12
Prepared by Ng Siew Kai

Six Sigma Case Study 1 -MFI

  • Upload
    skng

  • View
    565

  • Download
    1

Embed Size (px)

DESCRIPTION

Six sigma case study on Injection Molding Operation (Melt Flow Index quality issue)

Citation preview

Page 1: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

Page 2: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

1.0 Objective :

To determine the effect of critical injection parameters on MFI

(Degradation %).

2.0 Machine/ Material:

Machine : 7E3, Screw diameter : 22mm

Resin : Cycoloy C1100HF

Page 3: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

3.0 Experiment Flow

Molding D.O.E

Melt Flow

Index Test

• Use Cutter to cut part

• Study effect of

parameters on MFI

• Study effect of six critical

molding parameters

Trial sample

preparation

Page 4: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

Melt Flow Rate : Introduction

One of the most common causes of plastic part failure is

polymer degradation during melt processing.

In most materials, this degradation results in a reduction in the

average molecular weight of the polymer.

This reduction is readily measured by a variety of techniques,

the simplest being the melt flow rate test. - Michael Sepe

Simple Interpretation :

Melt flow Rate/ index is an inverse measure of molecular weight.

When polymer encountered degradation, average molecular

weight will reduce and MFR value will high.

- Shan, Handbook of

Plastic Technology

Page 5: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

1. Injection Speed : 20 - 40

2. Injection Pressure : 50 - 100

3. Holding Pressure : 10 - 30

4. Hot runner temperature : 240 – 2600C

5. Meld Temperature : 240 – 2600C

6. Mold Temperature : 70 – 900C

Responses : MFI Degradation %

MFI Degradation % = (MFI – MFI resin) / MFI resin

4.0 Design Of Experiment

(DOE : ¼ Fractional Factorial 26, Resolution IV )

Page 6: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

4.1 DOE Matrix and Result :

Factional Factorial 26 (R IV)

Response

Page 7: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

Inj press

Inj Sped

Mold temp

Hold press

Melt temp

Hot runner

43210

Term

Standardized Effect

2.262

Pareto Chart of the Standardized Effects(response is Degrad. %, Alpha = .05)

Factorial Fit: Degrad. % versus Inj Sped, Hot runner, ...

Estimated Effects and Coefficients for Degrad. %

Term Effect Coef SE Coef T P

Constant 26.726 0.7905 33.81 0.000

Inj Sped 0.834 0.417 0.7905 0.53 0.611

Hot runner 6.114 3.057 0.7905 3.87 0.004

Melt temp 4.249 2.124 0.7905 2.69 0.025

Mold temp -1.446 -0.723 0.7905 -0.91 0.384

Inj press 0.649 0.324 0.7905 0.41 0.691

Hold press -2.311 -1.156 0.7905 -1.46 0.178

Ct Pt 2.654 3.2595 0.81 0.436

4.2 ANOVA : Degradation

From the ANOVA analysis :

1. Hot runner temperature is a significant factor for MFI Degradation.

2. Melt temperature is a significant factor for MFI Degradation.

Page 8: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

403020

30.0

28.5

27.0

25.5

24.0

260250240 260250240

908070

30.0

28.5

27.0

25.5

24.0

1007550 302010

Inj SpedMean

Hot runner Melt temp

Mold temp Inj press Hold press

Corner

Center

Point Type

Main Effects Plot for Degrad. %Data Means

4.3 Main Effect Plot : Degradation

From the Respond Graph :

1. When Hot runner temperature increase, MFI Degradation % will

increase.

2. When Melt temperature increase, MFI Degradation % will increase.

Page 9: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

4.4 Interaction Plot

260250240 260250240 908070 1007550 302010

30

25

20

30

25

20

30

25

20

30

25

20

30

25

20

Inj Sped

Hot runner

Melt temp

Mold temp

Inj press

Hold press

20 Corner

30 Center

40 Corner

Inj Sped Point Type

240 Corner

250 Center

260 Corner

runner

Hot

Point Type

240 Corner

250 Center

260 Corner

temp

Melt

Point Type

70 Corner

80 Center

90 Corner

temp

Mold

Point Type

50 Corner

75 Center

100 Corner

Inj press Point Type

Interaction Plot for Degrad. %Data Means

From the Interaction Plot Graph :

No significant interaction among the six factors.

Page 10: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

4.6 Response Optimzer

Inj Speed = 20

Hot runner = 240

Melt temp = 240

Mold temp = 90

Inj press = 50

Hold press = 30

Coincidently, same to Trial 9 condition

Predicted Responses

Degradation % = 18.9

Page 11: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

4.7 Transfer Function :

Degradation % = -96.933 + (0.306*Hot runner temperature) + (0.212*Melt

temperature) –(0.072*Mold temperature)-(0.116*Hold pressure)

Estimated Coefficients for Degrad. % using

data in uncoded units

Term Coef

Constant -94.7094

Hot runner 0.305688

Melt temp 0.212438

Mold temp -0.0723125

Hold press -0.115563

Ct Pt 2.65437

Page 12: Six Sigma Case Study 1 -MFI

Prepared by Ng Siew Kai

5.0 Summary :

� Hot Runner Temperature and Melt Temperature are significant

factors for MFI Degradation.

� Hot Runner Temperature and Melt Temperature need to be

controlled at low setting. The Optimum condition, which

coincidently has the same condition as Trial 9.