scholarly journals The Study of Optimal Molding of a LED Lens with Grey Relational Analysis and Molding Simulation

2019 ◽  
Vol 63 (4) ◽  
pp. 278-294 ◽  
Author(s):  
Min-Wen Wang ◽  
Fatahul Arifin ◽  
Van-Hanh Vu
Keyword(s):  
Injection Molding ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Injection Speed ◽  
Relational Analysis ◽  
Total Displacement ◽  
Packing Pressure ◽  
Grey Relational

Injection molding technology is known as the most widely used method in mass production of plastic products. To meet the quality requirements, a lot of methods were applied in optimization of injection molding process parameter. In this study the optimization based on Taguchi orthogonal array and Grey relational analysis (GRA) is used to optimize the injection molding process parameters on a LED lens. The four process parameters are: packing pressure, injection speed, melt temperature and mold temperature. The multi-response quality characteristics are total displacement, volumetric shrinkage, and thermal residual stress. The optimal molding parameters are packing pressure (90 MPa), injection speed (300 mm/sec), melt temperature (270 °C) and mold temperature (90 °C). The luminous uniformity of the LED is 92.61 % and the viewing angle of the LED is 124.76°. Among the four factors, packing pressure plays the key role in reducing total displacement, volumetric shrinkage, and thermal residual stress.

The simulation of the warpage rule of the thin-walled part of polypropylene composite based on the coupling effect of mold deformation and injection molding process

2018 ◽  
Vol 25 (3) ◽  
pp. 593-601 ◽  
Author(s):  
Jixiang Zhang ◽  
Xiaoyi Yin ◽  
Fengzhi Liu ◽  
Pan Yang
Keyword(s):  
Injection Molding ◽  
Coupling Effect ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Plastic Part ◽  
Molding Process ◽  
Melt Temperature ◽  
Packing Pressure ◽  
Thin Walled ◽  
Packing Time

Abstract Aiming at the problem that a thin-walled plastic part easily produces warpage, an orthogonal experimental method was used for multiparameter coupling analysis, with mold structure parameters and injection molding process parameters considered synthetically. The plastic part deformation under different experiment schemes was comparatively studied, and the key factors affecting the plastic part warpage were analyzed. Then the injection molding process was optimized. The results showed that the important order of the influence factors for the plastic part warpage was packing pressure, packing time, cooling plan, mold temperature, and melt temperature. Among them, packing pressure was the most significant factor. The optimal injection molding process schemes reducing the plastic part warpage were melt temperature (260°C), mold temperature (60°C), packing pressure (150 MPa), packing time (2 s), and cooling plan 3. In this situation, the forming plate flatness was better.

Influence of Injection Molding Process Parameters on Sink Marks of Injection Parts Based on Moldflow

2013 ◽  
Vol 347-350 ◽  
pp. 1163-1167
Author(s):  
Ling Bai ◽  
Hai Ying Zhang ◽  
Wen Liu
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Mold Temperature ◽  
Processing Parameters ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Packing Pressure ◽  
Sink Marks ◽  
Research Show

Moldflow software was used to obtain the best gate location and count. Influence of injection molding processing parameters on sink marks of injection-piece was studied based on orthogonal test. The effects of different process parameters were analyzed and better process parameters were obtained. Results of research show that decreasing melt temperature, mold temperature, the increasing injection time and packing pressure can effectively reduce the sink marks index.

Optimization and Design for Parameter in Injection Molding Technology of Cell Shell of Polypropylene

2011 ◽  
Vol 189-193 ◽  
pp. 537-540
Author(s):  
Jia Min Zhang ◽  
Ming Yi Zhu ◽  
Zhao Xun Lian ◽  
Rong Zhu
Keyword(s):  
Injection Molding ◽  
Injection Pressure ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Technological Parameters ◽  
Molding Process ◽  
Melt Temperature ◽  
Injection Speed ◽  
Technical Parameters ◽  
High Degree

