Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method
This project focuses on the optimization of injection molding machine using High Density Polyethylene (HDPE) material. The objective of this experiment is to provide statistical evidence for optimizing parameters of the injection molding process. Design of Experiment (DOE) is a powerful technique i...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/20782/1/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method%20-%20Wan%20Noor%20Azrina%20Wan%20Azhari%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/20782/2/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method.pdf |
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| Summary: | This project focuses on the optimization of injection molding machine using High Density Polyethylene (HDPE) material. The objective of this experiment is to provide
statistical evidence for optimizing parameters of the injection molding process. Design of Experiment (DOE) is a powerful technique in order to achieve the high quality of
product especially in mass production industries. This experiment was conducted to find out the optimal parameter setting in Injection Molding process in order to minimize the time, waste and cost. In this case study, the Taguchi method is used. It is an alternative way compared with the traditional method which is inefficient and unreliable with One Factor At A Time (OFAT) approach. The Taguchi method had been chosen in these studies because instead of having to test all possibilities, it only performed as per standard orthogonal arrays to investigate the effects of the entire machining parameters through small number of experiments. The parameter and factor that involved in this
case study are shot size, injection pressure, injection speed and clamping force. After gaining all the parameter and results from the experiment, it will be interpreted in
Minitab 17 software using ANOVA to verify the optimal parameter. The samples yet to be evaluated for weight changes to find the best set of parameter with less value of
shrinkage percentage. Finally, the result proved that the optimum parameter reduced the percentage of shrinkage and ANOVA identified shot size parameter as the most significance input towards volumetric shrinkage. |
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