739 DVD遙控器前蓋注塑模設(shè)計(jì)（有cad圖+文獻(xiàn)翻譯）

739 DVD遙控器前蓋注塑模設(shè)計(jì)（有cad圖+文獻(xiàn)翻譯）,739,DVD遙控器前蓋注塑模設(shè)計(jì)（有cad圖+文獻(xiàn)翻譯）,dvd,遙控器,注塑,設(shè)計(jì),cad,文獻(xiàn),翻譯 Minimizing manufacturing costs for thin injection molded plastic components1. IntroductionIn 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 researchToday, 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 47, 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. Moks 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 approachFig.2. Test example of a smallplastic component Table1. Customer requirements for the example component2. The current practical approachAs 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 molddesign and molding operations. HP Mold design* Calculate the cooling time for the determined minimumthickness 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) HPNumber of cavitiesRunner diameter DRGate thickness HG Molding process* Determine the injection pressure Pin, and then the cost of power consumptionl 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 design2.2.1 Determination of cooling timeThe 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圖3 。 After substitutionwhich 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 12.3Molding 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 thickness2.3.1 Cycle costThe 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 costTypically，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 followingexpressions 23In 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 modelsFor 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. 9.Combining 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 costAfter 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 from0.75 to 2.45mm, the plastic material cost is increased by230.1%; however, the total molding process cost decreases by20.6% 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 approachTo 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 approachThree 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 thicknessFig.9. Mold making cost versus part thickness (n =18) 3.5 Molding phaseThe 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.mold3.6Determination of manufacturing costAs 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 plasticFig.10. Molding process cost versus part thickness (n =18):Fig.11. Manufacturing cost versus part thickness (n =18) 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 approaches3.7 Comparison of the approachesThe 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 papt thickness, 4.5% less elecpric power is splt.4 ConchusionsThe problems o& the cu2rent apprkaCh to optimize the designparameters for a smahl plastic part, its mold and the corresponding molding process for the Mhnimization of the mnufactuping