the FMEA table shows
that there are potential causes that have a high influence of causing a leaking
radiator, the causes are “flux too thick”, and “parts are not checked before sent to
the production plant”, the recommended actions done in those causes are able to
give results in a short time, so the improvement actions to reduce those causes
will be analyzed. To be able to improve process, the potential causes’ RPN must
be reduced or even eliminated.
4.3.4.1. Changing Flux Concentration
The first improvement is to reduce the leaking radiator occurrence by finding the
right flux concentration. Nocolok flux is a powder or liquid based material
consists of mainly aluminum, the flux is mainly used in brazing process to
strengthen the bonds of parts coated in the flux. Figure 4.7 is the picture of the
flux packaging, figure 4.8 shows the flux powder, and figure 4.9 shows the flux
liquid being mixed.
43
Figure 4.7 Nocolok Flux Packaging
Figure 4.8 Nocolok Flux Powder
44
Figure 4.9 Nocolok Flux Being Mixed
The current concentration of flux is 0.6. The company initially used 0.6 as the flux
concentration because the 0.6 concentration was the flux concentration used in the
previous product of radiator produced in the company, the concentration of 0.6 is
deemed suitable for the previous type of radiator, the previous type did not have
problems using 0.6 as the flux concentration, so the company don’t see why that it
cannot be used for the current, as it turns out that the flux concentration of 0.6
causes a lot of leaking on the current radiator product, the company have to find
the new right concentration.
The concentration is obtained by comparing the weight of flux powder and water
used in the mixture, if the flux concentration is 0.6 it means the content of the flux
or Aluminum powder compared to the whole mixture is 6 to 10. The flux
concentration of 0.6 is too thick to be sprayed on the radiators.
To find the right concentration, brazing trials using 16 different consistencies are
done. Each concentration will be applied into five racks of radiators. The
temperature of the brazing machine, the speed of brazing machine conveyor, the
measurements of the parts used in the radiator, and the flux blower pressure are
the same applied to all the radiators in the trial, the difference is only the flux
concentration used to coat the radiator. After the brazing process, the racks of
radiators are sent to the leaking test machines to be tested whether the radiator
45
leak or not. One radiator rack consists of 6 radiators. So there are 30 radiators
used for each concentration. The result of the trial is shown in table 4.10.
Table 4.10 Flux Concentration Trial Result
Flux
Concentration
Number of
Leaking
Radiators
0.575 17
0.550 15
0.525 12
0.500 11
0.475 8
0.450 7
0.425 5
0.400 4
0.375 3
0.350 3
0.325 5
0.300 6
0.275 7
0.250 10
0.225 12
0.200 13
The radiators with flux concentration of 0.6 is leaking because the flux is too thick
and cannot reach the small joints of parts on the radiator, while the radiators with
flux concentration of 0.2 has leaking because the flux is too runny and dripping
out of the radiator while in the brazing machine, thus leaving small holes in the
cracks. From the result of the trial the flux concentration which produces the least
number of leaking radiators are 0.35 and 0.375 with 3 leaking radiators. To find
the concentration that will produce zero number of leaking radiators, an equation
that represents the relationship between the number of leaking radiator and the
flux concentration has to be obtained. To find the equation, Minitab is used to
evaluate the data using the Quadratic Regression Model.
If the concentration of flux is too low or too high, the number of leaking radiators
will increase, so the most suitable flux concentration must lies in the middle, if the
data in table 4.10 is inserted to a scatter chart shown in figure 4.10, the plots will
form a u- shape similar to the quadratic model.
46
Figure 4.10 Number of leaking radiators
Based on figure 4.10, it can be seen that the most suitable flux concentration is
placed in the middle of the chart and when the data is inserted to the polynomial
regression analysis shown in figure 4.13, the r – square of the model is 96.3%,
which indicates that the data is accountable with the quadratic regression model,
hence, the quadratic regression is used to find the most suitable flux concentration.
