Meshing

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Moldex3D software is provided several meshing methods to analyze model such as Auto Tetrahedral method, Hybrid Mesh method, and Boundary Layer. The following present characters of each meshing method, based on that the suitable method is chosen to mesh product.

Auto Tetrahedral meshing method is the simplest method for three-dimensional solid mesh creation. Users can easily create tetrahedral mesh from a closed surface. The disadvantage of this method is that it requires more elements per unit volume to achieve the same mesh quality as other types of solid mesh. The mesh quality described here is defined by the quality tables in Moldex3D Mesh and the element layer count across thickness direction. For Auto Tetrahedral meshing, users do not have full control of the element layer count of parts. Thus, sometimes the CAE analysis cannot provide correct temperature distribution in poor quality regions.

On the other hand, the Hybrid meshing is very different from the tetrahedral meshing. People can easily control the mesh quality to meet the solver’s requirement.

The disadvantage of this method is that inexperienced users have to spend more time constructing the mesh. The constructing time of hybrid mesh is three times or more than that of the auto tetrahedral mesh. For most users, it is a big drawback despite the possibility of achieving higher mesh quality.

Moldex3D Mesh provides the Boundary Layer Mesh (BLM) method. For BLM, users do not have to spend much time in solid mesh generation. In addition, the quality of solid mesh provided by BLM is good enough for analysis to obtain accurate results.

Generally, it provides at least five-element layer count across thickness direction for the

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entire part. In that way, the increase in temperature caused by shear heating phenomena at the cavity boundary can be simulated more accurately. Furthermore, the analysis results of the filling pattern, pressure profile, and so on, can be predicted more accurately as well [19]. The Fig.3.11 shows the comparison among different meshing methods in the Modex3D software.

For the dental floss box product to ensure good quality mesh for analysis to obtain accurate results, Boundary Layer Mesh method with level 3 is chosen for analysis simulation. The Fig.3.12, Table 3.6 show product be meshed by Moldex3D 2012 software, and mesh summary, respectively.

Fig.3. 10 The comparison difference among meshing methods [19]

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Fig.3.11 The product is meshed by Moldex3D 2012 Table 3.4 Summary of mesh properties

Mesh Type Boundary Layer Mesh (BLM)

Level mesh 3

Cavity(Part) volume 31.5324 (cc)

Hot runner volume 17.3585 (cc)

Element number 985542

Part elements 985542

Node number 748117

In addition, the injection machine is chosen in the catalogue of Moldex3D software to simulation analysis, when mold base, runner system, cooling system, and mesh all of systems are completed design. The main parameters of injection machine to simulation process are clamping force at 490kN, injection pressure maximum at 240MPa, injection rate maximum at 128cm³/sec.

31 3.3 Taguchi method

3.3.1 Introduction

The Taguchi method developed by Taguchi consists of three stages which are system, parameters, and tolerance designs, respectively. The system design phase is the determining the suitable working levels of design factors. It includes designing and testing a system based on the engineer’s judgment of selected materials, and nominal product process parameters. The parameter design is used to optimize the setting of the process parameter values for improving performance characteristics and to identify the product parameter values under the optimal process parameter values. Moreover, it is expected that the process parameter values obtained from the parameter design are insensitive to the variation of environmental condition and other noise factors.

Therefore, the parameter design and the system design are the key in the Taguchi method to achieving high quality without increasing cost. The tolerance design is used for determining and analysis of the tolerances in optimal settings recommended by the parameter design [22].

The Taguchi method involves reducing the variation in a process through robust design of experiments. The overall objective of the method is to produce high quality product at low cost to the manufacturer. Taguchi developed a method for designing experiments to investigate how different parameters affect the mean and variance of a process performance characteristic that defines how well the process is functioning. 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.

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Instead of having to test all possible combinations like the factorial design, the Taguchi method tests pairs of combinations. This allows for the collection of the necessary data to determine which factors most affect product quality with a minimum amount of experimentation, thus saving time and resources. The Taguchi method is best used when there are an intermediate number of variables (3 to 50), few interactions between variables, and when only a few variables contribute significantly [22].

