WARPAGE ANALYSIS VERIFICATION BETWEEN SIMULATION AND EXPERIMENTAL OF DUMBBELL PLASTIC PART IN THE INJECTION MOULDING PROCESS

Injection moulding is widely used to produce a variety of plastic parts. Its process involved various process parameters, which plays an important roles in influencing the quality and productivity of plastic parts. In this case, the application of Computer Aided Engineering (CAE) software is essenti...

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Main Authors: Md Ali, Mohd Amran, Salmah, Siti, Zolkarnain, Marjom, Umar , Al-amani, RAJA ABDULLAH, RAJA IZAMSHAH, Abu Bakar, Mohd Hadzley, Zulkeflee, Abdullah, Abdul Aziz, Mohd Sanusi
Format: Article
Language:English
Published: Sci.Int.(Lahore 2014
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Online Access:http://eprints.utem.edu.my/id/eprint/13846/1/2014-Amran-ISORIS2014-WARPAGE_ANALYSIS_VERIFICATION_BETWEEN_SIMULATION.pdf
http://eprints.utem.edu.my/id/eprint/13846/
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Summary:Injection moulding is widely used to produce a variety of plastic parts. Its process involved various process parameters, which plays an important roles in influencing the quality and productivity of plastic parts. In this case, the application of Computer Aided Engineering (CAE) software is essential to enhance the quality of plastic parts in the injection moulding industry. This paper deals with the application of Moldflow Plastic Insight (MPI) intergrated with a statistical technique using Taguchi Method. The purpose of this application is to study the effect of process parameters on warpage deflection in dumbbell plastic part. Subsequently, the result of CAE simulation was validated with the aid of experimental data result. The Process parameters involved in this study were core temperature, cavity temperature, melt temperature and cooling time. Based on the simulation and experimental results, it was found that the most significant parameter affected warpage deflection is cavity temperature, followed by core temperature, melt temperature and cooling time. In addition, the results show that the minimum and maximum percentages of the differential of warpage deflection between the simulation and experiment are 4% and 10.89% respectively. Thus, this indicates that there is a good agreement between the simulation and the experimental data result.