Optimization of Warpage on Plastic Part by Using Genetic Algorithm (GA).

This study was concentrated on the effects of parameters processing on the molded part towards the warpage issues by implementing Computer-Aided Engineering (CAE) which is Autodesk Moldflow Insight (AMI) software for the simulation of the experiment. Details properties of 80 Tonne Nessei NEX 1000 injection molding machine has been used in this study. Acrylonitrile Butadiene Styrene (ABS) was used as the thermoplastic material to mold the front panel housing. The variable parameters of the process are melt temperature, cooling time, packing pressure and packing time. Experimental data are set off by Design of Experiment (DOE) based on face centred Center Composite Design (CCD). The prediction model of warpage will be used in Genetic Algorithm (GA) for optimization of variables to minimize the warpage. The result shows that GA has reduced the warpage value by 36.15%. [ABSTRACT FROM AUTHOR]