Present apiem 8 12 53

DESIGN OF EXPERIMENT APPROACH FOR

IMPROVING RICE MILLING QUALITY

Worlaluck Jankrajang1

Faculty of Engineering, Department of Industrial Engineering

Eastern Asia University, Phathumtani, 12110, THAILAND

[email protected]

The rice milling industry is one of the major agro-industries in Thailand. The

greatest grain losses among all the milling processes come from the milling equipment

adjustments at the beginning of operation. Generally there is no uniformity in the adjustments

of the equipment being used. This leads to grain losses and additional setup costs which are

the major problem.

The principle objective of this study is to determine the most influenced factors on

the head rice yield and to set the parameters for the influenced factors so that the head rice

yield is maximized.

•The processing of paddy in a rice mill at Chitralada Royal Project.

•Rice milling is the process of removing the hulls and brans form grain paddy in

order to produce edible rice.

• At Chitralada, the existing head rice yield is 56 percent head rice which is lower

than the standard of compared to the standard of The Rice Inspections

Committee of the Board of Trade (medium size of rice mill) which is 60 percent

head

•The greatest grain losses (low head rice yield) among all the milling processes

came from the milling equipment adjustments at the beginning of operation.

Generally there was no uniformity in the adjustments of the equipment being

used.

• The greatest grain

losses among all the

milling processes

came from the

whiteners

adjustments at the

beginning of the

operation.

•Traditionally the initial adjustment in

rice milling is a trial and error process

•This process was repeated until there

was an appreciable difference

between the inlet and the outlet

sample.

•So, there is no definite data to reply

on and the choice is left to miller’s

experience.

•In this study, stages other

than whitening process are

not considered.

Physiological factors are

disregarded and

environmental conditions

are controlled by the

laboratory.

•Furthermore, this study is

based on and limited to the

capabilities of the existing

machine.

2. METHODOLOGY

Design of experiments is a powerful tool that can be utilized in this

experiment.

•In this experiment the historical data from Production Report to analyze the

result.

Factor

Type 1 Type 2 Type 3

Low

(-1)

High

(+1)

Low

(-1)

High

(+1)

Low

(-1)

High

(+1)

Roller

Speed

(rpm)

Whitener

no. 1 (A) 950 1000 1000 1050 1050 1100

Whitener

no. 2 (B) 950 1000 1000 1050 1050 1100

Whitener

no. 3 (C) 950 1000 1000 1050 1050 1100

Table 1 Types of Roller Speed Setting.

Factor

Type 1 Type 2

Low

(-1)High

(+1)

Low

(-1)High

(+1)

Clearance

(time of

brown

size)

Whitener

no. 1 (D) 1 1.5 1.5 2

Whitener

no. 2 (E) 1 1.5 1.5 2

Whitener

no. 3 (F) 1 1.5 1.5 2

• Data were collected in 2 levels of 6 factors full factorial design. The existing data

can be classified into

•3 types of Roller Speed setting

•and 2 types of Clearance setting

Experiment 1 Experiment 2

Process Factor

Low

(-1)

High

(+1)

Low

(-1)

High

(+1)

Whitening

Roller

Speed

(rpm)

Whitener

no. 1 (A) 950 950 1000 1000

Whitener

no. 2 (B) 950 950 1000 1000

Whitener

no. 3 (C) 950 950 1000 1000

Clearance

(time of

brown

rice size)

Whitener

no. 1 (D) 1 1.5 2 1.5

Whitener

no. 2 (E) 1 1.5 2 1.5

Whitener

no. 3 (F) 1 1.5 2 1.5


Low

(-1)

High

(+1)

Low

(-1)

High

(+1)

1000 1000 1050 1050

1000 1000 1050 1050

1000 1000 1050 1050

1 1.5 2 1.5

1 1.5 2 1.5

1 1.5 2 1.5


Low

(-1)

High

(+1)

Low

(-1)

High

(+1)

1050 1050 1100 1100

1050 1050 1100 1100

1050 1050 1100 1100

1 1.5 2 1.5

1 1.5 2 1.5

1 1.5 2 1.5

Table 3 Factors and level for the rice mil system.

