Warpage Optimization on Battery Cover Using Genetic Algorithm (GA)

被引：1

作者：

Hazwan, M. H. M. ^{[1
]}

Shayfull, Z. ^{[2
,3
]}

Nawi, M. A. M. ^{[1
]}

Ahmad, M. ^{[1
]}

Syafiq, Mohamad A. K. ^{[1
]}

Roslan, A. M. ^{[1
]}

机构：

[1] Univ Malaysia Perlis, Sch Engn Technol, Kampus UniCITI Alam, Padang Besar 02100, Perlis, Malaysia

[2] Univ Malaysia Perlis, Sch Mfg Engn, Kampus Tetap Pauh Putra, Arau 02600, Perlis, Malaysia

[3] Univ Malaysia Perlis, Ctr Excellence Geopolymer & Green Technol CEGeoGT, Green Design & Manufacture Res Grp, Kangar 01000, Perlis, Malaysia

来源：

5TH INTERNATIONAL CONFERENCE ON GREEN DESIGN AND MANUFACTURE 2019 (ICONGDM 2019) | 2019年 / 2129卷

关键词：

SYSTEM;

D O I：

10.1063/1.5118203

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Injection moulding process is a quite popular process in current industries to produce and replicate a various shape of plastic parts. However, the process involved a lot of processing parameters which is importance to control in order to minimise defect such as warpage. Nowadays, there are a lot of optimisation approaches that can be employed to obtain the suitable processing parameters setting to overcome this kind of defects. In this study, an artificial intelligent optimisation method which is Genetic Algorithm (GA) approach has been carried out to minimise warpage condition. The battery cover was tested with the selected processing parameters of packing time, cooling time, melting temperature, and mould temperature. Based on the Autodesk Mouldflow Insight (AMI) simulation results warpage value is 1.038 mm and GA approach demonstrated a warpage reduction and the results were 0.7005 mm. Thus, by utilising GA in minimising warpage on the moulded part can be applied in injection moulding sector.

引用

页数：9

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