The Taguchi method involves reducing the variation in a process through robust design of experiments. The experimental design proposed by Taguchi involves using orthogonal arrays to organize the parameters affecting the process and the levels at which they should be varies. Instead of having to test all possible combinations like the factorial design, the Taguchi method tests pairs of combinations. The Taguchi arrays can be derived or looked up. Small arrays can be drawn out manually; large arrays can be derived from deterministic algorithms. Generally, arrays can be found online. The arrays are selected by the number of parameters (variables) and the number of levels (states). In this paper, the specific steps involved in the application of the Taguchi method will be described with example.

1. QC STORY
PREPARED BY K.KARTHIKEYAN 1
DOE

2. QC STORY
PREPARED BY K.KARTHIKEYAN 2
DOE PROJECT TITLE

3. QC STORY
3PREPARED BY K.KARTHIKEYAN
DOE
1.1 Problem Statement
High flash fail rejections in manufacturing line
1.0 PROBLEM SELECTION
What is Flash fail rejections?
It is the insulation failure between armature core and
copper wire coil wound on the armature core. This is
being checked in manufacturing line.

4. QC STORY
4PREPARED BY K.KARTHIKEYAN
DOE
1.2 Why this Problem is important ?
Flash fail rejection is top in Pareto in manufacturing line
rejection.
This will resulting increase scrap value and if not detected
during testing stage can results customer line rejection and
warranty return.
1.3 Theme
To Reduce the manufacturing line rejection.
1.4 Target
Elimination of flash fail rejection in armature before Wk No.15.
1.0 PROBLEM SELECTION

5. QC STORY
5PREPARED BY K.KARTHIKEYAN
DOE
1.5 Action Plan
STEP
P
A
P
A
P
A
P
A
P
A
P
A
P
A
Planned - Actual -
WK NO.15WK NO.13
Problem selection
Observation
WK NO.14WK NO.10 WK NO.11 WK NO.12
Conclusion
Analysis
Action
Check
Standardisation
1.0 PROBLEM SELECTION

6. QC STORY
PREPARED BY K.KARTHIKEYAN 6
DOE
0.194 0.182 0.192 0.186 0.188 0.194
0.143 0.145
0.135 0.137 0.143 0.141
0
0.05
0.1
0.15
0.2
0.25
WK4 WK5 WK6 WK7 WK8 WK9
%Rejection
Week
2.0 OBSERVATION
Armature average rejection – 0.19 %
Average Flash fail rejection – 0.14 %
Average manufacturing line rejection was 1900 ppm ( From week
No.4 to 9) and Flash fail alone average rejection was 1400 ppm.

7. QC STORY
PREPARED BY K.KARTHIKEYAN 7
DOE
MANUFACTURING REJECTION - PARETO
2.0 OBSERVATION

8. QC STORY
PREPARED BY K.KARTHIKEYAN 8
DOE
3.0 ANALYSIS :
3.1 Defective analysis - Concentration chart:
The study of defectives shown all flash fail are due to defective powder coating and
wire touching core. A concentration chart diagram of defective shows no
concentration of defects
3.0 ANALYSIS
3.2 Comparing of Good & Bad sample:
In all bad samples the coating thickness found less than specification of 300 - 400
microns

9. QC STORY
9PREPARED BY K.KARTHIKEYAN
DOE
Gap between
Coil & Armature
3.3 CAUSE AND EFFECT DIAGRAM
A cause & effect diagram was constructed depicting the various probable causes.
Powder
Coating
thickness
Variation
MAN MATERIAL
Sop not adequate
OD clean belt
MACHINEMETHOD
Pre Heating
Temp
Lumps in Powder
Air Knife pressure
Component
orientation Process parameter
Masking JIG
MEASUREMENT
Coating Thickness
not Checked
properly
Not given in drawing
Humidity in powder
Jig not properly seated
Lack of training
Voltage Coater Pr
Uneven fluidization
Program selection
Cleaning method
Powder Storage
level
Cu Plate
Curing
temp
ENVIRONMENT
Humidity
Powder Storage
Room temp
Untrained
Operator
Fatigue
Shell life completed
Rust on Core
Conveyor
Speed
3.0 ANALYSIS