The combinations of 3 Roller Speed Setting and 2 Clearance setting resulted in 6 setting types

3. PERFORM EXPERIMENTS

3.1 Classical method using Full Factorial design with 3 replicates

The orthogonal array for 2 level 6 factors full factorial design was applied and the

head rice yield was obtained as follow;

Head rice yield = weight of head rice from head rice collector x 100(%)

weight of brow rice used for one test run

Experiment

1 2 3 4 5 6

Accept 82 88 192 148 62 43

Reject 110 104 0 44 130 149

4. ANALYZE DATA

4.1 Analysis of classical method data via ANOVA table

Table shows the summary of the accepted and rejected lot. It was observed that

experiment 3 has the highest number of accepted. Based on these results,

Experiment 3 was chosen to be analyzed.(The summary of accept and reject lot out of 192 runs. Analysis of the data was completed using MINITAB

software by selecting Balance ANOVA topic. Analysis of Variance (ANOVA) tables reports )

Analysis of Variance Table for experiment 3

Table shows that in experiment 3 P- value of any

factor was not less than the significance level at

1% or 5% Thus,

there was no influenced factor at the 95% and

99% confidence level in this experiment. That

means the Roller Speed can be set at either

1000 or 1050 rpm and also Clearance can be

set at 1 or 1.5 time of brown grain size.

Source DF SS MS F P

A 1 2574 2574 1.64 0.202

B 1 1328 1328 0.85 0.358

C 1 1844 1844 1.18 0.279

D 1 923 923 0.59 0.444

E 1 1628 1628 1.04 0.309

F 1 2194 2194 1.40 0.238

A*B 1 1807 1807 1.15 0.284

A*C 1 1698 1698 1.08 0.299

A*D 1 1328 1328 0.85 0.358

A*E 1 1491 1491 0.95 0.331

A*F 1 1524 1524 0.97 0.325

B*C 1 1881 1881 1.20 0.275

B*D 1 1628 1628 1.04 0.309

B*E 1 1524 1524 0.97 0.325

B*F 1 1698 1698 1.08 0.299

C*D 1 1593 1593 1.02 0.315

C*E 1 1360 1360 0.87 0.353

C*F 1 1881 1881 1.20 0.275

D*E 1 1328 1328 0.85 0.358

D*F 1 1235 1235 0.79 0.376

E*F 1 1146 1146 0.73 0.394

Error 170 266231 1566

Total 191 299844

Based on this analysis, settings were recommended for the factors which

would maximize the mean response. The best result is 66 percent head rice which

adjusted the location of the speed of whitener 1, 2 and 3 at 1050 rpm. The

Clearances were set at 1.5 times of grain size. To summarize, the optimum setting

for influenced factors are:

Factors Setting

Speed of whitening 1 1050 rpm



Clearance of whitening 1 1.5 time of grain



3.2 Taguchi method using Taguchi L12 design

Base on Rules of Thumb (4) Two-Level and Three Level Design

Choices for the Number of Factors (k>6). In this case k=6 factors, twelve

runs will be used to test the effects of the six controllable in a Taguchi L12

design.

With the aid of software program, the Taguchi 2-Level L12 design

portion provides 12 runs ,lists the array of noise factor conditions were

generated using a Taguchi L12 design.

The combination of the inner and outer arrays results in each run

of the controllable being repeated over the 12 conditions of the noise

factors.

