scholarly journals Processing Optimization for Metal Injection Molding of Orthodontic Braces Considering Powder Concentration Distribution of Feedstock

Polymers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2635
Author(s):  
Chao-Ming Lin ◽  
Jhih-Jyun Wu ◽  
Chung-Ming Tan
Keyword(s):  
Injection Molding ◽  
Metal Powder ◽  
Concentration Distribution ◽  
Metal Injection Molding ◽  
Molding Process ◽  
Melt Temperature ◽  
Powder Concentration ◽  
Aesthetic Appearance ◽  
Filling Time ◽  
Sintered Product

Metal injection molding (MIM) utilizes a compound consisting of metal powder particles and a binding agent as the feedstock material. The present study combines MIM mold flow simulations with the Taguchi method to clarify the individual and combined effects of the main MIM process parameters on the metal powder concentration distribution in the final sintered product. The results show that the molding process should be performed using a short filling time, a high melt temperature, a low packing pressure, a low mold temperature, and a small gate size. Given these process settings, the powder concentration uniformity and phase separation effect are significantly improved; giving rise to a better aesthetic appearance of the final sintered product and an enhanced mechanical strength.

The Effect of Injection Molding Process Parameters on the Buckling Properties of PBT/Short Glass Fiber Composites

2011 ◽  
Vol 284-286 ◽  
pp. 550-556 ◽  
Author(s):  
Ming Hsiung Ho ◽  
Pin Ning Wang ◽  
Chin Ping Fung
Keyword(s):  
Injection Molding ◽  
Glass Fiber ◽  
Process Parameters ◽  
Injection Molding Process ◽  
Skin Area ◽  
Molding Process ◽  
Melt Temperature ◽  
Short Glass Fiber ◽  
Filling Time ◽  
Short Glass

This study investigates the effect of various injection molding process parameters and fiber amount on buckling properties of Polybutylene Terephthalate (PBT)/short glass fiber composite. The buckling specimens were prepared under injection molding process. These forming parameters about filling time, melt temperature and mold temperature that govern injection molding process are discussed. The buckling properties of neat PBT, 15 wt%, and 30 wt% are obtained using two ends fixed fixture and computerized closed-loop server-hydraulic material testing system. The fracture surfaces are observed by scanning electron microscopy (SEM). The global buckling forces are raised when increased the fiber weight percentage of PBT. Also, the fracture mechanisms in PBT and short glass fiber matrix are fiber pullout in skin area and fiber broken at core area. It is found that the addition of short glass fiber can significantly strengthen neat PBT.

scholarly journals Optimization for Reducing Warpage in Injection Moulding

2018 ◽  
Vol 2 (5) ◽  
pp. 25-31
Author(s):  
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Large Scale ◽  
Simulation Software ◽  
Optimum Process ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Product Cycles ◽  
Filling Time

Injection molding is a standout technique utilized for the fabrication of thermoplastic parts in industry due to short product cycles, high part quality, good mechanical properties and low cost for large scale manufacturing. In molded case circuit breaker (MCCB), Trip-bar is one of the most critical components as safety is concerned which is manufactured by injection molding process. To get it manufactured within the specified warpage and deformities free, number of mold flow simulations is carried out using Creo-MoldFlow. The outcomes of the simulation are used to design the mold tool and the process parameters for injection molding are optimized. For process parameter optimization Taguchi based experimental design and ANOVA analysis is done. The objective of this work is to optimize the injection molding process parameters such as filling time, melt temperature and mold temperature to minimize the warpage. CAE flow simulation software is used to simulate the process and Grey Relational Analysis (GRA) is used to find out optimum process parameters.

Performance Predictor for Thin-Wall Plastic Parts Produced by Injection Molding

2000 ◽  
Author(s):  
H. P. Wang ◽  
Sreeganesh Ramaswamy ◽  
Irene Dris ◽  
Erin M. Perry ◽  
Dominic Gao
Keyword(s):  
Injection Molding ◽  
Process Development ◽  
Injection Molding Process ◽  
Thin Wall ◽  
Molding Process ◽  
Melt Temperature ◽  
Shear Degradation ◽  
Development Cycle ◽  
Filling Time ◽  
Plastic Parts

Abstract The objective of this work was to develop a numerical simulation tool that is able to predict the processing window for thin-wall plastic parts made by the injection molding process. This performance predictor links the processing conditions (filling time, resin inlet melt temperature, and so on) to the mechanical properties and failure mechanisms of the part, using empirical data developed for the thermal and shear degradation behavior of the resin. Usage of such a performance predictor will help to expedite the long process development cycle time and to reduce the potentially expensive tooling costs associated with the thin-wall segment of the plastics business.

