注塑模具英文翻译

Minimizing manufacturing costs for thin injection

molded plastic components

1. Introduction

In most industrial applications, the manufacturing cost of a plastic part is mainly governed by the amount of material used in the molding process.

Thus, current approaches for plastic part design and manufacturing focus primarily on establishing the minimum part thickness to reduce material usage.

The assumption is that designing the mold and molding processes to the minimum thickness requirement should lead to the minimum manufacturing cost. Nowadays, electronic products such as mobile phones and medical devices are becoming ever more complex and their sizes are continually being reduced.

The demand for small and thin plastic components for miniaturization assembly has considerably increased in recent years.

Other factors besides minimal material usage may also become important when manufacturing thin plastic components.

In particular, for thin parts, the injection molding pressure may become significant and has to be considered in the first phase of manufacturing.

Employing current design approaches for plastic parts will fail to produce the true minimum manufacturing cost in these cases.

Thus, tackling thin plastic parts requires a new approach, alongside existing mold design principles and molding techniques.

1.1 Current research

Today, computer-aided simulation software is essential for the design of plastic parts and molds. Such software increases the efficiency of the design process by reducing the design cost and lead time [1].

Major systems, such as Mold Flow and C-Flow, use finite element analysis to simulate the filling phenomena, including flow patterns and filling sequences. Thus, the molding conditions can be predicted and validated, so that early design modifications can be achieved. Although available software is capable of analyzing the flow conditions, and the stress and the temperature distribution conditions of the component under various molding scenarios, they do not yield design parameters with minimum manufacturing cost [2,3].

The output data of the software only give parameter value ranges for reference and leaves the decision making to the component designer. Several attempts have also been made to optimize the parameters in feeding [4–7], cooling [2,8,9], and ejection These attempts were based on maximizing the flow ability of molten material during the molding process by using empirical relation ships between the product and mold design parameters.

Some researchers have made efforts to improve plastic part quality by Reducing the

sink mark [11] and the part deformation after molding [12], analyzing the effects of wall thickness and the flow length of the part [13], and analyzing the internal structure of the plastic part design and filling materials flows of the mold design [14]. Reifschneider [15] has compared three types of mold filling simulation programs, including Part Adviser, Fusion, and Insight, with actual experimental testing. All these approaches have established methods that can save a lot of time and cost. However, they just tackled the design parameters of the plastic part and mold individually during the design stage. In addition, they did not provide the design parameters with minimum manufacturing cost.

Studies applying various artificial intelligence methods and techniques have been found that mainly focus on optimization analysis of injection molding parameters [16,17]. For in-stance He et al. [3] introduced a fuzzy- neuro approach for automatic resetting of molding process parameters. By contrast , Helps et al. [18,19] adopted artificial neural networks to predict the setting of molding conditions and plastic part quality control in molding. Clearly, the development of comprehensive molding process models and computer-aided manufacturing provides a basis for realizing molding parameter optimization [3 , 16,17]. Mok et al. [20] propose a hybrid neural network and genetic algorithm approach incorporating Case-Based Reasoning (CBR) to derive initial settings for molding parameters for parts with similar design features quickly and with acceptable accuracy. Mok’s approach was based on past product processing data, and was limited to designs that are similar to previous product data. However, no real R&D effort has been found that considers minimizing manufacturing costs for thin plastic components.

Generally, the current practical approach for minimizing the manufacturing cost of plastic components is to minimize the thickness and the dimensions of the part at the product design stage, and then to calculate the costs of the mold design and molding process for the part accordingly, as shown in Fig. 1.

The current approach may not be able to obtain the real minimum manufacturing cost when handling thin plastic components.

1.2Manufacturing requirements for a typical thin plastic component As a test example, the typical manufacturing requirements for a thin square plastic part with a center hole, as shown in Fig. 2,are given in Table 1.