Taguchi function has three kinds of functions including the smaller is the best, the nominal is the best, and the large is the better. Depending on the requirement of each issue, each function is chosen to appropriate:

1. The smaller is the best

For the case of minimizing the performance characteristic, the following definition of the S/N ratio should be calculated:

S/N = ² the S/N ratio should be calculated:

S/N = ²

For the case of maximizing the performance characteristic, the following definition of the S/N ratio should be calculated:

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n: number of trials for experiment i y: output value

m: target value of output

3.3.2 Methods involve in Taguchi process

In the injection molding process, many factors influence to quality of production such as temperature, pressure, time. The result of influences are shown on defects of product such as air trap, weld lines, short shorts, warpage, shrinkage, etc. However, warpage and shrinkage are important defect, which influence to deformation of product, assembling together, incorrect size. Therefore, warpage and shrinkage are reduced to increase quality of product, this section presents the general steps involved in the Taguchi method are as follows for optimal minimum warpage and shrinkage of the dental floss box [23].

1. Indentify the main objective for optimization: minimum warpage and shrinkage value in the injection molding.

2. Indentify the noise factors, testing conditions, and quality characteristic: melt temperature, injection pressure, packing pressure, packing time, cooling time, mold temperature.

3. Identify the objective function to be optimized: the smaller is the best.

4. The control factors and level: three control factors, that are melt temperature, packing pressure, packing time.

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5. Selection of the optimal levels of design parameters: three levels

6. Conduct the experiments indicated in the completed array to collect data on the effect on the performance measure.

7. Analysis of the experimental results using the Signal to Noise.

8. Complete data analysis to determine the effect of the different parameters on the performance measure.

3.3.3 Determining parameter Design Orthogonal Array

In the injection molding process, there are two main reasons influence to quality of production including design (design part, mold, runner, cooling, plates of mold) and process parameters (temperature, pressure, time). The results of influences are shown on defects of product such as air trap, wield line, short shorts, shrink mark, warpage, shrinkage, etc. However, warpage and shrinkage are important defects which relationship to deformation of product, assembly together, incorrect size. Therefore, warpage and shrinkage should be reduced to increase quality of product in the injection molding industry. In this study, the design issues are considered good for simulation process, and the process parameters are appropriately varied to find out set of optimal parameters in the injection molding of the dental floss box.

There are many parameters effect to characteristic warpage and shrinkage of product such as melt temperature, injection pressure, packing pressure, packing time, cooling time, mold temperature, water temperature, and ect. However, according to research previous and based on trial simulation using moldex3D eDesign demonstrate melt temperature, packing pressure, and packing time which major affect to warpage

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and shrinkage of dental floss box value in the injection molding. Therefore, melt temperature, packing pressure, packing time are chosen for design experiment via Taguchi method to optimal warpage and shrinkage in injection molding dental floss box process.

The effects of several process parameters based on the Taguchi's orthogonal design could be determined effectively from matrix experiments. The process parameters and levels are presented Table 3.5.

Table 3. 5 The process parameters and levels using plan testing

Levels Process parameters

Level 1 Level 2 Level 3

Melt temperature A 280^oC 300 ^oC 320^oC

Packing pressure B 130Mpa 145Mpa 160Mpa

Packing time C 2 s 4 s 6 s

A planning testimg were organized in using Taguchi's L9 (3³) Orthogonal Array based on data in Table 3.5. An experimental plan of three parameters with three levels are organized by the Taguchi method in Table 3.6, and nine-simulations with detail value of Orthogonal Array of Taguchi method shows in Table 3.7. Parameters value of level 2, they are calculated equal average value of these two levels. Other injection

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parameters such as injection pressure, mold temperatures, water temperature are constants and their values are 180MPa, 91.5^oC, and 25^oC, respectively.

Table 3. 6 The experimental layout using an L₉ (3³) Orthogonal Array of Taguchi Process parameters

Table 3.7 Nine- simulations with detail value of Orthogonal Array L9

Parameters

37 parameters to warpage and shrinkage of the product, influence of process parameters to dimension deformation of the product is shown in third part.

The parameters of simulation process are gotten in the Table 3.7. In addition, serve to the research influence of parameter to warpage and shrinkage, the process parameters range are chosen melt temperature range at 280-320^oC, packing pressure range at 100-160MPa, and packing time at 2-6s.

The quality of product depends on following parameters: T_m – melt temperature, Pk – packing pressure, Pj – injection pressure, tp – packing time, tc – cooling time, Tmd – mold temperature, Tnc - water temperature.

4.1 Influence of hot runner system design to quality of product

According to the chapter 3 presented the two cases design of hot runner system (shown in the Fig.3.6 in the chapter 3), this section analyzes results of influence of the two cases design of hot runner system to quality of product. Based on that result, the best method of design hot runner is chosen for simulation process to get high quality of product and small warpage-shrinkage value.

