Issue |
MATEC Web Conf.
Volume 95, 2017
2016 the 3rd International Conference on Mechatronics and Mechanical Engineering (ICMME 2016)
|
|
---|---|---|
Article Number | 02008 | |
Number of page(s) | 4 | |
Section | Material Structure and Measurement | |
DOI | https://doi.org/10.1051/matecconf/20179502008 | |
Published online | 09 February 2017 |
A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test
Department of Mechanical Engineering, Faculty of Engineering, Mahidol University, Salaya, Nakorn Pathom, 73170, Thailand
Laboratory of Computer Mechanics for Design (LCMD), Department of Mechanical Engineering, Faculty of Engineering, Mahidol University, Salaya, Nakorn Pathom, 73170, Thailand
Design of plastic bottles had preferred to use computer aided design (CAD) to propose desirable shapes. The strength also was regarded to pass the top load test unless an appearance of plastic bottles. Finite element method (FEM) was employed to analyze and predict the bottle shape which enough to support load under a collapsible regulation. Unfortunately, the redesign of bottle shape always performed when the desirable bottle shape had not passed the test. There was time consumption and loss of opportunity to compete producing of bottles. This research proposed a method to receive a desirable shape of plastic bottles together with top load strength. The master of bottle shape had been created which capable to change any dimensions before generated CAD and performed top load analysis with FEM. The artificial neural network (ANN) was employed to obtain the desirable bottle shape with top load resistance by varying dimension of the master bottle. The plastic bottle design would be performed rapidly with the ANN of master bottle shape. Consequently, the suitable dimension of plastic bottles which achieved by ANN could be used to design a desirable shape of bottles by using CAD and FEM without trial and error.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.