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Minimizing manufacturing costs for thin injection molded plastic componentsAbstract： Minimizing the cost of manufacturing a plastic component is very important in the highly competitive plastic injection molding industry. The current approach of R&D work focuses on optimizing the dimensions of the plastic component particularly in reducing the thickness of the component duringProduct design the first phase of manufacturing in order to minimize the manufacturing cost.。This approach treats the component dimensions established in the product design phase as the given input, and uses optimization techniques to reduce the manufacturing cost of mold design and molding for producing the component. In most cases, the current approach provides the correct solution for minimizing the manufacturing cost. However, when the approach is applied to a thin component typically when miniaturizing products,it has problems finding the true minimum manufacturing cost.This paper analyses the shortcomings of the current approach for handling thin plastic components and proposes a method to overcome them. A worked example is used to illustrate the problems and compare the differences when using the current approach and the new method proposed in the paper.Keywords Miniaturization of plastic parts Minimization of manufacturing Plastic part design and manufacturing cost .NomenclatureThe thickness of gateThe thickness of the rectangular channelLatent heat offusion ofPP=130kJ/kgThe length of gate=0.51.3The length of circular channelThe length of rectangular channelthe consistency index1/Poisson ratio of PP=0.35Plasticmaterial constant,The volume flow rateThe volume flow rateinside the rectangular channelThe volume flow rateinside the circularchannelThe radius of the circularchannelDistance of piston movementLoading time=31536000sTime for making single cavity mold insert=15hDry cycle time=16.5sEjection time=0.009sInjection time=0.5sDemolding temperature of PP=70 CMelt temperature ofPP=190 CThe width of gateThe width of the rectangular channelthe viscosityStrain of materialsStress of materialsThermal conductivity of steel=45W/mKShear stress of plastic materialShear rate of plastic materialPressure drop of spruePressure drop of secondary runnerPressure drop of tertiary runnerPressure drop of gatePressure drop of cavityPressure drop of circular channelPressure drop of rectangular channelJ.K.L.Ho () K.F.Chu C.K.MokDepartment of Manufacturing Engineering & Engineering Management,City University of Hong Kong,P.R. China香港大学工程制造与管理学院E-mail: .hkTel.: +852-27888425Fax: +852-278884231 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.1.1Current 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.2.1Product 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图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 mak