10. QC STORY
10PREPARED BY K.KARTHIKEYAN
DOE
1. Objective of the experiment
2. Selection of factors, levels and expected interactions
3. Selection of experimental design
4. Experimental preparation and randomize the Experimental run
5. Statistical data analysis
6. Experimental Conclusions and recommendations
4.0 STEPS FOR DESIGN OF EXPERIMENT
• ALL THE POSSIBLE CAUSES ARE INVALID. IT IS VERY DIFFCULT TO CHECK
PROBABLE CAUSE HENCE WE DECIDED TO DO DOE TO OPTIMIZE PROCESS
PARAMETER IN POWDER COATING PROCESS BY USING TAGUCHI METHOD.
3.0 ANALYSIS

11. QC STORY
11PREPARED BY K.KARTHIKEYAN
DOE
The Powder Coating process having the following 14 process parameters
2.0 Selection of factors and expected interactions and Response
DESIGN OF EXPERIMENT
To optimize the Powder Coating process parameters through Taguchi method.
1.0 Objective of the experiment:
Sl.No Parameter
1 Conveyor Speed (Hz)
2 Electrostatic Voltage (kV)
3 Sub coater pressure (Mpa)
4 Coater Pressure (Mpa)
5 Powder feeder Pressure (Mpa)
6 Air hopper Pressure(Mpa)
7 OD removal belt height (mm)
8 Air Knife 1 (Mpa)
9 Air Knife 2 (Mpa)
10 Air Knife 3 (Mpa)
11 Air Knife 4 (Mpa)
12 Air Knife 5 (Mpa)
13 Pre heating temperature (o
C)
14 Curing temperature (o
C)
Sl.No Parameter
1 Conveyor Speed
2 Electrostatic Voltage
3
Preheating
Temperature
4 Curing Temperature
5 Coater Pressure
Our team has selected all five key
process parameter to optimize the
powder coating process based on
the Experience and knowledge.

12. QC STORY
12PREPARED BY K.KARTHIKEYAN
DOE
A. Conveyor Speed in Hz ( 15 Hz)
B. Electrostatic voltage in kV (60 kV)
C. Preheating temperature in O C (150O c)
D. Curing temperature in O C ( 240O c )
E. Coater pressure in bar ( 0.05 bar)
2.a Choice of Main Factors
2.b. Interaction of Interest:
1. Conveyor speed & Coater pressure (A & E)
2. Electrostatic voltage & Coater pressure (B & E)
3. Preheating temp & Coater pressure (C & E)
4. Curing temp & Coater pressure (D & E)
DESIGN OF EXPERIMENT

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13PREPARED BY K.KARTHIKEYAN
DOE
2.c.Choice of factor levels
Three levels selected for each factors based on experience & knowledge
Level 1 , Level 2 , Level 3
Replication = 5 Nos
Factors Level 1 Level 2 Level 3
Conveyor speed (Hz) 15 16 17
Electrostatic Voltage (kV) 50 55 60
Preheating temperature ('C) 150 180 210
Curing temperature ('C) 240 280 320
Coater Pressure (bar) 0.03 0.05 0.08
Factors Specfication
Existing
Setting
Conveyor speed (Hz) 15 15
Electrostatic Voltage
(kV)
55 ±5 60
Preheating temperature
('C)
180±20°C 150
Curing temperature ('C) 280±40°C 240
Coater Pressure (bar) 0.05±0.02 0.05
2.d. Selection of Response
Coating thickness in Armature ( Spec: 300 – 400 microns)
DESIGN OF EXPERIMENT

14. QC STORY
14PREPARED BY K.KARTHIKEYAN
DOE
Total no of Factors 5 and 4 Interactions with 3 levels
3.1. Required Degree of freedom for main factor
= (No of levels - 1) X No of factors = (3 - 1) X 5 = 10
3.2. Required Degree of freedom for Interaction
= ((DOF of A X DOF of E) + (DOF of B X DOF of E)
+ (DOF of C X DOF of E) +( DOF of D X DOF of E) )
= ((3 - 1) X(3 – 1))+((3 - 1) X (3 - 1))+((3 - 1) X (3 - 1) )+( (3 - 1) X (3 - 1))
= 16
3. Selection of Experimental Design:
DESIGN OF EXPERIMENT

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15PREPARED BY K.KARTHIKEYAN
DOE
3.3.Total Degrees of freedom = DOF of Main effect + DOF of Interaction
= 10 + 16
= 26
3.4.Minimum no of Experiments = Total Degrees of Freedom + 1
= 26 + 1
= 27
3.5.Suitable Orthogonal Array
from Table
= L
27
(3) 13
DESIGN OF EXPERIMENT