Figure 4.11 Regression Summary Report
0
5
10
15
20
0.2 0.4 0.6
Number of Leaking Radiators
0.37
Flux Concentration
Lea
kin
g R
adia
tors
47
Figure 4.12 Residual vs. Fitted Value
Figure 4.13 Regression Analysis
Figure 4.11 shows the fitted line plot of the model, it shows that the model fits the
quadratic regression line. Figure 4.12 shows the residuals compared to the fitted
value of the model, although there are some residuals that are quite far from the
fitted values, there are no large residuals in the data. Figure 4.11 and 4.13 shows
the P – value and the adjusted R – square of the model, the P – value of 0, which
is lower than α = 0.05 means that the model provides a good fit to the data, it also
indicates that the relationship between Number of Leaking Radiators and Flux
48
Concentration is significant. The R – Square of 96.3% means that the flux
concentration accounts for 96.3% of the number of leaking radiators.
Using Quadratic Regression Model, an equation that represent the relationship
between number of leaking radiator and the flux concentration used to coat the
radiator is obtained. The equation is:
This equation can be used to predict Number of Leaking Radiators for a value of
Flux Concentration, or find the settings for Flux Concentration that correspond to
a desired value or range of values for Number of Leaking Radiators. Y represents
the number of leaking radiator and X represents the flux concentration. To
determine the concentration that produces no leaking radiators, the value of Y will
be zero and so the calculation will be:
The value of X that satisfies the equation above is 0.37, so the value of X is 0.37.
Since X represents the flux concentration, according to the equation, the flux
concentration that will results in zero number of leaking radiator is 0.37.
Therefore, it can be determined that the flux concentration that is the most suitable
to be used is 0.37.
If the correct concentration is coated on the radiator, the flux will cover the holes
in the radiator, strengthen the bonds between the radiator core parts, and protect
the radiator from rust. Using the right concentration of flux to be coated on the
radiator will prevent the radiator from leaking, thus lowering the number of
leaking radiators.
4.3.4.2. Parts Inspection
The second improvement is to add an inspection on outgoing parts from the
inventory warehouse to the production plant to prevent the defective parts to be
sent to the production plant and used in the radiator assembly.
Before the parts are sent to the plant, there are samples taken from the parts to be
visually examined by the quality staffs to make sure the parts are fit to be used in
the radiator assembly. If the samples fail the quality test, the new batch of parts
49
that has passed the quality test will be sent to the plant while the batch of parts
that failed the test will be sorted out first before sending them to the plant.
Before the improvement, the parts are only inspected when the parts have just
arrived at the storage, the company did not check the parts again when the parts
are going to be sent to the production line, although the parts may have been
broken during the storing in the storage. In the line, there are no inspections for
the parts also, so the broken parts that are used for assembly will cause the leaking
in the radiator. The flowchart of the parts inspection before the improvements is
shown on in figure 4.14.
YesThe parts are sent
to the plant
Tank Upper
Clinching
Air Leak Test
Drain Cock
Insertion
Water Leak Test Drying
Tank Lower
Clinching
Base Assembly
Cover Assembly
Core AssemblyFin Forming Flux SprayOil Dry Oven
Brazing Machine
Final Inspection
The defective parts
are sent back to
supplier
The parts are
stored
The parts are
received
Are the parts
defective?No
Figure 4.14 Parts Inspection before the Improvement
To improve the condition, the improvement that adds the inspection station before
the parts are sent to the production line is added. The items will be checked and
sorted by the quality staffs, which are idle at that time. The items per box will be
50
checked using random sampling, if the samples are good, the boxes of parts will
be sent to the production line. If the samples are not good, the boxes will have a
full inspection to sort the good parts with the defective parts, and then the good
parts will be compiled to other boxes to be sent to the production line. The other
inspection station is in the production line, it is placed after the clinching process,
before the radiators are sent to the leaking test machines. The parts of the radiator
cores are inspected, if the parts are not good. The core will be inspected on that
station, if not, it will be sent back to be reworked at the station where it can be
reworked. The flowchart of the parts inspection after the improvement is shown in
figure 4.15.
