In order to study the relationship between the main process parameters and the cell size, the mathematical model of cell growth of microcellular foaming injection process is built. Then numeric simulation is employed ...In order to study the relationship between the main process parameters and the cell size, the mathematical model of cell growth of microcellular foaming injection process is built. Then numeric simulation is employed as experimental method, and the Taguchi method is used to analyze significance of effect of process parameters on the cell size. At last the process parameters are focused on melt temperature, injection time, mold temperature and pretidied volume. The significance order from big to small of the effect of each process parameters on cell size is melt temperature, pre-filled volume, injection time, and mold temperature. On the basis of above research, the effect of each process parameter on cell size is further researched. Appropriate reduction of the melt temperature and increase of the pre-filled volume can optimize the cell size effectively, while the effects of injection time and mold temperature on cell size are less significant.展开更多
This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of vari...This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance(ANOVA),a process modeling algorithm by artificial neural network(ANN),and a multi-objective parameter optimization algorithm by genetic algorithm(GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.展开更多
Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining ...Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories： Case-based reasoning methods, expert sys- tem-based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.展开更多
Since plastic products are with the features as light, anticorrosive and low cost etc., that are generally used in several of tools or components. Consequently, the requirements on the quality and effectiveness in pro...Since plastic products are with the features as light, anticorrosive and low cost etc., that are generally used in several of tools or components. Consequently, the requirements on the quality and effectiveness in production are increasingly serious. However, there are many factors affecting the yield rate of injection products such as material characteristic, mold design, and manufacturing parameters etc. involved with injection machine and the whole manufacturing process. Traditionally, these factors can only be designed and adjusted by many times of trial-and-error tests. It is not only waste of time and resource, but also lack of methodology for referring. Although there are some methods as Taguchi method or neural network etc. proposed for serving and optimizing this problem, they are still insufficient for the needs. For the reasons, a method for determining the optimal parameters by the inverse model of manufacturing platform is proposed in this paper. Through the integration of inverse model basing on MANFIS and Taguchi method, inversely, the optimal manufacturing parameters can be found by using the product requirements. The effectiveness and feasibility of this proposal is confirmed through numerical studies on a real case example.展开更多
文摘In order to study the relationship between the main process parameters and the cell size, the mathematical model of cell growth of microcellular foaming injection process is built. Then numeric simulation is employed as experimental method, and the Taguchi method is used to analyze significance of effect of process parameters on the cell size. At last the process parameters are focused on melt temperature, injection time, mold temperature and pretidied volume. The significance order from big to small of the effect of each process parameters on cell size is melt temperature, pre-filled volume, injection time, and mold temperature. On the basis of above research, the effect of each process parameter on cell size is further researched. Appropriate reduction of the melt temperature and increase of the pre-filled volume can optimize the cell size effectively, while the effects of injection time and mold temperature on cell size are less significant.
基金The authors would like to thank the research group that took part in the study for their generous cooperation. Project 50965003 supported by National Natural Science Foundation of China.
基金(Nos. 20806040,61073059 and 61034005) supported by the National Natural Science Foundation of China
文摘This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance(ANOVA),a process modeling algorithm by artificial neural network(ANN),and a multi-objective parameter optimization algorithm by genetic algorithm(GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.
基金The authors would like to acknowledge the financial support from the National Natural Science Foundation of China （Grant Nos. 51675199 and 51635006） and the National Program on Key Basic Research Project （Grant No. 2013CB035805）.
文摘Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories： Case-based reasoning methods, expert sys- tem-based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.
文摘Since plastic products are with the features as light, anticorrosive and low cost etc., that are generally used in several of tools or components. Consequently, the requirements on the quality and effectiveness in production are increasingly serious. However, there are many factors affecting the yield rate of injection products such as material characteristic, mold design, and manufacturing parameters etc. involved with injection machine and the whole manufacturing process. Traditionally, these factors can only be designed and adjusted by many times of trial-and-error tests. It is not only waste of time and resource, but also lack of methodology for referring. Although there are some methods as Taguchi method or neural network etc. proposed for serving and optimizing this problem, they are still insufficient for the needs. For the reasons, a method for determining the optimal parameters by the inverse model of manufacturing platform is proposed in this paper. Through the integration of inverse model basing on MANFIS and Taguchi method, inversely, the optimal manufacturing parameters can be found by using the product requirements. The effectiveness and feasibility of this proposal is confirmed through numerical studies on a real case example.