Run A B C D E F

1 1000(-1) 1000(-1) 1000(-1) 1(-1) 1(-1) 1(-1)

2 1000(-1) 1000(-1) 1000(-1) 1(-1) 1(-1) 1.5(1)

3 1000(-1) 1000(-1) 1050(1) 1.5(1) 1.5(1) 1(-1)

4 1000(-1) 1050(1) 1000(-1) 1.5(1) 1.5(1) 1(-1)

5 1000(-1) 1050(1) 1050(1) 1(-1) 1.5(1) 1.5(1)

6 1000(-1) 1050(1) 1050(1) 1.5(1) 1(-1) 1.5(1)

7 1050(1) 1000(-1) 1050(1) 1.5(1) 1(-1) 1(-1)

8 1050(1) 1000(-1) 1050(1) 1(-1) 1.5(1) 1.5(1)

9 1050(1) 1000(-1) 1000(-1) 1.5(1) 1.5(1) 1.5(1)

10 1050(1) 1050(1) 1050(1) 1(-1) 1(-1) 1(-1)

11 1050(1) 1050(1) 1000(-1) 1.5(1) 1(-1) 1.5(1)

12 1050(1) 1050(1) 1000(-1) 1(-1) 1.5(1) 1(-1)

Design matrix for the Taguchi method.

A B C D E F

-50 -50 -50 -0 -0 -0

-50 -50 -50 -0 -0 +0.5

-50 -50 +50 +0.5 +0.5 -0

-50 50 -50 +0.5 +0.5 -0

-50 +50 +50 -0 +0.5 +0.5

-50 +50 +50 +0.5 -0 +0.5

+50 -50 +50 +0.5 -0 -0

+50 -50 +50 -0 +0.5 +0.5

+50 -50 -50 +0.5 +0.5 +0.5

+50 +50 +50 -0 -0 -0

+50 +50 -50 +0.5 -0 +0.5

+50 +50 -50 -0 +0.5 -0

Noise matrix for the Taguchi method.

The data matrix was obtained by crossing the design and noise matrices

4.2 Analysis of Taguchi method data by S/N ratio

Refer to S/N Table

the optimal settings are the ones that maximize the response which result

would be:A=1050, B=1050, C=1050, D=1.5, E=1.5, F= 1.5

MainEffect Plot for S/N Ratios.

setting high Speed of whitening 1, 2 and 3

and setting clearance of whitening 1, 2 and 3 at 1.5 times of grain size produced

high % head rice.

Analysis of the table and graph indicates that

setting high Speed of whitening 1, 2 and 3

and setting clearance of whitening 1, 2 and 3 at 1.5 times of grain size

produced high % head rice.

This combination was never tested in the experiment, thus the term

predicted best result. Based on new predicted best result of Taguchi

Method, the setting result was the same as the result from Classical

Method.

5. CONFIRM RESULTSThe 30 runs were constructed using the appropriated settings

The overall average 67 percent head rice with standard deviation 0.67 was found,

which correlated very closely to the 66 percent head rice of experiment 3.

This gave the team confidence in the experimental results and reinforced the

recommended setting which would result in increased the head rice yield as shown

the calculation below.

New setting gave: Mean 67 percent head rice (use the optimum setting)

Std 0.67

Previous setting gave: Mean 56 percent head rice (use the trial and error setting)

Std 6.11

Mean Increase (67 - 56 = 11) 11 percent head rice

Standard Deviation decrease 6.11 - 0.67 = 5.44

The new setting results in the improvement by [(100 11) / 56] = 17.85 %

and the variation is decreased by [(100 5.44) / 6.11] = 89.03 %

Calculation of Cost and Time SavingTotal Cost/run

= Fixed Cost + Variable Cost

= (Material Cost + Labor Cost + Overhead Cost) + (Shutdown + Defect Item)

The fix cost / run of chitralada Rice Mill are estimated by the combination between material cost, labor

cost and overhead cost, which is 2,800 Baht per run. The variable cost dues to cost of defect and machine

shut down during trial and error setup has been found to be a major expense to the total cost of each run.

Previously the actual variable cost per each run was 1,600 Baht (Expense Report of year 2000) due to

estimate 3 shutdowns during trial and error setup.