Fig.1. The current practical approach

Fig.2. Test example of a small

plastic component

Table1. Customer requirements for the example component

2. The current practical approach

As shown in Fig.1, the current approach consists of three phases: product design, mold design and molding process parameter setting. A main objective in the product design is to establish the physical dimensions of the part such as its thickness, width

and length. The phases of molded sign and molding subsequently treat the established physical dimensions as given inputs to calculate the required details for mold making and molding operations.

When applying the current practical approach for tackling the given example, the key variables are handled by the three phases as follows:

Product design

* Establish the minimum thickness (height) HP, and then calculate the material cost. HP is then treated as a predetermined input for the calculation of the costs of mold design and molding operations. HP

Mold design

* Calculate the cooling time for the determined minimum

thickness HP in order to obtain the number of mold cavities required. The mold making cost is then the sum of the costs to machine the:

–Depth of cutting (thickness) HP

–Number of cavities

–Runner diameter DR

–Gate thickness HG

Molding process

* Determine the injection pressure Pin, and then the cost of power consumption

Determine the cooling time t co, and then the cost of machine operations. The overall molding cost is the sum of the power consumption cost and machine operating cost.

The total manufacturing cost is the sum of the costs of plastic material, mold making and molding operations. Note that, in accordance with typical industry practice, all of the following calculations are in terms of unit costs.

2.1 Product design

This is the first manufacturing phase of the current practical approach. The design minimizes the thickness HP of the plastic component to meet the creep loading deflection constraint , Y (<1.47mmafter1yearofusage),and to minimize plastic material usage cost Cm. Minimizing HP requires [21]:

Figure 3 plots changes in HP through Eqs.1 and 2.The graphs show that the smallest thickness that meets the 1.47mm maximum creep deflection constraint is 0 .75mm,with a plastic material cost of $0.000483558/unit and a batch size of 200000 units.

This thickness will be treated as a given input for the subsequent molded sign and molding process analysis phases.

2.2Mold design

2.2.1 Determination of cooling time

The desired mold temperature is 25 C. The determined thickness is 0.75mm. Figure 4 shows the cooling channels layout following standard industry practices. The cooling channel diameter is chosen to be 3mm for this example.

From [22], the cooling time t co:

And the location factor,

BysolvingEqs.3and4, and substituting HP =0.75mm and the given values of the cooling channel design parameters, the cooling time (3.1s) is obtained.

The cycle time t cycle, given by E q. 5, is proportional to the molding machine operating costs, and consists of injection time (t in), ejection time (t e j), dry cycle time (t d c), and cooling time (t c o).

2.2.2 Determination of the number of mold cavities In general, the cost of mold making depends on the amount of machining work to form the required number of cores/cavities, runners, and gates. The given example calls for a two-plate mold

Fig.3.

Deflection and plastic materials costs versus part thickness Fig.4. Cooling channel layout that does not require undercut machining. Therefore, the ma chining work for cutting the runners and gates is proportional to the work involved in forming the cores/cavities and need not be considered. In the example, mold making cost Cmm is governed by (n, HP).

Generally, the minimum number of cavities, Nmin, is chosen to allow for delivery of the batch of plastic parts on time图3 。

After substitution

which is rounded To n =3,since the mold cannot contain 2.64 cavities. The machine operation capacity and the lead-time of production in the example are given as 21.5h/d and 21d, respectively. Moreover, as mentioned in the previous section, the cycle time is directly proportional to the part thickness HP. A curve of batch size against thickness is plotted in Fig. 5. As shown, at HP =0.75mm, the production capability (batch size) is 242470units.Thus the production capability of n =3 is larger than the required lot size (200000units).

For simplicity, the time taken for machining the depth of a thin component is treated as a given constant and added to the required time t CC for making a cavity insert. The C mm can then be calculated by n as expressed [1]

2.3Molding process

In the molding process, the cycle cost and power consumption cost are used to establish the molding operations cost as described in the following sections.

