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Lean Six Sigma

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Global Journal of Researches in Engineering: G
Industrial Engineering

Volume 14 Issue 2 Version 1.0 Year 2014
Type: Double Blind Peer Reviewed International Research Journal
Publisher: Global Journals Inc. (USA)
Online ISSN: 2249-4596 & Print ISSN: 0975-5861

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA Approach
By Md. Golam Kibria, Md. Enamul Kabir & S. M. Mahbubul Islam Boby
Khulna University of Engineering &Technology (KUET), Bangladesh
Abstract- Sophisticated customer demands and advanced technology have changed the way of conducting business. Financial condition of a manufacturing company largely depends on the defect rate of a product.
Understanding the key features, obstacles, and shortcomings of the six sigma method allows organizations to better support their strategic directions, and increasing needs for coaching, mentoring, and training. The objectives of this paper are to study and evaluate processes of the case organization, to find out the current sigma level and finally to improve the existing Sigma level through decreasing defects. According to objectives, current sigma level has been calculated, manufacturing process analyzed and suggestions given for improvement. Especially in analyzing phase different analysis tools like Production Layout, Process Block Diagram, Cause and Effect Diagram, Cheek Sheet,
Process control chart are used. FMEA is used as improvement tool. By using this it has been possible to improve productivity by reducing defects rate. This research work has been carried out in a cement manufacturing company to show how to implement Six- Sigma in this type of industry. This research related work does not only apply to cement manufacturing company but also in any other types of organizations. By implementing Six-Sigma a perfect synchronization among cost, quality, production time and control time can be achieved.

Keywords: six-sigma, improvement, process control chart, sigma level, FMEA.
GJRE-G Classification : FOR Code: 290502p

InvestigationofSigmaLevelattheStageofTestingCementafterPackingandImprovingitusingFMEAApproach
Strictly as per the compliance and regulations of:

© 2014. Md. Golam Kibria, Md. Enamul Kabir & S. M. Mahbubul Islam Boby. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecommons.org/licenses/bync/3.0/), permitting all non commercial use, distribution, and reproduction inany medium, provided the original work is properly cited. Investigation of Sigma Level at the Stage of
Testing Cement after Packing and Improving it using FMEA Approach
Md. Golam Kibria α, Md. Enamul Kabir σ & S. M. Mahbubul Islam Boby ρ

Keywords: six-sigma, improvement, process control chart, sigma level, FMEA.

S

I.

Introduction

ix- Sigma is a statistical measurement of only 3.4 defects per million. Six-Sigma is a management philosophy focused on eliminating mistakes, waste and rework. It establishes a measurable status to achieve and embodies a strategic problem-solving method to increase customer. Satisfaction and dramatically reduce cost and increase profits. Six-Sigma gives discipline, structure, and a foundation for solid decision making based on simple statistics. The real power of Six Sigma is simple because it combines people power with process power.
Author α: Lecturer, Department of Industrial Engineering &
Management (IEM), Khulna University of Engineering &Technology
(KUET), Khulna-9203, Bangladesh. e-mail: kibira.ipe.kuet@gmail.com
Author σ ρ: Undergraduate student, Department of Industrial
Engineering & Management (IEM), Khulna University of Engineering
&Technology (KUET), Khulna-9203, Bangladesh. e-mails: enamkuet@yahoo.com, bobyipe@yahoo.com

2014

The Six Sigma is a financial improvement strategy for an organization and now a day it is being used in many industries. Basically it is a quality improving process of final product by reducing the defects; minimize the variation and improve capability in the manufacturing process. The objective of Six Sigma 43 is to increase the profit margin, improve financial condition through minimizing the defects rate of product. It increases the customer satisfaction, retention and produces the best class product from the best process performance. If an organization is focused on customer satisfaction, then Six Sigma will offer a method and some tools for the identification and improvement of both internal and external process problems to better meet customer needs by identifying the variations in organization’s processes that might influence the customer’s point of view, negatively.
Year

technology have changed the way of conducting business.
Financial condition of a manufacturing company largely depends on the defect rate of a product. Understanding the key features, obstacles, and shortcomings of the six sigma method allows organizations to better support their strategic directions, and increasing needs for coaching, mentoring, and training. The objectives of this paper are to study and evaluate processes of the case organization, to find out the current sigma level and finally to improve the existing Sigma level through decreasing defects. According to objectives, current sigma level has been calculated, manufacturing process analyzed and suggestions given for improvement. Especially in analyzing phase different analysis tools like Production
Layout, Process Block Diagram, Cause and Effect Diagram,
Cheek Sheet, Process control chart are used. FMEA is used as improvement tool. By using this it has been possible to improve productivity by reducing defects rate. This research work has been carried out in a cement manufacturing company to show how to implement Six- Sigma in this type of industry. This research related work does not only apply to cement manufacturing company but also in any other types of organizations. By implementing Six-Sigma a perfect synchronization among cost, quality, production time and control time can be achieved.

