Dimensional consistency is a critical attribute for injection molded part quality and is highly dependent on the polymer morphology, the thermal expansion, and various processing parameters. The dimensional shrinkage can be estimated by knowing the pressure-volume-temperature behavior of the polymer but with limited accuracy. There are various process monitoring systems available in the market; none of which has the capability of directly monitoring and controlling the real time shrinkage and part dimensions online. With a view to measuring in-mold shrinkage, a button cell type in-mold shrinkage sensor was developed, validated, and compared against the traditional shrinkage prediction and estimation methods. The shrinkage sensor consists of an elastic diaphragm instrumented with strain gages connected in a full bridge circuit. The sensor is placed beneath the movable pin that is protruded into the mold cavity and remains in contact with the sensor diaphragm. The sensor diaphragm is deflected due to the melt pressure acting on the pin into the mold cavity and is retracted back toward its original position as the melt solidifies and shrinks away from the mold cavity wall. The sensor signals acquired during each molding cycle were analyzed to validate the sensor performance in a design of experiments as a function of packing pressure, melt temperature, cooling time, and coolant temperature. The regression results indicate that the shrinkage sensor outperforms cavity pressure transducers and other methods of predicting the in-mold shrinkage. For polypropylene, the shrinkage sensor is able to measure the shrinkage to an average accuracy of 0.01 mm for a molded part with a nominal thickness of 2.5 mm. The coefficient of correlation, R2, between the sensor’s final positions to the final part thickness was 0.921 for the in-mold shrinkage sensor. Other dimension prediction methods had lower correlation coefficients.

1.
Malloy
,
R.
, 1994,
Plastic Part Design for Injection Molding
,
Hanser Gardner Publication, Inc.
,
Cincinnati, OH
.
2.
Fischer
,
J. M.
, 2003,
Handbook of Molded Part Shrinkage and Warpage
,
William Andrew, Inc.
,
Norwich, NY
/
Plastics Design Library
.
3.
Kazmer
,
D. O.
, 2007,
Injection Mold Engineering
,
Hanser Gardner Publication, Inc.
,
Cincinnati, OH
.
4.
Baaijens
,
F. P. T.
, 1991, “
Calculation of Residual Stresses in Injection Molded Products
,”
Rheol. Acta
0035-4511,
30
, pp.
284
299
.
5.
Kennedy
,
P.
, and
Zheng
,
R.
, 2001, “
High Accuracy Shrinkage and Warpage Prediction for Injection Molding
,”
ANTEC 2002 Annual Technical Conference
, pp.
1
7
.
6.
Chang
,
R.
, and
Chiou
,
S.
, 1995, “
A Unified K-BKZ Model for Residual Stress, Analysis of Injection Molded Three-Dimensional Thin Shapes
,”
Polymer
0032-3861,
35
, pp.
1733
1747
.
7.
Fan
,
B.
,
Kazmer
,
D. O.
,
Bushko
,
W. C.
,
Theriault
,
R. P.
, and
Poslinski
,
A. J.
, 2003, “
Warpage Prediction of Optical Media
,”
J. Polym. Sci., Part B: Polym. Phys.
0887-6266,
41
, pp.
859
872
.
8.
Kazmer
,
D. O.
,
Westerdale
,
S.
, and
Hazen
,
D.
, 2008, “
A Comparison of Statistical Process Control (SPC) and On-Line Multivariate Analyses (MVA) for Injection Molding
,”
Int. Polym. Process.
0930-777X,
23
, pp.
447
458
.
9.
Kazmer
,
D.
,
Barkan
,
P.
, and
Ishii
,
K.
, 1996, “
Quantifying Design and Manufacturing Robustness Through Stochastic Optimization Techniques
,”
ASME Design Automation Conference
.
10.
Staczek
,
P.
,
Bogucki
,
M.
, and
Plaska
,
S.
, 2006, “
Modeling of Transverse Mold Shrinkage for the Injection Molded Molds With a Variable Wall Thickness
,”
Advances in Manufacturing Science and Technology
0137-4478,
30
, pp.
49
59
.
11.
Chiang
,
H. H.
,
Himasekhar
,
K.
,
Santhanam
,
N.
, and
Wang
,
K. K.
, 1993, “
Integrated Simulation of Fluid Flow and Heat Transfer in Injection Molding for the Prediction of Shrinkage and Warpage
,”
ASME J. Eng. Mater. Technol.
0094-4289,
115
, pp.
37
47
.
12.
Zhou
,
H. M.
,
Feng
,
W.
,
Geng
,
T.
, and
Li
,
D. Q.
, 2006, “
Residual Thermal Stresses Simulation of Television Panel in the Forming Process. Part 2: Simulations and Validation
,”
Proc. Inst. Mech. Eng., Part C: J. Mech. Eng. Sci.