Fig.5. Mold making cost versus part thickness

2.3.1 Cycle cost

The cycle cost C is defined as the labor cost for molding machine operations. The calculation of cycle cost, given by E q. 8, mainly depends on the cycle time and number of mold cavities

For the example, the value of labor cost per hour, L, is given as $1.19/h. Also, Cp can be calculated, as t cycle =20.1sand n = 3 when HP = 0.75mm, as found earlier. And so Cp =$0.0022147/unit.

2.3.2 Power consumption cost

Typically，within the operating cycle of a molding machine，maximum power is required during injection. Hence, longer injection times and higher injection pressures increase the power consumption cost.

For the purposes of this example, an injection time of tin =0.5sisselectedand applied for the molding process。The required hydraulic power PH, power consumption E i, and cost CPC for injection can be found from the following expressions [23]

In E q. 9, 0.8 is the mechanical advantage of the hydraulic cylinder for power transmission during molding, and the resulting electric power cost of CE = HK$1.0476/kWh is given in E q. 11. To find CPC, the sum of the required injection pressures Pin in the feeding system and cavity during molding need to be found. Required injection pressures. Based on the mold layout design, the volume flow rate Q in the sprue is equal to the overall flow rate, and the volume flow rate in each primary and secondary runner will be divided by the separation number, Ni, according to:

The volume flow rate in a gate and cavity equals to that of the runner connecting to them. Tan [24] derived simplified models

For filling circular and rectangul a r channels that can be employed for the feeding system design in this study

1. Sprue and runner (circular channel)

The pressure drop of sprue and runner is express e d a s:

2. Cavity and gate (rectangular channel)

The pressure drop of cavity and gate is expressed as:

Further, the temperature-dependent power law viscosity model can be defined as:

Based on the values of the volume flow rate and consistency index m (T) for each simple unit, the pressure drop P can be found by using E q s. 12to15. Thus, the

required filling pressure is the sum of pressure drops P in the sprue, primary runner, secondary runner, gate, and cavity:

Required power consumption. Given the shape and dimensions of the part and feeding channel, the pressure drops of the sprue , runner, gate , and cavity are obtained through the calculation froE q s. 12 to 15, and are substituted into E q. 16. The required injection pressure Pin is calculated and substituted into the E q.

https://www.360docs.net/doc/a64271961.html,bining E q s. 10 and 11, the power consumption cost CPC is calculated and depends on the variation of injection pressure, which is indirectly affected by the thickness of product as shown in the following E q .17.

After substitution, this becomes:

Then the molding cost

After calculation, C molding = $0.0022147/unit+$0.003755/unit,when HP =0.75mm, n =3.

2.4Remarks on the current practical approach Based on Esq. 8 to 18 it can be shown that as the part thickness,Hp, increases, the necessary injection pressure

Fig.6. Molding process cost versus thickness consumption cost) decreases but the cycle time (and thus labor cost) increases and so there is a minimum total molding process cost, as shown in Fig.6 for the example in this study. As can be seen the minimum molding process cost is Hp =2.45mm.

If the test example part thickness, Hp, were increased from

0.75 to 2.45mm, the plastic material cost is increased by

230.1%; however, the total molding process cost decreases by

20.6% to $0.004741/unit. Moreover, the total manufacturing cost for the part falls by9.54%, a saving of $0.0001174/unit.

Thus, applying the current practical approach does not give the true minimum manufacturing cost. The current practical approach mainly focuses on minimizing the thickness of the part to reduce the plastic material usage and achieve shorter cooling times. When the part is thin, higher injection pressures are needed during the molding process, which substantially increases the molding process costs and consequently shifts the true minimum manufacturing cost for the part away from the minimum thickness solution.

3 The proposed approach

To overcome the shortcoming of the current practical approach, a concurrent approach is proposed for minimizing the manufacturing cost for plastic parts made by injection molding.