Numerical Optimization of Shrinkage and Warpage on the Injection Molding Process Parameters of Electrical Connector

2017 ◽  
Vol 868 ◽  
pp. 183-191 ◽  
Author(s):  
Yun Wang ◽  
Li Yu Chen ◽  
Xia Ming Yang ◽  
Yan Zhao ◽  
Zhen Ying Xu ◽  
...  
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Mold Temperature ◽  
Influential Factors ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Influence Of Process Parameters ◽  
Filling Time ◽  
The Impact

Integrated with orthogonal design method and numerical simulation, injection molding process of the Y-type electrical connectors was conducted to study the influence of process parameters on volume shrinkage rate and maximum warpage, which are regarded as product quality indices. The multi-indices valuation model for the main influencing factors of the process is developed. The influencing sensitivity to the multi-objective of the processing parameters, such as melt temperature, mold temperature, injection time and holding pressure, is determined by range analysis. Through analyzing the diagrams of influential factors, the optimized process parameter diagram is obtained and verified by simulation. The optimum parameters minimizing the warpage defect and shrinkage are: melt temperature (528K), mold temperature (338K), filling time (0.6s), holding pressure (100%) and holding time (10s). The results show that it is effective to balance the impact of process parameters on the shrinkage and warpage. The work can provide optimal design and process reference for the quality control and assembly precision.

scholarly journals Induced network-based transfer learning in injection molding for process modelling and optimization with artificial neural networks

2021 ◽  
Vol 112 (11-12) ◽  
pp. 3501-3513
Author(s):  
Yannik Lockner ◽  
Christian Hopmann
Keyword(s):  
Injection Molding ◽  
Transfer Learning ◽  
Injection Molding Process ◽  
Process Data ◽  
Molding Process ◽  
Melt Temperature ◽  
Processing Industry ◽  
Source Models ◽  
Plastics Processing ◽  
Artificial Neural

AbstractThe necessity of an abundance of training data commonly hinders the broad use of machine learning in the plastics processing industry. Induced network-based transfer learning is used to reduce the necessary amount of injection molding process data for the training of an artificial neural network in order to conduct a data-driven machine parameter optimization for injection molding processes. As base learners, source models for the injection molding process of 59 different parts are fitted to process data. A different process for another part is chosen as the target process on which transfer learning is applied. The models learn the relationship between 6 machine setting parameters and the part weight as quality parameter. The considered machine parameters are the injection flow rate, holding pressure time, holding pressure, cooling time, melt temperature, and cavity wall temperature. For the right source domain, only 4 sample points of the new process need to be generated to train a model of the injection molding process with a degree of determination R2 of 0.9 or and higher. Significant differences in the transferability of the source models can be seen between different part geometries: The source models of injection molding processes for similar parts to the part of the target process achieve the best results. The transfer learning technique has the potential to raise the relevance of AI methods for process optimization in the plastics processing industry significantly.

Determination of Optimum Process Parameters in Gas-Assisted Injection Molding

2011 ◽  
Vol 143-144 ◽  
pp. 494-498
Author(s):  
Ke Ming Zi ◽  
Li Heng Chen
Keyword(s):  
Injection Molding ◽  
Delay Time ◽  
Optimization Design ◽  
Gas Pressure ◽  
Optimum Process ◽  
Injection Molding Process ◽  
Technological Parameters ◽  
Molding Process ◽  
Element Analysis ◽  
Melt Temperature

With finite element analysis software Moldflow, numerical simulation and studies about FM truck roof handle were conducted on gas-assisted injection molding process. The influences of melt pre-injection shot, gas pressure, delay time and melt temperature were observed by using multi-factor orthogonal experimental method. According to the analysis of the factors' impact on evaluation index, the optimized parameter combination is obtained. Therefore the optimization design of technological parameters is done. The results show that during the gas-assisted injection molding, optimum pre-injection shot is 94%,gas pressure is 15MPa,delay time is 0.5s,melt temperature is 240 oC. This study provided a more practical approach for the gas-assisted injection molding process optimization.

scholarly journals Effects of Injection Molding Screw Tips on Polymer Mixing

2018 ◽  
Vol 62 (3) ◽  
pp. 241-246 ◽  
Author(s):  
Dániel Török ◽  
József Gábor Kovács
Keyword(s):  
Injection Molding ◽  
Processing Parameters ◽  
Raw Material ◽  
Molding Machine ◽  
Surface Color ◽  
Melt Temperature ◽  
Injection Molding Machine ◽  
Aesthetic Appearance ◽  
Molded Parts ◽  
Injection Molded

In all fields of industry it is important to produce parts with good quality. Injection molded parts usually have to meet strict requirements technically and aesthetically. The aim of the measurements presented in our paper is to investigate the aesthetic appearance, such as surface color homogeneity, of injection molded parts. It depends on several factors, the raw material, the colorants, the injection molding machine and the processing parameters. In this project we investigated the effects of the injection molding machine on surface color homogeneity. We focused on injection molding screw tips and investigated five screw tips with different geometries. We produced flat specimens colored with a masterbatch and investigated color homogeneity. To evaluate the color homogeneity of the specimens, we used digital image analysis software developed by us. After that we measured the plastication rate and the melt temperature of the polymer melt because mixing depends on these factors. Our results showed that the screw tips (dynamic mixers) can improve surface color homogeneity but they cause an increase in melt temperature and a decrease in the plastication rate.

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