To inspect the parts before the parts are sent, two people from the quality division
will be assigned to inspect the parts that are going to be sent to the production line
and sort the defective parts from the good parts if in the sampling there are
defective parts found, the people are the employee that are on standby and are not
doing any other activity.
The person that will inspect the parts in the radiator and rework the radiator in the
production line if there are defects in the radiator parts are the line supervisor with
another inspector assigned by the supervisor, if the line supervisor is not available,
a senior operator will take place of the supervisor, and the station where the senior
operator is originally working will be manned with another operator assigned by
the supervisor or the manager.
So the total inspectors added in this improvement action is three to four persons
and the persons assigned with this job are the employee with low working time, so
it will not disturb the other processes in the radiator production.
51
The parts are
inspected before
sent to the plant
Are the parts
defective?
Yes
The defective items
are separated from
the good parts
The parts are sent
to the plant
The rest of good
parts are compiled
into one box
Tank Upper
Clinching
Air Leak Test
Drain Cock
Insertion
Water Leak Test
Drying
Tank Lower
Clinching
Base AssemblyCover Assembly
Core AssemblyFin Forming Flux SprayOil Dry Oven
Brazing Machine
Final Inspection
No
The defective parts
are sent back to
supplier
The parts are
stored
The parts are
received
Are the parts
defective?
No
Are there defects in
the parts ?
Yes
The Item is
reworked
No
Yes
Figure 4.15 Parts Inspection after the Improvement
By adding an inspection before the parts are sent to the production plan, the
defective parts can be sorted out to prevent the operators from using defective
parts for the radiator assembly, and to inspect the parts again in the production
line, the defective parts used in assembling the radiators is reduced and the
number of leaking radiators caused by a defect in the parts is also reduced.
52
4.3.5. Control
The fifth and the last point in the Six Sigma DMAIC method is control, where in
this method the results after the improvements are compared to the condition
before the improvements are implemented. The tools that will be used to
determine whether the improvements are successful or not are Defect Per Million
Opportunities (DPMO), sigma level, and defective percentage.
After using the improvements from the previous step, the flux concentration of
0.37 and the addition of inspection station in the system, the defective percentage
and the defect per unit of the radiators produced is obtained again using the same
method as the data collection, which uses 400 sample size and 30 number of
samples. The partial data of the number of defectives and the defective per unit is
shown in table 4.11 and 4.12. The full data is presented in appendix 4 and 5.
How to calculate the defective percentage is by dividing the number defective by
the sample size and multiply it by 100, and then the defective percentage is
obtained. For example, how to calculate the defective percentage of sample
number 5 is by dividing 18 by 400 and multiply the result with 100, and then the
result of defective percentage of 4.5 percent is obtained.
The equation is shown below:
Table 4.11 Defective Percentage after Improvement
Sample
No.
number of
defectives
Defective
Percentage
1 9 (9/400)*100 =2.25
2 13 3.25
3 7 1.75
4 19 4.75
5 18 4.5
6 13 3.25
7 8 2
53
Table 4. 11 Defective Percentage after Improvement (continued)
Sample
No.
number of
defectives
Defective
Percentage
8 18 4.5
9 10 2.5
10 9 2.25
How to calculate defect per unit is by dividing the sum of all the occurrences by
the sample size. For example to calculate defect per unit of sample number 3 is by
dividing 12 by 400, and then the result of defect per unit 0.03 is obtained.
Table 4.12 Defects per Unit after Improvement
Sample
No.
Defects per
Unit
1 12/400 = 0.04
2 0.05
3 0.03
4 0.06
5 0.07
6 0.04
7 0.02
8 0.05
9 0.03
10 0.02
After the defective percentage per sample is obtained, the calculation of DPMO,
Sigma Level, and defective percentage of the system after improved can be done.
