Numerical simulation analysis and process optimization of high gloss injection molding of complex st
Time:2020-08-06 09:09:39 / Popularity: / Source:
High gloss injection molding is also known as rapid heat cycle molding (RHCM) and steam-assist injection technology (SAIT). High gloss injection molding can effectively eliminate defects such as weld marks, ripples, silver lines, and floating fibers on the surface of product, improve strength and quality of molded products. Products formed using this technology have higher gloss, can save secondary processing costs, meet consumers’ requirements for thinner and lighter products, better mechanical properties. It is a short-process green production technology.
Now take complex structure of coffee machine shell as research object, use MoldFlow software to simulate process of its high gloss injection molding, combine orthogonal experimental design method and range analysis method, with volume shrinkage, warpage deformation, and sink mark index as main evaluation indicators, use range analysis method and comprehensive balance method to analyze, use signal-to-noise ratio as comprehensive evaluation index to obtain optimal process parameter combination for forming product.
Now take complex structure of coffee machine shell as research object, use MoldFlow software to simulate process of its high gloss injection molding, combine orthogonal experimental design method and range analysis method, with volume shrinkage, warpage deformation, and sink mark index as main evaluation indicators, use range analysis method and comprehensive balance method to analyze, use signal-to-noise ratio as comprehensive evaluation index to obtain optimal process parameter combination for forming product.
1 Highlight injection CAE model
Pro/E software is used to establish a three-dimensional model of product, size of model is 224mm*195mm*177mm. Due to complex structure of original product with holes and protruding structures, there are many rounded corners, which are not conducive to modeling and finite element analysis. Use CAD doctor software to optimize model and import it into MoldFlow software. After modifying grid defect, number of grid cells is 29,200, and matching rate is 92%, which meets process requirements. Set position of gating system of product after modifying grid and get model. Actual product, model and gating system are shown in Figure 1.
(A) Products
(B) Model and gating system
Figure 1 Products,models and gating system
Coffee machine shell is a complex structural part. Product's use environment requires not only good strength and rigidity, but also good heat resistance, oxidation resistance, and good surface gloss. Therefore, ABS/PMMA plastic is used as material.
2 Optimization of high gloss injection molding process parameters
01 Orthogonal experimental design
Compared with multi-factor experiments, orthogonal experimental design is a test method that requires fewer tests and test results can more fully reflect test effect. Evaluation indicators used in orthogonal test include: volume shrinkage during ejection (Y1); warpage deformation (Y2); sink mark index (Y3). Through research on RHCM molding process, select five factors such as melt temperature/℃(A), mold temperature/℃(B), holding pressure/MPa(C), holding pressure time/s(D), injection time/s (E) as evaluation indicators. Level and value of process parameters are formulated according to experience and recommended values of enterprise. Level and factors of test are shown in Table 1. According to selection of level factor table, use L16 (45) orthogonal test table, where L is code of orthogonal table, 16 is number of experiments, 4 is number of levels, and 5 is number of factors. Orthogonal experiment table and test results are shown in Table 2.
02 Data range analysis
Range is difference between maximum value and minimum value in a set of measured values, which reflects range of a set of data fluctuations. In order to obtain relationship between each factor and index, find out trend and law of index changing with factor, seek optimal combination of each factor level, range analysis method is used to obtain range of each process parameter under each level, as shown in Table 3. Kij is mean value of j-th quality index at i-th level under a certain process parameter; i=1~4, representing 4 levels; j=1~3, respectively representing volume shrinkage, warpage deformation, and sink mark index during ejection; Rj represents range of j-th quality index under influence of a certain parameter.
(A) Volume shrinkage rate
(B) Warpage deformation
(C) Sink mark index
Figure 2 Factors affecting trends
Volume shrinkage rate: Holding pressure C has the greatest influence on volume shrinkage rate, followed by melt temperature A, injection time E has the least influence. Effect order of each factor is CABDE, and the best combination of factors is C4A4B4D4E4. Influence trend of factors is as follows As shown in Figure 2(a).