II.

Literature Review

Though Fredrick Taylor, Walter Shewhart and
Henry Ford played a great role in the evolution of sixsigma in the early twentieth century, it is Bill Smith, Vice
President of Motorola Corporation, who is considered as the Father of Six-sigma. Fredrick Taylor came up with the methodology of breaking systems into subsystems in order to increase the efficiency of manufacturing process. Henry Ford followed his four principles, namely continuous flow, interchangeable parts, division of labor and reduction of wasted effort, in order to end up in an affordable priced automobile. The development of control charts by Walter Shewhart laid the base for statistical methods to measure the variability and quality of various processes.
Later during the 1950s, the Japanese
Manufacturing sector revolutionized their quality and competitiveness in the world based on the works of Dr.
W. Edwards Deming, Dr. Armand Feigenbaum, and Dr.
Joseph M Juran. Dr. W. Edwards Deming developed the improvementcycle of ‘Plan-Do- Check-Act’, better known as the PDCA cycle. Dr. Joseph M Juran gave to the world his ‘Quality Trilogy’ and it was Dr. Armand
Feigenbaum who initiated the concepts of ‘Total Quality
Control’ (TQC). Between 1960 and 1980, the Japanese understood that everyone in an organization is important to maintain quality and so training programs were
© 20 14 Global Journals Inc. (US)

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

Abstract- Sophisticated customer demands and advanced

Year

2014

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

44

conducted for almost all employees not considering the department they belong to. Any organization that is dynamically working to build the theme of six-sigma and to put into practice, the concepts of six-sigma, in its daily management activities, with noteworthy improvements in the process performance and customer satisfaction is considered as a six –sigma organization [3].
M. Sokovićet al. undertook papers to identify areas in the process where extra expenses exist, identify the biggest impact on production expenses, introduce appropriate measurement system, improve process and reduce expenses on production times, and implement improvements [4]. Gustav Nyren represented the variables influencing the chosen characteristics variable and then optimized the process in a robust and repeatable way [5].John Racine focuses on what sixsigma is today and what its roots are both in Japan and in the west and what six-sigma offers the world today
[6]. Zenon Chaczkoet al. introduced a process for the module level integration of computer based systems which is based on the Six-sigma Process Improvement
Model, where the goal of the process is to improve the overall quality of the system under development [7].
Philip Stephen highlighted a distinct methodology for integrating lean manufacturing and six-sigma philosophies in manufacturing facilities [8]. Thomas
Pyzdek focuses that helps the user identify worthy papers and move them steadily to successful completion, the user identify poorly conceived papers before devoting any time or resources to them, the user identify stalled papers and provide them with the attention they need to move forward again, the user decide when it’s time to pull the plug on dead papers before they consume too much time and resources and provide a record for the user that helps improve the paper selection, management and results tracking process. III.

Methodology

The preface of implementing Six-sigma is very complicated job with several steps, which relates to observe carefully, and concentrating deeply in all of the processes. Data was collected through interviews, discussions and questionnaire. All data were useful here for better understanding the production system. The collected data then interpreted into suitable format for the concerned study. The methodology, which is used in this study, enables to collect valid and reliable information and to analyze those data to conclude with a correct decision. Defects were observed and their root causes were investigated. After getting the existing scenario of the organization, the current sigma level was calculated and then the way to improve this level was analyzed. © 2014 Global Journals Inc. (US)

IV.