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The Table 4.1 shows simulation results of the two cases design of hot runner system. The case (a) (two gates inject a cavity) using set of parameters are melt temperature at 280^oC, packing pressure at 160MPa, injection pressure at 180MPa. The case (b) (one gate inject a cavity) using set of parameters are melt temperature at 280⁰C, packing pressure at 180MPa, injection pressure at 200MPa. Other parameters as packing time at 6s, mold temperature at 91.5^oC, cooling time at 15s are fixed value.

Table 4.1 Simulation results of the two cases design of hot runner system The result of product when using hot

runner case (a)

The result of product when using hot runner case (a)

Filling process at 20% volume

Filling process at 50% volume

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Filling process at 100% volume

Although injection pressure and packing pressure value in the case (b) is higher than that in the case (a), the results in the Table 4.1 showed the product of the case (b) incompletely filled when the filling process finish simulation. The short short problem appeared on the product surface. Oppositely, the product of the case (a) is completed filling and the short short problem did not appear on the product surface. Therefore, design hot runner of the case (a) is chosen for simulation process in the optimization of warpage and shrinkage process. Because, If using the hot runner system of case (b) must increase pressure or temperature value, that it is main causes create stress in the mold, abrasion of mold, appear flash on the product, and low mold life.

4.2 Influence parameters process to warpage and shrinkage

The section presents influence of melt temperature, packing pressure, packing time to warpage and shrinkage value. The value of each parameter is researched to influence of warpage and shrinkage make changing warpage and shrinkage, that value are varied with each level, other parameter are fixed value in the simulation process.

4.2.1 Influence of melt temperature to warpage and shrinkage

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The melt temperature is a main factor influence to quality of the product such as weld line, burning material, etc. The purpose of this section is research of influence of melt temperature to warpage and shrinkage value of the product, melt temperature value is changed from 280^oC to 320^oC, other parameters are constant value such injection pressure 180MPa, packing pressure at 160MPa, packing time at 6s, cooling time at 15s, and mold temperature at 91.5^oC. The Table 3.4 shows influence results of melt temperature to warpage and shrinkage value.

Table 4.2 Influence results of melt temperature to warpage and shrinkage Summary results of warpage and shrinkage

Result of warpage Result of shrinkage

The value of warpage and shrinkage at 280^oC of melt temperature

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Value of warpage and shrinkage at 290^oC of melt temperature Summary results of warpage and shrinkage

Result of warpage Result of shrinkage

Value of warpage and shrinkage at 300^oC of melt temperature

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Value of warpage and shrinkage at 310^oC of melt temperature Summary results of warpage and shrinkage

Result of warpage Result of shrinkage

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Value of warpage and shrinkage at 320^oC of melt temperature

The Table 4.3 shows summary of warpage and shrinkage value at different melt temperature. The Fig.4.1 illustrate relation between temperature and warpage-shrinkage value. According to the results, when using low or high melt temperature make warpage and shrinkage value increase. Melt temperature at 280^oC creates biggest warpage, its value is 0.293mm. Melt temperature at 320^oC creates biggest shrinkage value. Warpage and shrinkge value are smallest when melt temperature at 300^oC, that value are 0,199mm and 1.695%, respectively.

Table 4. 3 Summary of warpage-shrinkage value at different temperature levels

Factor Levels of melt temperature

Melt temperature (^oC) 280 290 300 310 320

Warpage value (mm) 0.293 0.291 0.199 0.256 0.262 Volumetric shrinkage

value (%) 2.739 1.944 1.695 2.101 2.74

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Fig.4. 1 Relation between melt temperature and warpage-shrinkage value 4.2.2 Influence of packing time to warpage and shrinkage

Using the same method at section 4.2.1 above, the packing time is changed different level from 2s to 6s, other parameters are constant value such as melt temperature at 300^oC, injection pressure 180MPa, packing pressure at 160MPa, cooling time at 15s, and mold temperature at 91.5^oC.

The collection Warpage and shrinkage result present in the Table 4.4. Based on the results in the Table 4.4, the graph is drawn to present relation between packing time and warpage-shrinkage value as shown in Fig.4.2. Packing time at 2s make biggest warpage and shrinkage value. Packing time at 6s creates smallest warpage and shrinkage value.

If packing time continuous increases to 8s then the graph of warpage and shrinkage has upward direction. Therefore, the result also demonstrates when packing time has long enough value in injection molding to get small warpage and shrinkage. In addition, the graph of Fig.4.2 presents the packing time creates 1s for every experiment, that makes warpage and shrinkage value significantly change. Hence , the degree of influence of packing time to warpage and shrinkage is significant in the injection molding process.