Warpage deformation: mold temperature B has the greatest influence on warpage deformation, followed by melt temperature A, injection time E has the least influence. Order of influence of each factor is BACDE, and the best combination of factors is B1A4C4D1E2. Influence trend of factors is as follows As shown in Figure 2(b).
Sink mark index: Holding pressure C has the greatest influence on sink mark index, followed by melt temperature A, injection time E has the least influence. Effect order of each factor is CABDE, and the best combination of factors is C4A4B4D3E4. Influence trend of factors is as follows As shown in Figure 2(c).
It can be seen from Figure 2 that for melt temperature A, three indicators all show that value obtained at level 4 is the smallest (evaluation criteria of three indicators are the smaller the better), so melt temperature is selected as 260℃.
For mold temperature B, although warpage deformation increases with increase of mold temperature, fluctuation range of warpage deformation is within 0.5mm in whole test, and maximum warpage deformation is 1.426mm. It is very small in actual production, if considering factors of reducing other indicators, other indicators can be well reduced by changing mold temperature, and other indicators can be given priority. Volume shrinkage rate and sink mark index are the smallest when mold temperature is set to level 4. After comprehensive consideration, mold temperature is selected as 130℃.
For packing pressure C, each index is the smallest when packing pressure is set to level 4. It can be seen from Figure 2 that increasing packing pressure can significantly reduce sink mark index. For volume shrinkage rate, increase of holding pressure will first increase its value, and then as pressure increases, volume shrinkage rate will also decrease. Increase of holding pressure will reduce warpage deformation, so holding pressure is selected as 90MPa.
For holding pressure time D, its influence on each factor is not very significant. For sink mark index and volume shrinkage rate, increase of holding pressure time will improve these indicators, but for warpage deformation, the longer holding time, then the greater warpage deformation, because this factor is not significant, pressure holding time is selected as 20s based on experience.
Influence of injection time E on each index is the least significant among five factors. It can be seen from Figure 2 that its influence on each index is also very small, so this factor can be selected as 1.5s based on experience.
In summary, final optimized scheme is A4B4C4D3E1, and evaluation index values obtained by this scheme are shown in Figure 3.
Warpage deformation: mold temperature B has the greatest influence on warpage deformation, followed by melt temperature A, injection time E has the least influence. Order of influence of each factor is BACDE, and the best combination of factors is B1A4C4D1E2. Influence trend of factors is as follows As shown in Figure 2(b).
Sink mark index: Holding pressure C has the greatest influence on sink mark index, followed by melt temperature A, injection time E has the least influence. Effect order of each factor is CABDE, and the best combination of factors is C4A4B4D3E4. Influence trend of factors is as follows As shown in Figure 2(c).
It can be seen from Figure 2 that for melt temperature A, three indicators all show that value obtained at level 4 is the smallest (evaluation criteria of three indicators are the smaller the better), so melt temperature is selected as 260℃.
For mold temperature B, although warpage deformation increases with increase of mold temperature, fluctuation range of warpage deformation is within 0.5mm in whole test, and maximum warpage deformation is 1.426mm. It is very small in actual production, if considering factors of reducing other indicators, other indicators can be well reduced by changing mold temperature, and other indicators can be given priority. Volume shrinkage rate and sink mark index are the smallest when mold temperature is set to level 4. After comprehensive consideration, mold temperature is selected as 130℃.
For packing pressure C, each index is the smallest when packing pressure is set to level 4. It can be seen from Figure 2 that increasing packing pressure can significantly reduce sink mark index. For volume shrinkage rate, increase of holding pressure will first increase its value, and then as pressure increases, volume shrinkage rate will also decrease. Increase of holding pressure will reduce warpage deformation, so holding pressure is selected as 90MPa.
For holding pressure time D, its influence on each factor is not very significant. For sink mark index and volume shrinkage rate, increase of holding pressure time will improve these indicators, but for warpage deformation, the longer holding time, then the greater warpage deformation, because this factor is not significant, pressure holding time is selected as 20s based on experience.