Data Analysis and Results

a) Process Measurement

In this measurement stage, different variables are identified to measure. As it has been trying to improve the sigma level of the organization, initially the present sigma level has been measured by using an
Excel based sigma calculator.
Sigma level is a procedure to know the existing condition of a production shop. The calculation of sigma level is based on the number of defects per million opportunities (DPMO).
In order to calculate DPMO, three distinct pieces of information are required:
i. The number of units produced. ii. The number of defect opportunities per unit. iii. The number of defects.
The actual formula is:
DPMO=

(Number of defects ∗1000000 )

((Number of defects opportunities per unit)∗number of units)

For this purpose, the relevant data is collected.
By using collected data, the defect rate of each process is calculated and converted into the total defects.
Moreover, in order to observe the situation better Sigma level is calculated in the final stage of testing cement after packing. After packing that means the final product actually gives the Sigma level of the manufacturing company. •

Sigma level at the stage of testing cement after packing: No. of defects (D) = 17 total defects
No. of opportunities for a defect (O) = 7 opportunities (categories of defect types) [ Compressive strength 3 days, Compressive strength 7days,
Compressive strength 28 days, Initial Setting Time, Final
Setting Time, Fineness, Residue]
No. of units (U) = 122
Total number of opportunities (TOP) = U * O =
854 total opportunities
DPU = D / U = 17/122= .139344262 defects per unit
DPO = D / TOP = 17/854 = 0.019906323
DPMO
=
DPO
0.019906323*1000000= 19906.323

*

1000000=

Out of a million opportunities, the long term performance of the process would create 19906.323 defects. Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

After plotting the required information into sigma level calculator, the calculator shows that the Sigma level at the stage of testing cement after packing is 3.6.
Hence, to improve this level, different quality improvement tools have to be employed and the organization has to be set a milestone to achieve.

b) Process Analysis

Year

2014

It is a very important stage to consider because lack of proper analysis may lead to the process to a wrong way, which will deviate, from the main function of

improvement. In this stage, different basic tools of quality are preferably used to analyze the real condition of the processes.
i. Process Block Diagram
To find out the existing problem of a complete production process, it is more preferable to represent the operation sequence by process flow diagram. For this purpose, the operation sequence is analyzed and obtained a chart shown in following figure.

Figure 1 : Process Block Diagram of the Cement Industry ii. Cause and Effect Diagram
To analyze a problem cause & effect diagram is one of the best tools. After obtaining process flow

diagram, the next step is to find the root cause and subcause of the existing process. The required cause & effect diagram is shown in the Figure 4.2

Figure 2 : Cause and Effect Diagram of Case Organization
© 20 14 Global Journals Inc. (US)

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

45

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

iii. Cheek Sheet
A check sheet is very useful in data collection activity. It is more effective to identify defects. Here

defects are seen in a tabular form in time basis. The required Cheek Sheets are given in Table 1, 2, 3 and 4.

Year

2014

Table 1 : Check sheet for month August 2013

46

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

Table 2 : Check sheet for month September 2013

Table 3 : Check sheet for month October 2013

Table 4 : Check sheet for month November 2013

© 2014 Global Journals Inc. (US)

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

iv. Process Control Chart
A control chart is a graphical and analytic tool for monitoring process variation. The natural variation in a process can be quantified using a set of control limits.
Control limits help distinguish common-cause variation from special-cause variation. Typically, action is taken to eliminate special-cause variation and bring the process back in control. Process has seven constraints

(Fineness, Residue, Initial setting time, Final setting time, Compressive strength 3 days, Compressive strength 7 days & Compressive strength 28 days).
Seven control charts have been drawn by taking each constraint. All control charts have two axis, in X-axis days are plotted & Y-axis constrains (each control chart has individual constrain) are plotted.

380

360

LCL= 360

355
350
0

20

40

60

80

100

120

Percent (%)

Figure 3 : Control chart for Fineness
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0

UCL= 1.0 %

LCL= 0.0
0

20

40

60

80

100

120

Initial setting time ( min)

Figure 4 : Control chart for Residue
200
195
190
185
180
175
170
165
160

UCL= 190 min
LCL= 180 min

0

20

40

60

80

100

120

Figure 5 : Control chart for initial setting time
© 20 14 Global Journals Inc. (US)

Year

UCL= 370

365

47

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

Fineness m2/Kg

370

2014

375

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

420
Final setting time ( min)

410
400
UCL= 400 min

390
380

LCL= 380 min

370
360

0

20

40

80

100

120

Figure 6 : Control chart for final setting time
Compressive Strength (MPa)

2014

18
17.5
17
16.5
16
15.5
15
14.5
14

UCL= 16.2 MPa
LCL= 15 MPa
0

20

40

60

80

100

120

Figure 7 : Control chart for Compressive Strength (3 Days)
Compressive Strength (MPa)