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Table 4. 4 Summary of warpage and shrinkage value using different packing time

Factor Levels of packing time

Packing time value

(s) 2 3 4 5 6 8

Warpage value

(mm) 0.468 0.380 0.343 0.300 0.199 0.256

Shrinkage value

(%) 4.007 3.454 2.915 2.142 1.695 2.21

Fig.4. 2 Relation between packing time and warpage- shrinkage value 4.2.3 Influence of packing pressure to warpage and shrinkage

This section presents influence of packing pressure to warpage and shrinkage of the product. Value of packing pressure is changed from 100MPa to 160MPa with four levels as Table 4.6, other parameters are constant value such as melt temperature at 300^oC injection pressure at 180MPa, packing time at 6s, cooling time at 15s, and mold temperature at 91.5^oC.

Table 4. 5 Summary of warpage-shrinkage value using different packing pressure levels

Factor Levels packing pressure

Packing pressure value (MPa) 100 130 145 160

Warpage value (mm) 0.444 0.306 0.256 0.199

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Shrinkage value (%) 3.016 2.74 2.205 1.695

Fig.4. 3 Relation between packing pressure and warpage-shrinkage value

The Table.4.5 shows summary of warpage and shrinkage using different packing pressure levels. Based on the results, the graph is drawn in the Fig.4.3 that presents relation between packing pressure and warpage-shrinkage value. The warpage and shrinkage value has biggest when using packing pressure at 100MPa, their values are 0.444mm and 3.016%, respectively. The packing presure at 160Mpa get smallest warpage and shrinkage, their values are 0.199mm and 1.695%, respectively.

4.3 Influence of process parameters to deformation of the product

This section evaluates displacement of the product length, and tests several curve profiles on the product. The section has two parts, the first parts is building model for testing process, and the second part shows results analysis including the displacement of the product length, and displacement of several curve profiles of the product.

4.3.1 Building model for testing process

Because the dental floss box include three small parts assembled together, deformation of product dimensions have major influence to assembly process. Hence,

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building model to test displacement of the product dimension and displacement of several curve profiles of the product are important to improve quality of the product.

The Fig.4.4 shows some positions of the product tested deformation in the injection molding process. D1, D2, D3 are dimension 1, dimension 2, and dimension 3 of the product length at three positions, and several red lines are curve profiles of the product checked in the injection process.

Fig.4. 4 Several positions of the product in testing process

The Fig.4.5 shows model for testing process to check displacement of the product length, and displacement of several curve profiles. There are total 34 measurement nodes established on the product like the Fig.4.5 (a). The nodes have numbers from 1 to 28 using test displacement of several curve profiles on the product. The curve profiles of the product are tested by nodes as follows: node 1 to node 7 used to test left curve of part 1, node 7 to node 14 used to test right curve of part 1, node 15 to node 21 used to

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test left curve of part 2, and node 22 to node 28 used to test right curve of part 2. The nodes have numbers from 29 to 34 used to test the displacement of the product length.

The distance of the node 29 and node 32, node 30 and node 33, node 31 and node 34 are D1, D2, D3, respectively. The Fig.4.5 (b) presents measurement nodes that are set up to prepare for the simulation process in the Moldex3D 2012 software.

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Fig.4. 5 Model for testing process of the product 4.3.2 Analysis result

The value of X, Y, Z coordinate of measurement nodes in initial state and final state in the injection molding process is shown in the Fig.4.6 when the simulation process is completed in the Moldex3D. The comparison of difference X, Y, Z value of measurement nodes at two states presents deformation the product dimension depended on changing process parameters.

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Fig.4. 6 Data of measure nodes in the injection molding process 4.3.2.1 Measurement D1, D2, D3 dimension

Three D1, D2, D3 dimensions are calculated based on comparison of difference of the node's value in Z value at final states. So equations calculated for D1, D2, D3 are:

D1 = Z₂₉ – Z₃₂ (Dimension 1) (4.1)

D2 = Z30 – Z33 (Dimension 2) (4.2)

D3 = Z31 – Z34 (Dimension 3) (4.3)

D = ^{1 2 3} 3 D D D

(Average dimension of D1, D2, D3) (4.4) X, Y, Z coordinate

of measured nodes at initial states

X, Y, Z coordinate of measured nodes

at final states

Displacement of measured nodes at

final states

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D_TC = 107.5 mm (Standard of the product length shows on Fig.3.1) Table 4.6 Zi value of the each experiment

Z_i coordinate value

51 Based on results in the Table 4.7, the error percent of the product length () can be changed from 0.044% to 0.376%. The values of experiments 1, 6, 8 which has short

51 Based on results in the Table 4.7, the error percent of the product length () can be changed from 0.044% to 0.376%. The values of experiments 1, 6, 8 which has short

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