Influence of injection time E on each index is the least significant among five factors. It can be seen from Figure 2 that its influence on each index is also very small, so this factor can be selected as 1.5s based on experience.
In summary, final optimized scheme is A4B4C4D3E1, and evaluation index values obtained by this scheme are shown in Figure 3.
(A) Volume shrinkage rate
(B) Warpage deformation
(C) Sink mark index
Figure 3 Test results of optimized scheme
It can be seen from Figure 3 that volume shrinkage rate obtained by above solution during ejection is 3.831%, warpage deformation is 1.203mm, and sink mark index is 1.723%, which meets molding quality requirements of product.
03 Signal to noise ratio analysis
Refer to test parameters in Taguchi technology as individual variables and use a group with a smaller number of runs to perform optimization tests, without considering interaction between parameters. Use signal-to-noise ratio parameter in Taguchi technology to measure and determine product quality characteristics of each factor at different levels, determine optimal plan. Since test design aims to reduce occurrence of defects, small characteristic in quality characteristic evaluation method is used, that is, the smaller value obtained, the better quality of product. Record signal-to-noise ratio as η, and its calculation formula is:
Among them, n is number of tests; yi is result of i test.
For overall evaluation index, signal-to-noise ratio in Taguchi technology is used for measurement. Formula for comprehensive quality evaluation index is:
For overall evaluation index, signal-to-noise ratio in Taguchi technology is used for measurement. Formula for comprehensive quality evaluation index is:
Among them, yi (i=1, 2, 3) represents product molding volume shrinkage, warpage deformation and sink mark index in turn; qi (i=l, 2, 3) represents weight of each index in turn, taking 35%, 30%, 35% respectively; y is a comprehensive evaluation index for product molding quality. Table 4 shows signal-to-noise ratio of each group of test data and optimized test plan.
It can be seen from Table 4 that fourth group of experimental data has the best results in orthogonal experiments and the smallest signal to noise ratio. However, after continuing to optimize fourth group of experimental data, value of signal to noise ratio obtained by orthogonal experiment is lower than that, which proves correctness of experimental results.
04 Product trial production process and results
Select the best process parameters obtained through orthogonal experimental design and range analysis, form products on injection molding machine. During molding process, surface of mold parts is heated up quickly by using high temperature and high pressure water vapor. When surface temperature of cavity wall exceeds 110 ℃, plasticized plastic melt is injected into closed cavity. At this time, keep mold temperature unchanged. After injection is finished, air supply is stopped, and water vapor in pipe is blown by air pressure. Finally, cooling water is introduced to make mold temperature drop rapidly until it cools, and mold is opened to take out product. High gloss injection molding divides mold temperature control into four stages: heating, high temperature maintenance, cooling, and low temperature maintenance, and quickly realizes above four temperature change processes in a short time, to ensure that technology improves restoration of molding mold and improves surface color difference of product. Compared with traditional injection technology, it has obvious advantages.
Products were randomly selected for testing and assembly, it was found that surface defects such as weld marks, ripples, and air pockets on the products were improved. Actual shape of product is shown in Figure 4.
Products were randomly selected for testing and assembly, it was found that surface defects such as weld marks, ripples, and air pockets on the products were improved. Actual shape of product is shown in Figure 4.
Figure 4 Actual product
Amount of warpage deformation at opening of product is within allowable fluctuation range, surface gloss is good, which reduces post-processing and secondary processing procedures of product, reduces production cost, and improves molding quality of product. Assemble product to coffee machine, matching accuracy of coffee machine barrel bracket and host is improved. Surface treatment of product is carried out after manufacturer's inspection to meet factory requirements.
Recommended
Related
- Technology Frontier | Research on structural characteristics and formation mechanism of defect zones12-08
- Analysis and Improvement of Injection Molding Part Defects - Cold Slug12-08
- Technology Frontier丨Dynamic Analysis of Packing Force of Die Castings12-07
- Understanding physical property table of injection molding materials and setting process parameters12-07
- Technology Frontier | Mold Optimization Design to Solve Leakage Defects of Aluminum Alloy Die Castin12-06