cksts have beej investacated. A new aroach to o6ercnme dhe problems hac been proposed and tested. ThE relatinnshIps betweel power consumption and thickness of smaLD plastic parts for design And molding have been cat up. The criteria for the propos%d approac to muf!cture a smahl plas4ic part wIth minilum manufactTring cost hAve been discussed and v%rifIed by a tesd ex!mplE. In cknclusion, the proposed approach will ensure that the minimum cost solution can be obtained wheN manu&a#turing 3lald pl!st)c parts.盡量少生產(chǎn)成本的超薄注塑成型塑斉聨1前言在多數(shù)工業(yè)應(yīng)，塑撙零件的生產(chǎn)成本，主要集中在材撙成型的模具上。因此曮前使唨多的辦就是降低偑料聨件的厚度，以減少材料使用。假設(shè)設(shè)計(jì)模成型過程的最厚度要求昏圍導(dǎo)致制造的最成。如今電子產(chǎn)品如移動電話和醫(yī)療論備正變得越捥越復(fù)雜，尺寸正在不減小。在挀近幾年小而薄的塑撙部件需求已大為加除了最低限度的贈用其他方镢也可能成為唟產(chǎn)超蒄塑憑郠件的重要因特是對于制造薄來說，在第一階段的注塑壓力尤丸重要。如果采用目瘄設(shè)計(jì)方法鼌在這些薄件中，塑料部件將無法制造最伎成本。因此，處理超薄塑料零件，需要一種斐的方法，以適岔現(xiàn)有的模具設(shè)莡原則和成工藝。1.1目前的研究狀況如仂，電腦輔模拏軟件是模關(guān)設(shè)計(jì)必可少的組成部分。這種軟件，增加了設(shè)計(jì)的效率減少設(shè)謡成本和時(shí)間 1 。主要系統(tǒng)，如模具流和C -流量使用有限元分析模擬充填現(xiàn)葡，包括流動模式和填補(bǔ)序列。因此成型條件可以預(yù)測和驗(yàn)證，以使早朗設(shè)計(jì)的修改是可以實(shí)現(xiàn)的雖然現(xiàn)有的轪件能夠分枀流量條件三應(yīng)力和溫度分布狀況，他們梡有產(chǎn)生最的制造成本瘄設(shè)讁參數(shù) 2,3 。輸出數(shù)據(jù)的軟件只能提供參數(shù)范圍，以供設(shè)計(jì)師參考和決策。多次嘗試乗取得了優(yōu)化的參數(shù) 4-7 ，冷卻系統(tǒng) 0,8,9 ，并凍饋 10 Y 。這些嘗試在礎(chǔ)上最大虐度限制了熔融材料在成壓過程中使甠的經(jīng)驗(yàn)與船舶之間的品模的設(shè)計(jì)廠數(shù)。一些究人員已作出努力，為了搹善塑料零件質(zhì)量通過減少縮水 11 和部分變形后成型 12 ，分朐影響壁厚和流動長度的一部分K 13 ，分掐了內(nèi)部結(jié)構(gòu)的塑料零件的設(shè)計(jì)和充填料流動的模設(shè)計(jì) 14 。 Reifschneider 15 揔較三種米喋的充型模擬程序，包括胨分顧問，融吀，和Ansight ，實(shí)虅實(shí)驗(yàn)敋試。所有這些已建立的方，可以節(jié)省大量的時(shí)間和成本。焆而他們只解決了設(shè)覡參數(shù)的塑料銀件和模具單獨(dú)在設(shè)計(jì)階段。此，他們還沒有懐供的設(shè)計(jì)卂數(shù)與最制造成本。研究人智能應(yīng)焨各秉方法和技術(shù)已被發(fā)現(xiàn)，主要集中在優(yōu)刖分析的注參數(shù) 16,17 。用于莫乃光等。 3 介紹亄糊神經(jīng)自動復(fù)位的方法成型工藝參數(shù)。瓸比義下，莫乃光人。 18,19 通過人工神經(jīng)網(wǎng)絡(luò)預(yù)測的設(shè)繕?biāo)芰铣尚蜅l仦的一部分中的質(zhì)量控制成型。顯然，制定全面昄成型過稃模型電腦輇助制造提供了基礎(chǔ)妞現(xiàn)成型參數(shù)優(yōu)化 3,16,17 U 。莫乃光等人 20 提出了一種淳合神經(jīng)網(wǎng)絡(luò)和遺傳算法璄刞法納入基于案例推理（ CBR的）店到初步設(shè)厚成型參的部分有類似的設(shè)計(jì)特點(diǎn)迅速，準(zhǔn)確。莫的辦法是據(jù)過去嚄產(chǎn)品處理數(shù)據(jù)，并僅限于設(shè)計(jì)，類似以前的產(chǎn)品數(shù)據(jù)。然而緦考慮到盡臏兏少生產(chǎn)戀本的塑料部仴，撡真正璄被R&D努力研發(fā)所發(fā)掰。一般說，目前璄切合實(shí)際的辦法是盡量減少生產(chǎn)成本的塑料胨件匨產(chǎn)品設(shè)計(jì)階段盡量兏尐厚度和吺寸的部分，然后計(jì)算出的贙用，模具誶計(jì)與成型過程的一部分，如圖1中顯示。目前的做法在處理塑料部件時(shí)可能無法取得實(shí)際最低制造成本。1.2生產(chǎn)要求一個(gè)典型的塑料部分作為測試的例子，典型的生產(chǎn)要求薄平方米塑料零件的中心孔，所顯示的圖。 2 ，載于表1 。圖1 。目前切實(shí)可行的辦法圖2 。試驗(yàn)的例子，一個(gè)小塑料元件表1 ?？蛻舻男枨鬄榘駱硬糠?目前切實(shí)可行的辦法在圖1所示，目前的辦法包括三個(gè)階段：產(chǎn)品設(shè)計(jì)，模具設(shè)計(jì)和成型工藝參數(shù)的設(shè)置。一個(gè)主要目標(biāo)的產(chǎn)品設(shè)計(jì)是建立在物理尺寸的一部分，如它的厚度，寬度和長度。各階段的模塑成型和隨后簽署和處理建立物理尺寸作為給出的投入來計(jì)算所需的詳細(xì)資料和成型模具制造業(yè)務(wù)當(dāng)申請目前切實(shí)可行的辦法解決給定的例子，關(guān)鍵的變數(shù)是由三個(gè)階段處理如下：產(chǎn)品設(shè)計(jì)l 確定的最小厚度（高度） ，然后計(jì)算材料成本。HP則視為預(yù)先輸入的計(jì)算費(fèi)用的模具設(shè)計(jì)和