16. QC STORY
16PREPARED BY K.KARTHIKEYAN
DOE
3.6. Required Linear graph:
3.7. Standard Linear graph (Select from orthogonal table):
A
E B
C
D
B X E
A X E
D X E
C X E
1
5 2
9
10
7
6
118
3
124
13
1
5 2
9
10
7
6
118
3
124
13
DESIGN OF EXPERIMENT

17. QC STORY
17PREPARED BY K.KARTHIKEYAN
DOE
3.8. Modified Standard Linear graph
Assignment of factors is done using the Linear graph
Nodes – factors
Lines – interaction between factors
1
(A)
2
(B)
9
(C)
10
(D)
6 7 (AXE)
8 11 (BXE)
4 12 (DXE)
3 13 (CXE)
5
(E)
DESIGN OF EXPERIMENT

18. QC STORY
18PREPARED BY K.KARTHIKEYAN
DOE
3.9. Draw Design Layout of Experiment: (From OA table) = L27 Array
DESIGN OF EXPERIMENT

19. QC STORY
19PREPARED BY K.KARTHIKEYAN
DOE
FACTORS AND LEVELS FOR THE EXPERIMENTS
1. A – Conveyor Speed in HZ
2. B – Electrostatic Voltage kV
9. C - Preheating Temperature °C
10. D - Curing Temperature °C
5. E – Coater Pressure in bar
6 7. Conveyor Speed in HZ X Coater Pressure in bar ( AXE)
8 11. Electrostatic Voltage kV X Coater Pressure in bar (BXE)
3 13. Preheating Temperature °C X Coater Pressure in bar (CXE)
4 12. Curing Temperature °C X Coater Pressure in bar (DXE)
DESIGN OF EXPERIMENT

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20PREPARED BY K.KARTHIKEYAN
DOE
3.10 Physical Layout of Experimentation:
DESIGN OF EXPERIMENT

21. QC STORY
21PREPARED BY K.KARTHIKEYAN
DOE
4. 0 Experimental run Result:
DESIGN OF EXPERIMENT

22. QC STORY
22PREPARED BY K.KARTHIKEYAN
DOE
171615
340
330
320
605550 210180150
320280240
340
330
320
0.080.050.03
C onv ey or speed
MeanofMeans
Electrostatic v oltage Preheating temp
C uring Temp C oater pressure
Main Effects Plot for Means
Data Means
Interpretation
A2,B1,C2,D2, & E1
are best levels
AVERAGE RESPONSE GRAPHS OF MAIN EFFECTS
Interpretation of Experimental trials
5.0 Analysis and Interpretation of Experimental trials:

23. QC STORY
23PREPARED BY K.KARTHIKEYAN
DOE
AVERAGE RESPONSE GRAPHS OF INTERACTION EFFECTS
Interpretation : Electrostatic Voltage x Coater pressure, Preheating Temperature x
Coater pressure, Curing Temperature x Coater pressure interactions are exists
350
330
310
605550 320280240
350
330
310
0.080.050.03
350
330
310
350
330
310
171615
350
330
310
210180150
Conveyor speed
Electrostatic voltage
Preheating temp
Curing Temp
Coater pressure
15
16
17
speed
Conveyor
50
55
60
voltage
Electrostatic
150
180
210
temp
Preheating
240
280
320
Temp
Curing
0.03
0.05
0.08
pressure
Coater
Interaction Plot for Means
Data Means
Interpretation of Experimental trials

24. QC STORY
24PREPARED BY K.KARTHIKEYAN
DOE
SELECTION OF OPTIMUM COMBINATION (BASED ON MAIN EFFECT
PLOT AND INTERACTION EFFECT PLOT)
The best combination is
A2 B1 C2 D2 & E1
The best levels of individual factors are
Factors Level 1 Level 2 Level 3
Conveyor speed (Hz) 15 16 17
Electrostatic Voltage (kV) 50 55 60
Preheating temperature ('C) 150 180 210
Curing temperature ('C) 240 280 320
Coater Pressure (bar) 0.03 0.05 0.08
Interpretation of Experimental trials