The use of L27 (35) orthogonal to the battery shell injection molding process is optimized. The main factors of technical parameters were determined mould temperature, melt temperature, the speed of injection, injection pressure, cooling time.On the basis of actual production, to determine the factors values of different process parameters.Combination of scrapped products in key (reduction and a high degree of tolerance deflated) tests were selected in the process parameters within the scope of the assessment. Various factors impact on the product of the total height followed by cooling time, mold temperature, melt temperature, injection pressure, injection speed from strong to weak .The best products technological parameters were determined.Good results were obtained for production.

scholarly journals Effects of Injection Molding Process Parameters on the Chemical Foaming Behavior of Polypropylene and Polystyrene

Polymers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 2331
Author(s):  
Chen-Yuan Chung ◽  
Shyh-Shin Hwang ◽  
Shia-Chung Chen ◽  
Ming-Chien Lai
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Mold Temperature ◽  
Expansion Ratio ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Foaming Agent ◽  
Experimental Database ◽  
Injection Speed

In the present study, semi-crystalline polypropylene (PP) and amorphous polystyrene (PS) were adopted as matrix materials. After the exothermic foaming agent azodicarbonamide was added, injection molding was implemented to create samples. The mold flow analysis program Moldex3D was then applied to verify the short-shot results. Three process parameters were adopted, namely injection speed, melt temperature, and mold temperature; three levels were set for each factor in the one-factor-at-a-time experimental design. The macroscopic effects of the factors on the weight, specific weight, and expansion ratios of the samples were investigated to determine foaming efficiency, and their microscopic effects on cell density and diameter were examined using a scanning electron microscope. The process parameters for the exothermic foaming agent were optimized accordingly. Finally, the expansion ratios of the two matrix materials in the optimal process parameter settings were compared. After the experimental database was created, the foaming module of the chemical blowing agents was established by Moldex3D Company. The results indicated that semi-crystalline materials foamed less due to their crystallinity. PP exhibits the highest expansion ratio at low injection speed, a high melt temperature, and a low mold temperature, whereas PS exhibits the highest expansion ratio at high injection speed, a moderate melt temperature, and a low mold temperature.

The Application of Moldflow in Injection Molding of the Helmet

2015 ◽  
Vol 1096 ◽  
pp. 366-370
Author(s):  
Yong Cheng Huang ◽  
Hong Bin Liu ◽  
Hai Tao Wu
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Hold Time ◽  
Mold Temperature ◽  
Appropriate Technology ◽  
Injection Molding Process ◽  
Injection Time ◽  
Molding Process ◽  
Melt Temperature ◽  
Packing Pressure

Considering the importance of the reasonable injection molding technology.Based on the application of moldflow in injection molding of the helmet .By adjusting the mold temperature, melt temperature, injection time, packing pressure, hold time and so on the injection molding process parameters to develop appropriate technology methods to get the best injection molding parameters.

scholarly journals Effect of micro injection molding parameters on cavity pressure and temperature assisted by Taguchi method

Mechanika ◽  
2019 ◽  
Vol 25 (4) ◽  
pp. 261-268
Author(s):  
Quan Wang ◽  
Chongying Yang ◽  
Kaihui Du ◽  
Zhenghuan Wu
Keyword(s):  
Injection Molding ◽  
Experimental Work ◽  
Complex Geometry ◽  
Mold Temperature ◽  
Mold Cavity ◽  
Injection Molding Process ◽  
Cavity Pressure ◽  
Molding Process ◽  
Melt Temperature ◽  
Packing Pressure

The injection molding process is one of the most efficient processes where mass production through automation is feasible and products with complex geometry at low cost are easily attained. In this study, an experimental work is performed on the effect of injection molding parameters on the polymer pressure and temperature inside the mold cavity. Different process parameters of the injection molding are considered during the experimental work including packing pressure, packing time, injection pressure, mold temperature, and melt temperature. The cavity pressure is measured with time by using Kistler pressure sensor at different injection molding cycles. The results show the packing pressure is significant factor of affecting the maximum of diverse spline cavity pressure. The mold temperature is significant factor of affecting the maximum cavity temperature. The results obtained specify well the developing of the cavity pressure and temperature inside the mold cavity during the injection molding cycles.