The calculation of DPMO based on equation (2-2) is shown below:
To calculate the sigma level, the DPMO will be divided with one million and then
use NORMSINV function in Microsoft Excel to return the value to the inverse of
the standard cumulative, and then add the value with 1.5 sigma shift. From that
calculation, the result sigma level of 3.85 is obtained.
To calculate the defective percentage is to divide the number of defects with the
total sample taken. The calculation is shown below:
54
The data has been collected and the result of the DPMO, sigma level, and the
defective percentage is known. The DPMO of the improved system is 9416.7, the
sigma level is 3.848, and the defective percentage is 3.76 %.
Table 4.13 Current and Improved Performance
Before
improved
After
improved
DPMO 14083.33 9416.67
Sigma Level 3.69 3.85
Defect percentage 5.63 % 3.77 %
Table 4.13 shows that the improved system has lower DPMO, higher sigma level,
and lower defect percentage compared to the before improved system. Lower
DPMO means that in a million chances, it has a lower possibility of the defect to
occur, which is better than having a higher value of DPMO; higher sigma level
means it has become closer to the ideal sigma level which is 6, the improved
system has a defective percentage of 3.77%, it is lower than the defective
percentage before the process is improved and also lower than the maximum
defective percentage allowed by the company which is 5%.
4.4. Result Analysis
This part of data analysis will analyze the result of DMAIC that have been
implemented in the system in order to reduce the number of defective radiator,
especially leaking radiators. The improvement needed for the system has been
implemented in the system and the result is out.
4.4.1. Improvements
There are two improvement actions that have been done to improve the system.
The actions are:
1. Changing the flux concentration into the most suitable concentration and
update the flux concentration chart.
2. Inspecting the parts that are going to be sent to the production plant.
55
4.4.2. Implementation of Improvements
The implementation of the first improvement is by doing a trial using different
flux concentration and finding out which concentration is the best in coating the
radiator thoroughly to prevent the radiator from leaking. The result of the trial and
by using Quadratic Regression, it is determined that the most suitable flux
concentration to be used on the radiator is 0.37. By using 0.37 as the flux
concentration, the flux can cover the small holes in the radiator completely,
preventing the radiator from leaking, so the number of leaking radiator is lowered
by using the right concentration of flux. The implementation will be done by the
operators and the supervisors that is assigned to mix the flux, for the future use,
the production manager and the supervisors are informed with the use of 0.37 flux
concentration as the optimum flux concentration for this type of motorcycle
radiator, so if the new batch of flux is going to be made, the manager and
supervisors will oversee and inform the operator during the mixing of the flux to
make sure that the flux concentration is 0.37.
The second improvement action is done by adding two inspections. First is to
inspect the items before the items are sent to the plant, by doing this, the operators
will have an easier job assembling the radiator because most of the defective parts
are sorted out before the parts are sent to the production plant. Samples are taken
between batches of parts that are going to be sent the day after the inspection. If
the batch failed the inspection, a new batch of parts will be inspected, if the batch
passes, it will sent to the production plant, while the batches who did not pass will
be checked out for defective parts, then the remaining of the failed batch that good
for use will be added to another batch to be sent to the production plant. The
second inspection is done in the production line by the supervisor or a senior
operator accompanied with another operator, where the radiators will be checked
for defects and will be reworked if there are any defects on the parts By adding
these two inspection stations, the number of defective parts used for radiator
assembly will be reduced, thus reducing the number of leaking radiators.
56
4.4.3. Comparison
The result the quality of the radiator will now be compared by a chart to see the
differences between the quality before and after the improvement. The differences
between the quality valuations are presented in figure 4.16, 4.17, 4.18 and 4.19.
Figure 4.16 DPMO Comparisons Before and After Improvement
The DPMO of the system had reduced by almost a third after the improvement
has been implemented in the system. The DPMO before the improvement is
14,083.33 and after the improvement is 9,416.67. The reduction of DPMO by
33.13% indicates that in a million opportunities of production, the chances of the
process creates a defective radiator is reduced by 33.13%.