The trial and error setups were eliminated by the recommended setting. Based on this confirmation run,

actual variable cost mostly came from defect items, which was 700 Baht.

The saving cost per run was calculated as follows:

Total cost /run = Fixed Cost + Variable Cost

Current Total cost/run = 2,800 + 1,600 = 4,400 Baht

New Total cost/run = 2,800 + 700 = 3,500 Baht

Total cost saving = 4,400 – 3,500 = 900 Baht

So, the total cost was reduced by

[(90 * 100)/4,400] = 20.45 %

The new operation time was recorded during the confirmation run,

an average 142 minute per run that was less than the previous operation time (180 min)

since the shutdown were reduced.

So, the saving time per run was calculated as follows:

Saving time

= Current operation time – New operation time

= 180 – 142

= 38 min / run

So, the operation time reduce by [(38 * 100) / 180]

= 21.11 %

Approach The optimal setting

Estimate

Mean

Factor A B C D E F

Classical 1050 1050 1050 1.5 1.5 1.5 67

Taguchi 1050 1050 1050 1.5 1.5 1.5 67

6. DISCUSS OF THE RESULTFor comparing the results obtained from the classical method to those obtained from the

Taguchi method, the following items were concerned:

1) The optimal setting for each approach.

2) The mean response value at optimal sets of design variable values for each approach.

The comparison of the results from the two methods.

The table shows 67 percent head rice for the estimated mean of Classical and Taguchi Method.

Because the optimal settings of the two methods were the same, the estimated mean of improvement

process gives the same value of response.

Comparison of experiment results for the Rice Mill problem.

Advantage and Disadvantage of Classical Method:

Classical method is the simplest analysis technique by perform hypothesis

tests on all desired effects and classified as significant or not significant using the F

test. Further more, Classical object to use the statistics because it represent the close

correlation between the mean and the variability.

But the disadvantage is that too many runs need to be performed i.e. if we

run completely full factorial design of 4 levels for three Roller Speed factors and 3

levels for three Clearance factors, the full factorial design would consist of 43 * 33 =

1,728 runs while Taguchi method needs only 144 runs (the combination of the inner

and outer arrays = 12 * 12 runs). It is 12 times of Taguchi’s number of runs

Advantage and Disadvantage of Taguchi Method:

The idea of using tabled orthogonal arrays and marginal mean analysis is

very comfortable for analyze. As stated above, Taguchi uses the formula for

signal to noise to define the optimum operating point for the process in that the

combination of factor settings which maximizes this function defines the

optimum instead of uses statistic.

But the disadvantage of Taguchi Method is no statistical evidence that

causes this method to loose information compared to separate measurements

of mean and variability in the case.

7. CONCLUSIONS

Through the use of a designed experiment, the investigators were able to accomplish the

objective of determining the most influenced factors on rice milling process and setting the

parameters for the influenced factors for the improvement of head rice yield.

Furthermore, the operating time and overall costs were reduced. The most influenced

factors on the percent head rice result from this experiment were the suitable setting parameters

are Speed of whitening 1 at 1050 rpm, Speed of whitening 2 at 1050 rpm. Speed of whitening 3 at

1050 rpm. Clearance of whitening 1 at 1.5 time of grain. Clearance of whitening 2 at 1.5 time of

grain and Clearance of whitening 3 at 1.5 time of grain.

With these settings it was possible to reduce overall costs by 20.45% and operating time by

21.11%.

From the confirmation runs under these appropriate settings condition all runs of response variables

pass the specification and the head rice yield is improved by 17.85% from the previous percent head rice

which is 56%. The new head rice yield falls in the interval 65 – 69 percent head rice with mean 67

percent head rice and standard deviation 0.67. Furthermore, the improvement in the head rice yield of

this new setting was nearly met the commercial standard of the Rice Inspections Committee of the Board

of Trade which is 60 percent head rice. This also indicates a positive trend of Chiralada Rice Mill’s

product to competitive in the commercial market.

.

Present apiem 8 12 53

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