3.1Framework of the proposed approach

Three parallel phases of product design, mold design, and molding process setting are undertaken for the proposed approach showninFig.7. The parallel phases handle individual cost functions for material cost, molding cost, and mold making cost,

Which add to yield the total manufacturing cost . The product shape and dimensions (the possible range of thicknesses) are considered as the main design inputs at the beginning of design phase, as shown in Fig. 7.

The proposed approach will provide a possible solution by considering the three phases simultaneously. The outputs are options for combinations of the thickness of the part , the number of mold cavities , and the minimum manufacturing cost that meet all the given requirements.

Fig.8. Creep deflection and plastic material cost versus thickness

Fig.9. Mold making cost versus part thickness (n =1–8)

3.5 Molding phase

The molding process cost is the sum of cycle cost and power consumption cost. Each number of mold cavities has its own curve of molding cost as shown in Fig. 10. Each curve is inversely proportion to the thickness of the plastic component. The lowest point of the curve is the minimum cost. Usually, when the curve has no sharp turning point and asymptotes, it means that enlarging the thickness cannot reduce molding cost very much.

If the thickness of product is increased, lower injection pressure is required during

molding, thus the power consumption cost is reduced, but the cycle time is lengthened and the cycle cost is increased.

As in Fig. 10, assuming an eight cavity mold, the thickness of the plastic part should be less than 2.81mm, with minimum molding cost lessthan$0.00475676/unit.mold

3.6Determination of manufacturing cost

As discussed, the results obtained in sections 3.3, 3.4, and 3.5 can be combined to yield a total manufacturing cost that is the summation of the part design, mold making, and molding process costs. Eight different curves have beendrawninFig.11, for the different numbers of mold cavities. The minimum manufacturing cost is obtained from the lowest point among the eight curves in this study. From Fig.11, the thickness of the plastic

Fig.10. Molding process cost versus part thickness (n =1–8):

Fig.11. Manufacturing cost versus part thickness (n =1–8)

component is 1.44mm, with minimum manufacturing cost of $0.00843177/unit and n =3.

The lowest manufacturing cost is obtained after inputting all values of thickness and numbers of cavities with in the allowable range, 0.01mm to 6mm and 1 to 8, respectively.

Table2. Comparison of results for the different approaches

3.7 Comparison of the approaches

The results for the current and proposed approaches are summarized in Table 2. When the thickness is increased from 0.75 to 1.44mm, the plastic material cost increases by 92%, but reduces total manufacturing cost by 72.4%. An improvement of 85.9% for the creep deflection is also obtained in the functional design. Further, with the 1.44mm part thickness, 34.5% less electric power is spent.

4 Conclusions

The problems of the current approach to optimize the design parameters for a small plastic part, its mold and the corresponding molding process for the minimization of

the manufacturing costs have been investigated. A new approach to overcome the problems has been proposed and tested. The relationships between power consumption and thickness of small plastic parts for design and molding have been set up. The criteria for the proposed approach to manufacture a small plastic part with minimum manufacturing cost have been discussed and verified by a test example. In conclusion, the proposed approach will ensure that the minimum cost solution can be obtained when manufacturing small plastic parts.

尽量减少生产成本的超薄注塑成型塑料部件

1前言

在多数工业应用中，塑料零件的生产成本，主要集中在材料成型的模具上。

因此，目前使用最多的办法就是降低塑料部件的厚度，以减少材料使用。

假设设计模具及成型过程的最小厚度要求是直接导致制造的最低成本。

如今，电子产品如移动电话和医疗设备正变得越来越复杂，其尺寸正在不断减小。在最近几年小而薄的塑料部件需求已大为增加

除了最低限度的物质使用其他方面也可能成为生产超薄塑料部件的重要因素

特别是对于制造薄件来说，在第一阶段的注塑压力尤为重要。

如果采用目前的设计方法，在这些薄件中，塑料部件将无法制造最低成本。

因此，处理超薄塑料零件，需要一种新的方法，以适应现有的模具设计原则和成型工艺。

1.1目前的研究状况

如今，电脑辅助模拟软件是模具设计必不可少的组成部分。这种软件，增加了设计的效率，减少设计成本和时间[ 1 ] 。主要系统，如模具流和C -流量，使用有限元分析，模拟充填现象，包括流动模式和填补序列。因此，成型条件可以预测和验证，以使早期设计的修改是可以实现的。虽然现有的软件能够分析流量条件下应力和温度分布状况，他们没有产生最低的制造成本的设计参数哦[ 2,3 ] 。输出数据的软件只能提供参数值范围，以供设计师参考和决策。