Multi-Objective Optimization in Manufacturing Engineering for Slender Pen Rod Injection Molding Quality Based on Grey Correlation

2013 ◽  
Vol 345 ◽  
pp. 486-493
Author(s):  
Xiao Hong Tan ◽  
Lei Gang Wang ◽  
Wen Shen Wang
Keyword(s):  
Injection Molding ◽  
Grey Relational Analysis ◽  
Injection Molding Process ◽  
Multi Objective Optimization ◽  
Molding Process ◽  
Melt Temperature ◽  
Multi Objective ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper a new approach for the optimization of the multi-objective injection molding process based on the Taguchi robust design combined with the grey relational analysis has been studied. A grey relational grade obtained from the multi-objective grey relational analysis is used to solve the injection molding process with the multiple performance characteristics including volume shrinkage (R1) and axial deformation (R2), the injecting parameters, namely mold temperature, melt temperature, holding pressure and holding time are optimized. By orthogonal polar difference analysis and statistical analysis of variance (ANOVA) of grey relational grade, main factors influencing and the best process parameters were determined: A=50°C,B=250°C,C=30MPa,D=9s.Under the case of continuity factor, Fitting the response surface further the optimal combination of in continuous space r is identified: A=50.3°C,B=250°C,C=29MPa,D=8.3s. Experimental results have shown that the Taguchi combined with the grey relational analysis can avoid human evaluation of the multi-objective optimization, and Injection molding multi-objective optimization is implemented more objectively, and product performance in the process can be improved effectively through this approach.

scholarly journals Towards Optimization of μ-Injection Molding Process for a New V-shaped Geometrical Component Using X-Ray CT-Based Quality Characterization

2019 ◽  
Vol 3 (1) ◽  
pp. 13
Author(s):  
Jitendra Rathore ◽  
Giovanni Lucchetta ◽  
Simone Carmignato
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Functional Performance ◽  
Quality Criteria ◽  
Mold Temperature ◽  
Process Window ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Injection Speed

The influence of micro-injection molding process parameters on a molded component’s quality is very prominent. Depending on the functional performance of the part, the desired quality is defined by several criteria which may include dimensional tolerances, shrinkage/warpage, fiber characteristics, and internal defects. A correlation of process parameters with the defined quality attributes needs to be investigated for a new geometrical component. In this work, a micro-component with a new V-shaped geometry is chosen, as this type of geometry finds potential applications in the medical industry. The parts are manufactured with polyoxymethylene resin with a full-factorial design of experimental plan with investigating parameters of mold temperature, melt temperature, injection speed, and packing pressure. The number of internal pores and amount of volumetric shrinkage are identified as the critical quality criteria and the effect of the process parameters is studied with respect to those criteria. The measurement results indicated that the presence of pores is inevitable within the chosen process window; however, the amount can be minimized with careful selection of process settings. Moreover, the statistical analyses demonstrated the significance levels of the process parameters.

Optimization of Injection Molding Process Parameters with Material Properties Based on GA and BP

2013 ◽  
Vol 345 ◽  
pp. 586-590 ◽  
Author(s):  
Xiao Hong Tan ◽  
Lei Gang Wang ◽  
Wen Shen Wang
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Axial Deformation ◽  
Molding Process ◽  
Melt Temperature ◽  
Bp Network ◽  
Injection Parameters ◽  
Moldflow Simulation

To obtain optimal injection process parameters, GA was used to optimize BP network structure based on Moldflow simulation results. The BP network was set up which considering the relationship between volume shrinkage of plastic parts and injection parameters, such as mold temperature, melt temperature, holding pressure and holding time etc. And the optimal process parameters are obtained, which is agreed with actual results. Using BP network to predict injection parameters impact on parts quality can effectively reduce the difficulty and workload of other modeling methods. This method can be extended to other quality prediction in the process of plastic parts.Keyword: Genetic algorithm (GA);Neural network algorithm (BP);Injection molding process optimization;The axial deformation

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