25
24
23
22

UCL= 22 MPa

21
20

LCL= 20 MPa

19
18

0

20

40

60

80

100

120

Figure 8 : Control chart for Compressive Strength (7 Days)
36
Compressive Strength (MPa)

Year

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

48

60

34

UCL= 33 MPa

32
30

LCL= 30 MPa

28
26

0

20

40

60

80

100

Figure 9 : Control chart for Compressive Strength (28 Days)
© 2014 Global Journals Inc. (US)

120

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

24
23
22

UCL= 22 MPa

21
20

LCL= 20 MPa

19
18

0

20

40

60

80

100

120

2014

Compressive Strength (MPa)

25

Year

Figure 8 : Control chart for Compressive Strength (7 Days)

49
34

UCL= 33 MPa

32
30

LCL= 30 MPa

28
26

0

20

40

60

80

100

120

Figure 9 : Control chart for Compressive Strength (28 Days)
c) Process Improvement

In this stage, improvement strategies are developed for achieving the desired goal. According to the analysis, perfect measures should be taken to progress the current situation. As the major concern to improve sigma level here in the case organization to improve the productivity, it is highly needed to diagnose the critical issues. For this reason FMEA (Failure Mode and Effect Analysis is used to improve the current situation of the production shop.
i. FMEA (Failure Mode and Effect Analysis)
A failure modes and effects analysis (FMEA) is a procedure in product development and operations management for analysis of potential failure modes within a system for classification by the severity and likelihood of the failures. A successful FMEA activity helps a team to identify potential failure modes based on past experience with similar products or processes, enabling the team to design those failures out of the system with the minimum of effort and resource expenditure, thereby reducing development time and costs. In FMEA, failures are prioritized according to how serious their consequences are, how frequently they occur and how easily they can be detected. A FMEA also documents current knowledge and actions about the risks of failures for use in continuous improvement.

FMEA is used during the design stage with an aim to avoid future failures. Later it is used for process control, before and during ongoing operation of the process.
Ideally, FMEA begins during the earliest conceptual stages of design and continues throughout the life of the product or service. And for the Case Organization FMEA chart (Table-8) is given below according to the following three tables- Table 5, 6 and 7.

© 20 14 Global Journals Inc. (US)

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

Compressive Strength (MPa)

36

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

Year

2014

Table 5 : Table for Severity Number

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

50

Table 6 : Table for Occurrence Number

© 2014 Global Journals Inc. (US)

Table 7 : Table for Detection Number

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

7

Low water level, if
Mongla
port is busy

5

Use small cargos, by road. 7

245

Raw
Suddenly
block raw materials supply material supply rate to silo
2
path
3 Conveyer Tear and Production
Belt
wear system stops

8

Small size of outlet 5

By decreasing supply flow

6

240

Hopper

51
9

Long time running; Absence of proper lubrication at head and tail pulley Problem in feed rate

5

Repair

6

270

Weekly inspection; Proper lubrication system

4

Desired feed rate provides 2

64

Continuous inspection to control the proper feed rate
Continuous
inspection and change grinding media and linear when needed Continuous inspection of lubrication; replace motor if running for long time Continuous inspection and if needed replace air blower Continuous inspection and if needed replace spring

Defective
Raw
Raw cement Material materials not in
Weighing
correct
Scale
proportion
5 Ball Mill Linear and Defective cement grinding media; feed rate

8

8

Long time running 8

Repair when fine particles are in low rate 5

320

6

5

Long time running and problem in lubrication 5

7

175

5

If anything collapse at air circulation path; problem in air blower
Continuous
running

7

Repairs motor; provide proper lubrication system Repairs

5

175

5

Repairs

6

150

4

Replace;
Check the
PLC system

2

56

4

Bucket Problem in No cement
Elevator motor or will flow chain from ball mill 7 Separator

Rotor speed; air circulation flow

8

Vibrating spring Elasticity of spring decreases 9

Packing Problem in
Machine
sensor

Fine and coarse cement not separated
Fine
particle will not flow to cement silo properly Defective packing 2014

Production Production rate rate

Year

Risk
Priority
Number
(RPN)

Recom ended
Action

Increase depth of water level;
Raise the facilities of
Mongla port.
Give the desired size at outlet of hopper

Current
Controls

2

Potential
Cause(s) of
Failure

5

7

Long time running; and
PLC problem

Continuous inspection © 20 14 Global Journals Inc. (US)

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

Cargo

Potential
Effects of
Failure

Detection
(1-10)

1

Potential
Failure
Mode

Occurrence
(1-10)

Process
Steps

Severity
(1-10)

Row Number

Table 8 : FMEA (Failure Mode and Effect Analysis) Chart

Investigation of Sigma Level at the Stage of Testing Cement after Packing and Improving it using FMEA
Approach

If the recommended actions are followed then the risk priority number will be decreased at desired level as a result defective product will be decreased and hence the sigma level will be improved.

