A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test

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 s...

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Main Authors: Keawjaroen Piyapat, Suvanjumrat Chakrit
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/20179502008
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spelling doaj-7b166b7c6de54912b2327dad013e5b7a2021-04-02T07:14:44ZengEDP SciencesMATEC Web of Conferences2261-236X2017-01-01950200810.1051/matecconf/20179502008matecconf_icmme2017_02008A Master Shape of Bottles for Design under Desirable Geometry and Top Load TestKeawjaroen PiyapatSuvanjumrat ChakritDesign 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.https://doi.org/10.1051/matecconf/20179502008
collection DOAJ
language English
format Article
sources DOAJ
author Keawjaroen Piyapat
Suvanjumrat Chakrit
spellingShingle Keawjaroen Piyapat
Suvanjumrat Chakrit
A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test
MATEC Web of Conferences
author_facet Keawjaroen Piyapat
Suvanjumrat Chakrit
author_sort Keawjaroen Piyapat
title A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test
title_short A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test
title_full A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test
title_fullStr A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test
title_full_unstemmed A Master Shape of Bottles for Design under Desirable Geometry and Top Load Test
title_sort master shape of bottles for design under desirable geometry and top load test
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2017-01-01
description 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.
url https://doi.org/10.1051/matecconf/20179502008
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