Figure 4.17 Sigma Level Comparisons Before and After Improvement
14,083.33
9,416.67
0
2000
4000
6000
8000
10000
12000
14000
16000
Before After
DPMO
3.69
3.85
3.6
3.65
3.7
3.75
3.8
3.85
3.9
Before After
Sigma Level
Sigma level increased by
4.16%
DPMO reduced by
33.13 %
57
As for the sigma level of the system, the sigma level has increased by 4.16% from
3.69 to 3.85. The ideal sigma level is 6, so the higher Sigma Level a process has,
the lower the chances of the defect to occur, thus has lower defective percentage.
The process after the improvement has a Sigma Level closer to Sigma Level 6
compared to the process before improvements, so it has a better quality.
Figure 4.18 Defect per unit Comparisons Before and After Improvement
The average defect per unit has decreased by 51.3%, from 0.103 defects per unit
to 0.05 defects per unit. The reduction of the defect per unit indicates that the
defects on the radiators after the improvements have been applied have occurred
less frequently than before the improvements are implemented.
Figure 4.19 Defective Level Comparisons Before and After Improvement
0.103
0.05
0
0.02
0.04
0.06
0.08
0.1
0.12
Before After
Defect Per Unit
Average defect per
unit decreased by
51.3%
5.63
3.77
0
1
2
3
4
5
6
Before After
Defective Percentage Defective percentage
reduced by 33.13 %
58
The defective percentage of the system has lowered significantly from 5.63% to
3.77%. The reduction of the defective percentage is 33.13%. The percentage after
the improvement is lower the maximum percentage allowed by the company, so
the current system is acceptable by the company and the system is good for
production.
Based on the results of the research, it is known that the improvement that is
applied in PT. X has successfully reduced the defectives occurring on the
motorcycle radiators produced in PT. X significantly. The reduction of occurring
defectives also indicates that the quality of motorcycle radiators produced in PT.
X has increased significantly. Based in the statement earlier, it can be said that the
DMAIC that is done in PT. X has successfully improve the quality of radiators in
PT. X.
Based on the results that have been obtained from the previous calculations and
analysis, there are several conclusions that can be made and those conclusions and
some recommendations for future researches will be discussed in the next chapter.
59
CHAPTER V
CONCLUSION AND RECOMMENDATION
5.1. Conclusion
According to the results in the previous chapters, conclusions can be made in
order to solve the problem stated earlier. The conclusions are:
1. The factors that are causing the leaking in the radiators are:
• The flux concentration used in coating the radiator is too thick; the
flux cannot cover all the holes in the radiator.
• The parts are not checked before sent to the production plant, so
defective parts are used in the radiator making process.
2. The solutions to reduce the number of leaking radiators defects are:
• Changing the flux concentration into the most suitable
concentration, so the holes on the radiators are covered by the flux
and preventing the radiator from leaking.
• Adding inspection for the parts that are going to be sent to the
production plant, to reduce the number of defective parts used to
assemble the radiators, then lowering the number of leaking
radiators.
• After the solutions are applied to the system, the DPMO of the
system is reduced from 14.083.33 to 9.416.67, the sigma level
increased from 3.69 to 3.85, the average defect per unit from 0.103
defects to 0.05 defects, and the defective percentage of the radiator
has been reduced from 5.63 %, to 3.77%. From these result, it is
concluded that the implementation of DMAIC in the system has
successfully reduce the number of leaking radiators in PT. X.
60
5.2. Recommendation
There are some recommendations made for future researches. The
recommendations are:
This research only focuses on reducing the radiator defective percentage
by lowering the number leaking radiator. To reduce the percentage of
radiator defective more, other defects in the radiator such as dents and
scratches on the radiators has to be reduced also.
When doing a flux trial for the radiators, try to use as many consistencies
as possible, to obtain more reliable data of which flux concentration is the
most suitable for the radiator.