多次尝试也取得了优化的参数 [ 4-7 ] ，冷却系统[ 2,8,9 ] ，并反馈[ 10 ] 。这些尝试在基础上最大限度地限制了熔融材料在成型过程中使用的经验与船舶之间的产品和模具的设计参数。一些研究人员已作出努力，为了改善塑料零件质量通过减少缩水[ 11 ]和部分变形后成型[ 12 ] ，分析影响壁厚和流动长度的一部分[ 13 ] ，并分析了内部结构的塑料零件的设计和充填材料流动的模具设计[ 14 ] 。 Reifschneider [ 15 ]比较三种类型的充型模拟程序，包括部分顾问，融合，和Insight ，实际实验测试。所有这些已建立的方法，可以节省大量的时间和成本。然而，他们只是解决了设计参数的塑料零件和模具单独在设计阶段。此外，他们还没有提供的设计参数与最低制造成本。

研究人工智能应用各种方法和技术已被发现，主要集中在优化分析的注塑参数[ 16,17 ] 。用于莫乃光等人。 [ 3 ]介绍了模糊神经自动复位的方法成型工艺参数。相比之下，莫乃光等人。 [ 18,19 ]通过人工神经网络预测的设置和塑料成型条件的一部分中的质量控制

成型。显然，制定全面的成型过程模型和电脑辅助制造提供了基础，实现成型参数优化[ 3,16,17 ] 。莫乃光等人 [ 20 ]提出了一种混合神经网络和遗传算法的办法纳入基于案例推理（ CBR的）得到初步设定成型参数的部分有类似的设计特点迅速，准确。莫的办法是根据过去的产品处理数据，并仅限于设计，类似以前的产品数据。然而，考虑到尽量减少生产成本的塑料部件，没有真正的被R&D努力研发所发现。

一般来说，目前的切合实际的办法是尽量减少生产成本的塑料部件在产品设计阶段尽量减少厚度和尺寸的部分，然后计算出的费用，模具设计与成型过程的一部分，如图1中显示。

目前的做法在处理塑料部件时可能无法取得实际最低制造成本。

1.2生产要求

一个典型的塑料部分作为测试的例子，典型的生产要求薄平方米塑料零件的中心孔，所显示的图。2 ，载于表1 。

图1 。目前切实可行的办法

图2 。试验的例子，一个小塑料元件

表1 。客户的需求为榜样部分

2目前切实可行的办法

在图1所示，目前的办法包括三个阶段：产品设计，模具设计和成型工艺参数的设置。一个主要目标的产品设计是建立在物理尺寸的一部分，如它的厚度，宽度和长度。各阶段的模塑成型和随后签署和处理建立物理尺寸作为给出的投入来计算所需的详细资料和成型模具制造业务

当申请目前切实可行的办法解决给定的例子，关键的变数是由三个阶段处理如下：

产品设计

●确定的最小厚度（高度），然后计算材料成本。HP则视为预先输入的计算费用的模具

设计和成型业务。

模具设计

*计算冷却时间确定最低厚度HP，以获得一些模具腔需要。模具制造成本是下列参数费用的总和：

–切削深度（厚度）

–模具腔数量

–转轮直径

–G浇注系统厚度

模具生产

* 确定射出压力引脚，和能耗成本

●确定共同的冷却时间t ，和机器的成本运作。整体成型费用的总和，能耗成本和机器的

运行成本。

总制造成本是塑料材料费用的总和，模具制造及成型工艺的总和。请注意，根据典型的行业惯例，以下所有的计算方面的单位成本

2.1 产品设计

这是第一阶段的制造业目前的实际做法。设计最小厚度HP的塑料组件，以满足蠕变载入中挠度约束坐标“（< 1.47mm经过一年的使用），并尽量减少使用塑料材料成本。尽量减少厚度HP需要[ 21 ] ：

