Prediction of Process Parameters of New Injection Molding Products Based on Historical Qualified Product Data

Short glass fiber reinforced plastics (SGFRP) offer superior mechanical properties compared to polymers, while still also enabling almost unlimited geometric variations of components at large-scale production. PA6-GF30 represents one of the most used SGFRP for series components, but the impact of injection molding process parameters on the fatigue properties is still insufficiently investigated. In this study, various injection molding parameter configurations were investigated on PA6-GF30. To take the significant frequency dependency into account, tension–tension fatigue tests were performed using multiple amplitude tests, considering surface temperature-adjusted frequency to limit self-heating. The frequency adjustment leads to shorter testing durations as well as up to 20% higher lifetime under fatigue loading. A higher melt temperature and volume flow rate during injection molding lead to an increase of 16% regarding fatigue life. In situ Xray microtomography analysis revealed that this result was attributed to a stronger fiber alignment with larger fiber lengths in the flow direction. Using digital volume correlation, differences of up to 100% in local strain values at the same stress level for different injection molding process parameters were identified. The results prove that the injection molding parameters have a high influence on the fatigue properties and thus offer a large optimization potential, e.g., with regard to the component design.

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Multi-objective optimization of process parameters in plastic injection molding using a differential sensitivity fusion method

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-021-06762-8 ◽

2021 ◽

Vol 114 (1-2) ◽

pp. 423-449

Author(s):

Huifang Zhou ◽

Shuyou Zhang ◽

Zili Wang

Keyword(s):

Injection Molding ◽

Process Parameters ◽

Differential Sensitivity ◽

Plastic Injection Molding ◽

Fusion Method ◽

Multi Objective Optimization ◽

Multi Objective ◽

Optimization Of Process Parameters ◽

Plastic Injection

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Optimization of injection molding process for car fender in consideration of energy efficiency and product quality

Journal of Computational Design and Engineering ◽

10.7315/jcde.2014.025 ◽

2014 ◽

Vol 1 (4) ◽

pp. 256-265 ◽

Cited By ~ 18

Author(s):

Hong Seok Park ◽

Trung Thanh Nguyen

Keyword(s):

Energy Efficiency ◽

Energy Consumption ◽

Injection Molding ◽

Product Quality ◽

Process Parameters ◽

Optimization Problems ◽

Computational Cost ◽

Injection Molding Process ◽

Molding Process ◽

Nsga Ii

Abstract Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using nondominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

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A study of the effects of process parameters for injection molding on surface quality of optical lenses

Journal of Materials Processing Technology ◽

10.1016/j.jmatprotec.2008.08.006 ◽

2009 ◽

Vol 209 (7) ◽

pp. 3469-3477 ◽

Cited By ~ 66

Author(s):

Kuo-Ming Tsai ◽

Chung-Yu Hsieh ◽

Wei-Chun Lo

Keyword(s):

Injection Molding ◽

Surface Quality ◽

Process Parameters

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Warpage and Shrinkage Analysis and Optimization of Rapid Tooling Molded thin Wall Component Using Modified Particle Swarm Algorithm

Journal of Advanced Manufacturing Systems ◽

10.1142/s0219686719500045 ◽

2019 ◽

Vol 18 (01) ◽

pp. 85-102 ◽

Cited By ~ 2

Author(s):

Sagar Kumar ◽

Amit Kumar Singh

Keyword(s):

Injection Molding ◽

Process Parameters ◽

Simulation Analysis ◽

Statistical Significance ◽

Particle Swarm ◽

Processing Parameters ◽

Particle Swarm Algorithm ◽

Thin Wall ◽

Polybutylene Terephthalate ◽

Melt Temperature

This paper presents a systematic methodology to determine optimal injection molding conditions for minimum warpage and shrinkage in a thin wall relay part using modified particle swarm optimization algorithm (MPSO). Polybutylene terephthalate (PBT) and polyethylene terephthalate (PET) were injected in a thin wall relay component for different processing parameters: melt temperature, packing pressure and packing time. Further, Taguchi’s L9 (3[Formula: see text] orthogonal array is used for conducting simulation analysis to consider the interaction effects of the above parameters. A predictive mathematical model for shrinkage and warpage is developed in terms of the above process parameters using regression analysis. ANOVA analysis is performed to establish statistical significance within the injection molding parameters. The analytical model is further optimized using a newly developed MPSO algorithm and the process parameters values are predicted for minimizing shrinkage and warpage. The predicted values of shrinkage and warpage using MPSO algorithm are improved by approximately 30% as compared to the initial simulation values and comparable to previous literature results.

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Optimization of Process Parameters for Vertical-Faced Polypropylene Bottle Injection Molding

Advances in Materials Science and Engineering ◽

10.1155/2018/2635084 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Youmin Wang ◽

Zhichao Yan ◽

Xuejun Shan

Keyword(s):

Injection Molding ◽

Process Parameters ◽

Dwell Time ◽

Optimization Problem ◽

Injection Pressure ◽

Mold Temperature ◽

Orthogonal Test ◽

Injection Molding Process ◽

Injection Time ◽

Melt Temperature

In order to obtain the optimal combination of process parameters for vertical-faced polypropylene bottle injection molding, with UG, the model of the bottle was drawn, and then, one module and sixteen-cavity injection molding system was established and analyzed using Moldflow. For filling and maintaining pressure during the process of infusion bottle injection molding, the orthogonal test table L25 (56) using CAE was designed for injection molding of the bottle, with six parameters such as melt temperature, mold temperature, injection pressure, injection time, dwell pressure, and dwell time as orthogonal test factors. By finding the best combination of process parameters, the orthogonal experiment was completed, the results were analyzed by range analysis, and the order of influence of each process parameter on each direction of optimization was obtained. The prediction dates of the infusion bottle were gained under various parameters, a comprehensive quality evaluation index of the bottle was formulated, and the multiobjective optimization problem of injection molding process was transformed into a single-objective optimization problem by the integrated weighted score method. The bottle parameters were optimized by analyzing the range date of the weighted scoring method, and the best parameter combination such as melt temperature 200°C, mold temperature 80°C, injection pressure 40 MPa, injection time 2.1 S, dwell pressure 40 MPa, and dwell time 40 S was gained.

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