This paper presents the design, optimization, and simulation of plastic toy building blocks using mold flow analysis to mitigate issues like shrinkage, weld lines, and air traps. It highlights the effectiveness of Autodesk Moldflow software in optimizing injection molding processes by reducing costs and trial-and-error methods. The study investigates various factors affecting production cycles and quality, ensuring optimal design parameters for enhanced manufacturability.

1. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 33 editor@iaeme.com
1,2,3
Assistant Professor, Department of Mechanical Engineering, J.S.P.M.’S B.I.T,
Barshi, Solapur, Maharashtra, India
4
Associate Professor, Department of Mechanical Engineering, J.S.P.M.’S B.I.T,
Barshi, Solapur, Maharashtra, India
ABSTRACT
Mold flow simulation helps designers to see how their designs will be resulted after injection
molding process without needing to do the Injection Molding process. The use of simulation
programs saves time and reduces the costs of the Molding system design. Injection molding design
simulation holds an important role in analyzing the outcome of the design. In this paper plastic toy
building block part is analyzed and studied to solve the problems frequent rejections due to as
shrinkage, weld lines, air traps, and sink marks. All the designs were simulated with Autodesk Mold
flow Adviser. Autodesk Simulation Mold flow effectively eliminates the use of trial and error
method by validating and optimizing the design of plastic before production. This not only improves
the quality but also help us to guide about the selection of machines and the production planning.
Keywords: Injection moulding, Mould design, Mold flow simulation, Optimization Plastic Injection
mould, Mould Flow Plastic Advisor (MPA)
1. INTRODUCTION
Injection Moulding is one of the common methods to do the mass-production of plastic
product. Thermoplastics are science's gift to the toy industry. They can be melted at fairly low
temperatures, molded in colors with fine detail, and stand up well to play wear because of their
resilience.. Injection moulding is the most commonly used manufacturing process for the fabrication
of plastic parts. A wide variety of products are manufactured using injection moulding, which vary
greatly in their size, complexity, and application. Injection Molding is the way most of our plastic
toys are created. The material is injected under pressure into a two-part mold. The material is
allowed to cool, the mold is opened, and the solid product inside is ejected into a collection hopper.
Common problems associated with injection molding are numerous.
INJECTION MOLDING METHODS DESIGN, OPTIMIZATION,
SIMULATION OF PLASTIC TOY BUILDING BLOCK BY MOLD
FLOW ANALYSIS
Manmit Salunke1
, Rushikesh Kate2
, Vishwas Lomate3
, Gajanan Sopal4
Volume 6, Issue 6, June (2015), pp. 33-42
Article ID: 30120150606004
International Journal of Mechanical Engineering and Technology
© IAEME: http://www.iaeme.com/IJMET.asp
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
IJMET
© I A E M E

2. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 34 editor@iaeme.com
2. COMPUTER AIDED SIMULATION
Nowadays, Computer Aided Design is not limited to sketching and drafting, but also helps to
create analysable models as needed for computer based process simulation. Moldflow software, used
solution for Digital Prototyping, provides injection molding simulation tools for use on digital
prototypes. Providing in-depth validation and optimization of plastic parts and associated injection
molds, Moldflow software helps study the injection molding processes in use today. The Autodesk
Simulation Moldflow results help to identify the main problem areas before the part is manufactured
that are particularly difficult to predict with traditional methods. In conventional optimization
process includes actual shop floor trials in which pattern, feeder size, shape and location cores,
mould layout, gating etc are required to be changed in each iteration which is associated with
machining cost, tooling cost, modification cost, melting cost, fettling and transportation cost as well
as energy, materials, time are wasted in each trial until and unless the required results are obtained.
Analysis is essential for designing and mould making through simulation step-up and result
interpretation to show how changes to wall thickness, gate location, material and geometry affects
manufacturability and also experiments with “what-if” scenarios before finalizing a design. Injection
Moulding simulation software into the mould design process in order to analyze the product, foresee
the possible defects, and optimize the design to achieve the maximum outcome of the products with
minimum cycle time in each production cycle.
3. PROBLEM DEFINITION
Here a plastic toy building block of 60 mm leangth, 34 mm width and 1 mm thick is
analysed by taking different cases of Model and optimize runner. gating, sprue systems Determine
potential part defects, such as weld lines, air traps, and sink marks, and then rework designs to avoid
these problems. Create feed systems based on inputs for layout, size, and type of components, such
as sprue, runners, and gates.
4. OBJECTIVES OF THE WORK
1. To analyze the behaviour of Thermoplastic material during the production cycle from the
filling phase until the ejection phase.
2. To foresee the possible problem for a product design; and therefore able to op-timize the
design in the mould design process.
3. To achieve the minimum production cycle time
4. To construct a rapid prototyping of the mould cavity design into a standard mould plate.
5.1 Model details
A 3d model of part toy is created in solid Edge software
Fig. 1.1 a) 2D dimension of part Fig. Fig. 1.1 b) Actual toy building block

3. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 35 editor@iaeme.com
Fig.1.1c) Old design (2mm thikness at middle cavity) Fig. 1.1 d) new design (1mmuniform thikness)
Fig.1) 3D cad model of toy part
Fig. 2 Mechanical Properties of ABS material
5.2 Process settings
Melt temperature: 230.0 (C) Mold temperature: 50.0 (C)
Injection locations: 4 Max. machine injection pressure: 180.000 (MPa)
5.3Mold Data
Mold material Tool Steel P-20
Mold dimensions X: 300.00 (mm) Y: 150.00 (mm) Z: 50.02(mm)
Mold plate dimensions A plate: 25.02 (mm) B plate: 25.00 (mm)
5.4Material Data
Family abbreviation-LDPE
Family abbreviation-ABS Familyname -
Acrylonitrile
Familyname-polyethylenes (PE) copolymers (abs, Trade name -(10% Rubber)
Mold Temperature Range 20-70 °C 25-80°C
Melt Temperature 220°C 230°C
Ejection Temperature 80°C 88 °C
Maximum Shear Stress 0.11 MPa 0.28 MPa
Maximum Shear Rate 400001/s 12000 1/s
Modulus Of Elasticity 124 MPa 3500 MPa
Poison Ratio 0.41 0.36
Shear Modulus 43.97 MPa 1287 MPa
Melt Density 0.73537 g/cm3
0.94933 g/cm3
Specific Heat 4230 J/Kg-C 2400 J/Kg-C
Heating/Cooling Rate -0.3333c/s -0.3333c/s

4. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 36 editor@iaeme.com
5.5 Coolant information
Cooling circuit 1 Cooling circuit 2
Inlet coordinate : -320.00, -165.00, 42.00 -320.00, -165.00, -30.00
Temperature 25.0°C 25.0°C
Hose, Diameter 10.00 mm
Hose, Diameter 10.00 mm
Channel, Circular, Diameter (10.00 mm
Flow rate 10.0000 (lit/min) 10.0000 (lit/min)
5.6 Quality prediction for LDPE and ABS materials
Fig.3 a) single Part LDPE Fig.3 b) single Part ABS
Fill analysis for single part toy shows part have good quality when ABS material preffered.
5.7 Optimum molding conditions for ABS material
FIG.4 Optimum processing conditions
Parameter Optimum Value (ABS ) Default Value (ABS )
Mold surface temperature 58 °C 50.0 (C)
Melt temperature 230°C 230.0 (C)
Injection time 5.2 s 6.08

5. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 37 editor@iaeme.com
5.8Feed system cases details
CASE I CASE II CASEIII CASE IV
Sprue
dimensions
Cold, Circular Tapered,
Start Diameter (2.00 mm),
End Diameter (4.00 mm)
Cold, Circular Tapered,
Start Diameter (2.00 mm),
End Diameter (4.00 mm)
Cold, Circular
Tapered, Start
Diameter (5.00
mm), End Diameter
(4.00 mm)
Cold, Circular
Tapered, Start
Diameter (10.00 mm),
End Diameter (8.00
mm)
Runner
dimensions
Cold, Circular, Diameter
(3.00 mm)
Cold, Rectangular, Width
(3.00 mm), Thickness
(2.00 mm)
Cold, Circular,
Diameter (3.00
mm)
Cold, Circular,
Diameter (15.00 mm)
Gate
dimensions
Cold, Circular Tapered,
Start Diameter (3.00 mm),
End Diameter (1.00 mm)
Cold, Rectangular, Width
(2.00 mm), Thickness
(2.00 mm)
Cold, Circular
Tapered, Start
Diameter (3.00
mm), End Diameter
(1.00 mm)
Cold, Circular
Tapered, Start
Diameter (3.00 mm),
End Diameter (1.00
mm)
6. SIMULATION RESULT
6. A Gate Location Analysis
Optimum gate locations may need to be examining by running the filling analysis on
different best gate locations. Figure shows the result of gate location. Blue area represents the best
gate locations for the part.
Fig. 6A) best gate location
6. B Fill Time Analysis result
The Fill time result shows the position of the flow front at regular intervals as the cavity fills.
At the start of injection, the result is dark blue, and the last places to fill are red. If the part is a short
shot, the section which did not fill has no colour. Fill time is the time taken to fill up the part inside
the cavity; it is also to show how the plastic material flows to fill the cavity.
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig .6B) Fill Time Analysis result

6. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 38 editor@iaeme.com
6. C Confidance of fill analysis result
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig . 6C) Confidance of Fill Time Analysis result
6. D Quality prediction analysis result
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig .6D) Quality prediction analysis result
6. E Injection Pressure.
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig . 6E )Injection Pressure result
6. F RESSURE DROP
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig. 6F) pressure drop result

7. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 39 editor@iaeme.com
6 .G TEMPERATURE AT FLOW FRONT
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig. 6G) temperature at flow front result
6 .H. Time To reach ejection Temperature
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig.6H) Time to reach ejection Temperature result
6 .I. AIR TRAP Analysis result
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig. 6 .I) air trap analysis result
6 .J) weld lines analysis result
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
fig. 6J) weld lines analysis result

8. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 40 editor@iaeme.com
6 .L) cooling quality analysis result
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig.6 L) cooling quality analysis result
6. M). Wrap Analysis Result
Fig.A caseI Fig.B caseII Fig.C caseIII Fig.D caseIV
Fig. 6M) Wrap analysis result
7. RESULTS AND DISCUSSION
CASE I CASE II CASEIII CASE IV
Fill tab
Actual filling time
0.72 (s) 0.70 (s) 0.73 (s) 2.22 (s)
Actual Injection pressure 89.170 (MPa) 93.556 (MPa) 80.323 (MPa) 42.029 (MPa)
Clamp force area 71.6304 (cm^2) 69.9443 (cm^2) 71.6304 (cm^2) 105.3522 (cm^2)
Max. clamp force during filling 25.270 (tonne) 22.052 (tonne) 23.043 (tonne) 22.615 (tonne)
Velocity/pressure switch-over at %
volume 97.80 (%) 98.09 (%) 97.85 (%) 97.65 (%)
Velocity/pressure switch-over at time 0.69 (s) 0.68 (s) 0.69 (s) 2.12 (s)
Estimated cycle time 13.06 (s) 13.07 (s) 13.11 (s) 35s
Total part weight at the end of filling 20.594 (g) 20.568 (g) 20.611 (g) 21.208 (g)
Shot volume 23.1581 (cm^3) 22.8886 (cm^3) 23.3743 (cm^3) 72.2383 (cm^3)
Cavity volume 20.8127 (cm^3) 20.8127 (cm^3) 20.8127 (cm^3) 20.8127 (cm^3)
Runner system volume 2.3454 (cm^3) 2.0759 (cm^3) 2.5615 (cm^3) 51.4256 (cm^3)
Pack tab
Maximum clamp force during cycle 25.270 (tonne) 30.742 (tonne) 30.539 (tonne) 27.198 (tonne)
Max. wall shear stress 0.421 0.431 (MPa) 0.480 (MPa) 0.550 (MPa)
Total part weight 20.629 (g) 21.024 (g) 21.143 (g) 21.208 (g)
Cycle time 15.01 15.68 (s) 15.69 (s) 35.00 (s)

9. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 41 editor@iaeme.com
Cooling Quality
Maximum and minimum temperature
variance 5.1 C & -1.2 C
7.8 (C) (C) & -
7.4 C
5.1 (C) & -2.5
(C) 7.3 (C) & -9.5 C
Maximum and minimum cooling time
variance
0.49 (s) & -
0.57 (s)
1.47 (s) & -1.19
(s)
0.49 (s) & -0.57
(s)
1.65 (s) &-1.25
(s)
Cool tab
Maximum temperature, part 49.2 (C) 49.4 c 49.3 (C) 53.5 c
Minimum temperature, part 32.6 (C) 32.5 c 32.6 (C) 34.7 c
Average temperature, part 41.1 (C) 40.9 c 41.1 (C) 45.2 c
Mold exterior temperature 27.4 (C) 27.3 c 27.4 (C) 28.6 (C)
The comparison of initial and modified designs on various parameters
1) Considering initial design for plasic toy, 2mm thikness at moddle cavity, simulation result
showing cooling time of part not uniform and have very high value .Fill analysis shows poor
quality for part. So model is redesigned for unform wall thiknes 1mm .Then simulation result
shows better quality of part.
2) After fill analysis shows part have lower quality for LDPE material and high quality for ABS
material .Different four cases of runner sprue and gate system are analyzed by using ABS
material for plasic toy.
3) In case IV have large filling time and more runner system volume so wastage of material is
high. Case II have lower filling time but more shrinkage.
4) Case I have lower cycle time, high confidence of fill, high quality. So have good optimum
design solution for defect free part.
8. CONCLUSION
The filling time and the cooling time of a four cavity design does not increase to four
times longer than having a single cavity. So the cycle time for four cavities design is the most
optimum and efficient to be used in the production process. The analysis work shows the parameters
such as sink marks, fill time, weld line, air traps etc. that will affects the quality of the finished
product. Plastic Flow Simulation Simulate the flow of melted plastic to help optimize part and mold
designs, reduce potential part defects, and improve the molding process and decrease the cycle time
and to improve the Quality of the Product.
REFERENCE
1. Auto desk Mold-Flow Insight material data warehouse.
2. wikimedia Foundation, Inc, 2010. InjectionMoulding. [online] Available at: <http://en.
wikipedia. org/wiki/Injection_moulding> [Accessed 28 August 2010]
3. Bryce, D. M., ‘Plastic injection molding: Manufacturing process fundamental’. Society of
Manufacturing Engineers, (1996)
4. Sri. P V S M Varma and Sri. P N E Naveen, “Optimizing Injection Moulding Tool Cost by
Using Virtual Software Techniques” International Journal of Mechanical Engineering &
Technology (IJMET), Volume 4, Issue 6, 2013, pp. 227 - 240, ISSN Print: 0976 – 6340,
ISSN Online: 0976 – 6359

10. Injection Molding Methods Design, Optimization, Simulation of Plastic Toy Building Block by Mold Flow
Analysis, Manmit Salunke, Rushikesh Kate, Vishwas Lomate, Gajanan Sopal, Journal Impact Factor (2015):
8.8293 Calculated by GISI (www.jifactor.Com)
www.iaeme.com/ijmet.asp 42 editor@iaeme.com
5. Mr. A.B. Humbe and Dr. M.S. Kadam, “Optimization of Process Parameters of Plastic
Injection Molding For Polypropylene To Enhance Productivity and Reduce Time For
Development” International Journal of Mechanical Engineering & Technology (IJMET),
Volume 5, Issue 5, 2014, pp. 157 - 169, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359
6. Mr. A.B. Humbe and Dr. M.S. Kadam, “Optimization of Critical Processing Parameters For
Plastic Injection Molding of Polypropylene For Enhanced Productivity and Reduced Time
For New Product Development” International Journal of Mechanical Engineering &
Technology (IJMET), Volume 5, Issue 1, 2014, pp. 108 - 115, ISSN Print: 0976 – 6340,
ISSN Online: 0976 – 6359
7. Moldflow Plastic Insight, 2014. Moldflow Tutorial. [Software tutorial] Mold-flow
Corporation
8. Tang, S.H., Kong, Y.M.,Sapuan, S.M., Samin, R., and Sulaiman, S., “Design and thermal
analysis of plastic injection mold” , Journal of Materials Processing Technology, Vol. 171,
pp. 259-267, 2006.
9. http://www.engineersedge.com/injection_molding,.htm, 2006
10. http://www.efunda.com/DesignStandards/plastic_design/plastic_intro.cfm, 2006