图3地块的变化，HP通过Eqs.1和图2表明，最小厚度符合一点四七毫米最大蠕变变形的制约因素是0 0.75毫米，以塑料材料费用为$0.000483558/unit和一批规模200000单位。

这厚度将被视为一个特定的投入，随后签署和模压成型过程的分析阶段。

2.2模具设计

2.2.1测定冷却时间

理想的模具温度为25 c.在确定厚度0.75毫米。图4显示了冷却通道布局下列标准行业惯例。冷却通道直径为3毫米作为例子。

从[ 22 ] ，冷却时间t的合作：

和位置的因素

通过求解Eqs.3和4 ，而代以HP= 0.75毫米和提供价值的冷却通道的设计参数，获得冷却时间（3.1s ）。通过图9.5得到循环周期的时间t ，是成正比的成型机运营成本，并包括注射时间，浇注时间，干燥周期时间，和冷却时间。

2.2.2一般来说一些模具腔，模具制造费用的数额取决于加工的工作，形成所需数目的核心/腔，横浇道，和浇注系统。给定的例子叫做两板模具

图3 。

挠度及塑胶原料成本与部分厚度

图4。冷却通道的布局，不需要削弱加工。因此，在机器工作的切削加工浇道和浇口所涉及的工作，形成了核心/腔，不必加以考虑。在这个例子中，模具制造成本转换是由（n，HP）给与。

一般而言，最低数量的型腔数，Nmin ，由及时运送的一批塑料零件所选择

再替代，

这是四舍五入到n = 3 ，因为模具不能包含2.64该机器操作能力和准备时间的生产实例为21.5h / d和21d。此外，提到在上一节中，周期时间是成正比的。曲线的批量大小对厚度在图5中绘制。如表所示，在HP= 0.75毫米，年生产能力（批处理大小）是242470units.由于生产能力n=3大于所需的批量（200000units ）。

为了简洁明了，所需要的时间用于加工的深度，为了模具腔插入薄薄的部分将被视为某一常数和增加所需的时间tCC为了模具腔插入。在C毫米然后可以计算由N所表达[ 1 ]

2.3成型过程

在成型过程中，周期成本和能耗的费用是用来建立以下各节中所描述的成型工艺成本。图5 。模具制造成本与部分厚度

2.3.1周期成本

该周期成本C是指成型机操作的劳动成本。计算周期成本，因为通过E q。8 ，主要依赖于周期的时间和模具腔数量：

例如，劳动力成本的价值每小时C L, is given as $1.19/h. Also, Cp can be calculated, as t cycle =20.1sand n = 3 when HP = 0.75mm, as found earlier. And so Cp =$0.0022147/unit.

2.3.2能耗费用

通常情况下，营业周期内的成型机，最大功率时需要注射。因此，较长时间和较高的注射液注射压力增加了能耗成本。

就本条而言，例如，注射时间tin = 0.5sisselectedand用于成型过程。所需的液压动力PH 值，耗电量和成本每次注射可从下表[ 23 ] ：

在E q.9 ，0.8是机械利用液压缸输电成型，以及由此产生的在Eq.11均衡器上电力成本的CE= HK$1.0476/kWh。若要寻找CPC的总和，需要注射压力Pin的进给系统和腔成型过程中所需要的注射压力。基于模具的布局设计，体积流量Q在浇道等于总流量和流速的数量在每个初级和中级阶段将被离职数量所分割，

通过