25. QC STORY
25PREPARED BY K.KARTHIKEYAN
DOE
If the ‘F Calculated ’ value is greater than ‘ F Table’ value or p value
is less tan 0.05 then that factor shall be considered as significant.
If the ‘F Calculated ’ value is greater than ‘ F Table’ value or p value
is less tan 0.05 then that factor shall be considered as significant.
INTERPRETATIONINTERPRETATION
5. Interpretation through ANOVA Method:
DOF
Sum of
Square
MSS F cal F Table P value % Cont
Result
(Fcal > F Tab
2 65.80 32.90 0.152 3.080 0.859 0.1 Not Significant
2 14062.40 7031.20 32.425 3.080 0.000 25.5 Significant
2 557.60 278.80 1.286 3.080 0.281 1.0 Not Significant
2 6355.70 3177.85 14.655 3.080 0.000 11.5 Significant
2 1630.90 815.45 3.761 3.080 0.026 3.0 Significant
4 2247.20 561.80 2.591 2.455 0.041 4.1 Significant
4 817.90 204.48 0.943 2.455 0.442 1.5 Not Significant
4 3747.00 936.75 4.320 2.455 0.003 6.8 Significant
4 2321.100 580.275 2.676 2.455 0.036 4.2 Significant
108 23419.00 216.84 42.4
134 55225.00 100
Error
Total
Curing temp x coater pressure
(DXE)
Conveyor speed x coater pressure
(AXE)
Electrostatic voltage x coater
pressure (BXE)
Coater Pressure bar (E)
Conveyor speed - Hz (A)
Electrostatic voltage Kv -(B)
Preheating temp x Coater
pressure (CXE)
Factors
Preheating temperature °C ('C)
Curing temperature °C (D)
Interpretation through ANOVA

26. QC STORY
26PREPARED BY K.KARTHIKEYAN
DOE
INFERENCE ON ANOVA:
Interpretation Of ANOVA Based On P-Value
Based on the P Value from the ANOVA table the following are the inferences. The
details Of Individual Factor Significance And Significance of interaction were given
below.
Factors Level 1 Level 2 Level 3
A Conveyor speed (Hz) 15 16 17
B Electrostatic Voltage (kV) 50 55 60
C Preheating temperature ('C) 150 180 210
D Curing temperature ('C) 240 280 320
E Coater Pressure (bar) 0.03 0.05 0.08
1. Factor A - Insignificant
2. Factor B - Significant
3. Factor C - Insignificant
4. Factor D - Significant
5. Factor E - Significant
6. InteractionA X E - Significant
7. Interaction B X E - Insignificant
8. Interaction C X E - Significant
9. Interaction D X E - Significant
Interpretation through ANOVA

27. QC STORY
27PREPARED BY K.KARTHIKEYAN
DOE 4.0 ACTION
Factors
Previous
setting
Optimized
setting
A Conveyor speed in rpm 15 16
B Electrostatic voltage in kV 60 50
C Pre heat temperature in o C 150 180
D Curing temperature in o C 240 280
E Coater pressure in bar 0.05 0.03
From the Experiment the Armature powder coating process
parameters are optimized.
RECOMMENDED (OPTIMISED) PRODUCTION SETTING

28. QC STORY
28PREPARED BY K.KARTHIKEYAN
DOE
Based on the best optimum combination obtained from the results
of experiments a confirmatory run has been done and the results
were verified with the predicted values and found well near to the
values.
30 Nos.of samples taken for the optimum level and Cpk values
were recorded and the same values were interpreted.
CONFIRMATORY TRIAL WITH PREDICTED VALUES
4.0 ACTION

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29PREPARED BY K.KARTHIKEYAN
DOE
CONFIRMATORY TRIAL
5.0 CHECK
Before DOE : 1.07 After DOE : 1.27

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PREPARED BY K.KARTHIKEYAN 30
DOE
REJECTION TREND (After Improvements)
5.0 CHECK
6.0 STANDARDISATION

31. QC STORY
31PREPARED BY K.KARTHIKEYAN
DOE
> From the Design of Experiment analysis, powder
coating process parameter is optimized as per the
below process setting and it is clearly indicates that
the Powder coating process is well within the process
center.
7.0 CONCLUSION
> Thus by improving the Cpk of Powder coating process
Armature manufacturing line rejection reduced from 1900 PPM
to 700 PPM. Flash fail rejections reduced from 1400 PPM to 200
PPM

32. QC STORY
PREPARED BY K.KARTHIKEYAN 32
DOE