Optimization Of Injection Moulding Parameters Using Moldflow Simulation Software Analyze By Response Surface Method

The purpose of this study is to optimize injection moulding parameters moldflow simulation software analyze by Response Surface Method(RSM). The process parameters selected for this study are melting temperature, mold temperature, injection time and number of gate. In this study, the RSM using Box –...

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主要作者: Sulaiman, Muhammad Hidayat
格式: Thesis
語言:English
English
出版: 2019
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在線閱讀:http://eprints.utem.edu.my/id/eprint/24943/1/Optimization%20Of%20Injection%20Moulding%20Parameters%20Using%20Moldflow%20Simulation%20Software%20Analyze%20By%20Response%20Surface%20Method.pdf
http://eprints.utem.edu.my/id/eprint/24943/2/Optimization%20Of%20Injection%20Moulding%20Parameters%20Using%20Moldflow%20Simulation%20Software%20Analyze%20By%20Response%20Surface%20Method.pdf
http://eprints.utem.edu.my/id/eprint/24943/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=117724
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機構: Universiti Teknikal Malaysia Melaka
語言: English
English
實物特徵
總結:The purpose of this study is to optimize injection moulding parameters moldflow simulation software analyze by Response Surface Method(RSM). The process parameters selected for this study are melting temperature, mold temperature, injection time and number of gate. In this study, the RSM using Box – Behnken is used to determine the most significant parameters toward the responses and determine the optimum parameters values. Based on the design of experiment, 27 numbers of experimental data are collected and analyse using RSM modelling. The result collected was optimized using RSM meanwhile P-value and R- squared were calculated using analysis of variance (ANOVA). From the result analysis, the injection time is the most significant among the rest of factors toward the fill time response with 99% For volumetric shrinkage and deflection responses, melt temperature and number of gate contribute 58.58% and 60.32% respectively. Then, the interaction between process parameters toward responses are investigated. For response of fill time as the injection time is the only major factor that affect the fill time. As for volumetric shrinkage, the interaction between melt temperature and injection time made a quadratic shape as the increasing in melt temperature increases the shrinkage while the injection time increases the shrinkage up to 2.1s and after that the shrinkage decreases. As for deflection responses, the increasing melt temperature increase the deflection but the interaction from multiple number of gate decreases the deflection Finally, for the multi – response optimization, the optimization are 280oC melt temperature, 120oC mold temperature, 4.0s injection time and one gate. For the desirability of multi – response, it resulted 0.9593 while the predicted value resulted are 0.3593 deflection, 4.2441s fill time and 5.9209 volumetric shrinkage respectively.