Year

2014

V.

Global Journal of Researches in Engineering ( G ) Volume XIV Issue II Version I

52

Discussions

There were some uncertainties in the validity and reliability of the sampled data that are used in previous to analyze and improving sigma level of the cement manufacturing process. During the study not all, the information has collected instantly, but some previous records have also used for better understanding. The Sigma Level calculated for the case organization at the final stage of finished product is 3.6.
From the Six-Sigma value chart it can be concluded that the case organization is an average industry. Analyzing tools is used and it finds out where the maximum and serious defects were in different sections. Then the
Cause and Effect diagram determine the root causes of the problems. The check sheet represents defects at daily basis, which helps to find out in which day there were defects. Seven control charts are drawn to specify the process in control or not. The main reason for defective cement is then Compressive Strength. In addition, according to defects then Fineness, Setting time, Residue, Limestone, Slag and Fly ash. By using
FMEA (Failure Mode and Effect Analysis), Risk Priority
Number (RPN) at different stages of the manufacturing process were determined. From this case study the highest RPN was 320 (Ball Mill) and the lowest RPN was
56 (Packing Machine) in out of 1000. As the RPN increases, it indicates more risks and defects.
VI.

Recommendations

There are several approaches to choose from, when the goal is to increase the sigma level of a cement manufacturing company. The techniques used in this paper have been limited due to insufficient time and resources. In this paper only Process block diagram,
Cause and Effect diagram, Cheek sheet, process control chart are used for process analysis. FMEA isused as process improvement neglecting other improvement tool like 5S, Kaizen and Supermarket. An important suggestion for future work is to test if the findings are applicable to other steps of manufacturing and machines within the factory. Moreover, to take customers opinion about the product, this will help to identify the problems and can be solved easily.

References Références Referencias
1. Stevenson WJ,2005, ‘Competitiveness, Strategy and
Productivity’, Richard T. Hercher, Jr, Wanda J,
Zeman, ‘Operations Management’ 8th edition,
McGraw-Hill/Irwin, a business unit of the McGrawHill companies, Inc, 1221 avenue of the Americas,
New York, NY,10020,p (47-53).
© 2014 Global Journals Inc. (US)

2. Park, SH, 2003, ‘Six Sigma for Quality and
Productivity
Promotion’,
Asian
Productivity
Organization, Japan.
3. Siddhartan Ramamoorthy, 2003, ‘Lean Six Sigma
Applications In Aircraft Assembly’, B.E, Mechanical
Engineering, University of Madras, India.
4. Soković, M., Pavletić, D., and Krulčić, E., Six Sigma process improvements in automotive parts production, Journal of Achievements in Materials and Manufacturing Engineering, Vol. 19 No. 1, pp
96-102 (2006).
5. Nyrén G., A Six Sigma paper at Ericsson Network
Technologies, Master’s Research paper, MSc
Programmes in Engineering, Luleå University of
Technology (2007).
6. Racine J., A Directed Research Paper of the
Evolution of Six Sigma, Master’s Research paper,
MBA Program, Strayer University (2005).
7. Chaczko Z., Rahali E., and Tariq R., The Apllication of Six Sigma to Integration of Computer Based
Systems, World Academy of Science, Engineering and Technology 34, pp 332- 337 (2007).
8. Stephen, P., Application of DMAIC to Integrate Lean
Manufacturing and Six Sigma, Master’s Research paper , MSc in Industrial and Systems Engineering,
Virginia Polytechnic Institute and State University,
(2004).
9. Abid, M.A., Rehman, A.U., and Anees, M, 2010,
“How to minimize the defect rate of final product in textile plant by the implementation of DMAIC tool of six-sigma”, a program of “Master of
Industrial Engineering-Quality and Environmental
Management”, University of BORAS, School of
Engineering.

Appendix
MCML’S Quality Policy:
Residue-

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