0954-4062,
220
, pp.
583
591
.
13.
Chen
,
Y.
,
Yi
,
A. Y.
,
Su
,
L.
,
Klocke
,
F.
, and
Pongs
,
G.
, 2008, “
Numerical Simulation and Experimental Study of Residual Stresses in Compression Molding of Precision Glass Optical Components
,”
ASME J. Manuf. Sci. Eng.
1087-1357,
130
, p.
051012
.
14.
Huang
,
J.
, and
Fadel
,
G. M.
, 2001, “
Bi-Objective Optimization Design of Heterogeneous Injection Mold Cooling Systems
,”
ASME J. Mech. Des.
0161-8458,
123
, pp.
226
239
.
15.
Turng
,
L. S.
, and
Peic
,
M.
, 2002, “
Computer Aided Process and Design Optimization for Injection Moulding
,”
Proc. Inst. Mech. Eng., Part B
0954-4054,
216
, pp.
1523
1532
.
16.
Bataineh
,
O. M.
, and
Klamecki
,
B. E.
, 2005, “
Prediction of Local Part-Mold and Ejection Force in Injection Molding
,”
ASME J. Manuf. Sci. Eng.
1087-1357,
127
, pp.
598
604
.
17.
Tandeske
,
D.
, 1991,
Pressure Sensors: Selection and Application
,
Dekker
,
New York
.
18.
Maier
,
C.
, 1996, “
Infrared Temperature Measurement of Polymers
,”
Polym. Eng. Sci.
0032-3888,
36
, pp.
1502
1512
.
19.
Diduch
,
C.
,
Dubay
,
R.
, and
Li
,
W. G.
, 2004, “
Temperature Control of Injection Molding. Part I: Modeling and Identification
,”
Polym. Eng. Sci.
0032-3888,
44
, pp.
2308
2317
.
20.
Yokoi
,
H.
,
Murata
,
Y.
, and
Tsukakoshi
,
H.
, 1992, “
Measurement of Melt Temperature Profiles During Filling and Packing Processes Using a New Integrated Thermocouple Sensor
,”
ANTEC 92-Shaping the Future
, Vol.
2
, pp.
1875
1881
.
21.
Zhao
,
C.
, and
Gao
,
F.
, 1999, “
Melt Temperature Profile Prediction for Thermoplastic Injection Molding
,”
Polym. Eng. Sci.
0032-3888,
39
, pp.
1787
1801
.
22.
Varela
,
A. E.
,
Kamal
,
M. R.
, and
Patterson
,
W. I.
, 1996, “
A Method for Estimating Bulk Melt Temperature and Part Weight in Injection Molding of Amorphous Thermoplastics
,”
Adv. Polym. Technol.
0730-6679,
15
, pp.
17
28
.
23.
Jiang
,
M.
,
Thomas
,
C. L.
,
Peterson
,
R.
, and
Bur
,
A. J.
, 1997, “
New Ultrasonic Solidification Sensing Techniques for Injection Molding
,”
CAE and Intelligent Processing of Polymeric Materials
, ASME International Engineering Congress and Exposition: ASME, Materials Division, pp. 213–222.
24.
Jen
,
C. K.
,
Wen
,
S. S. L.
, and
Nguyen
,
K. T.
, 1999, “
Advances in On-Line Monitoring of the Injection Molding Process Using Ultrasonic Techniques
,”
Int. Polym. Process.
0930-777X,
14
, pp.
175
182
.
25.
Wang
,
H.
,
Cao
,
B.
,
Jen
,
C. K.
,
Nguyen
,
K. T.
, and
Viens
,
M.
, 1997, “
On-Line Ultrasonic Monitoring of the Injection Molding Process
,”
Polym. Eng. Sci.
0032-3888,
37
, pp.
363
376
.
26.
Bur
,
A. J.
, and
Thomas
,
C. L.
, 1996, “
Method and Apparatus for Monitoring Resin Crystallization and Shrinkage During Polymer Molding
,” U.S. Patent No. 5,519,211.
27.
Thomas
,
C. L.
, and
Bur
,
A. J.
, 1999, “
Optical Monitoring of Polypropylene Injection Molding
,”
Polym. Eng. Sci.
0032-3888,
39
, pp.
1291
1302
.
28.
Thomas
,
C. L.
, and
Bur
,
A. J.
, 1999, “
In-Situ Monitoring of Product Shrinkage During Injection Molding Using an Optical Sensor
,”
Polym. Eng. Sci.
0032-3888,
39
, pp.
1619
1627
.
29.
Timoshenko
,
S. P.
, and
Woinowsky-Krieger
,
S.
, 1959, “
Symmetrical Bending of Circular Plates
,”
Theory of Plates and Shells
, 2nd ed.,
McGraw-Hill
,
New York
, pp.
61
63
.
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