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Processing parameters Optimization of Injection Moulding in DN20 Vent of Water Meter Manufacturing

Authors :
Sateesh N.
Reddy S. Devakar
Subbiah Ram
Nagaraju D. Siva
Nookaraju BCh
Source :
E3S Web of Conferences, Vol 184, p 01008 (2020)
Publication Year :
2020
Publisher :
EDP Sciences, 2020.

Abstract

The conventional optimization process in Injection Moulding includes actual shop floor trials in which melt temperature, mould temperature, injection time, injection pressure, pattern, feeder size, shape and location cores, mould layout, gating etc. are changed in each iteration which involves high machining cost, tooling cost, modification cost, melting cost, and transportation cost as well as, materials, energy, time are wasted in each trial until and unless the required results are obtained. Water meter component (DN20 Vent) is designed in CREO 5.0, and then components are 3D printed to cross check the dimensions and also to confirm whether all the other components can be accommodated or not. Then the mould flow analysis will be performed on a water meter components using different materials and changing the processing parameters. The input processing parameters considered are melt temperature, mould temperature and injection time, whereas the responses are warpage, volumetric shrinkage, cycle time and quality prediction. Grey relational analysis is carried out to determine the optimum injection moulding processing parameters.. The effort has been made to minimize the warpage, volumetric shrinkage, cycle time and maximize the quality prediction mould cavity and core for the components are designed in CREO 5.0 and manufactured using P20 tool steel. Then the water meter components are manufactured by inputting the optimal processing parameters in injection moulding machine to achieve high productivity and quality.

Subjects

Subjects :
Environmental sciences
GE1-350

Details

Language :
English, French
ISSN :
22671242
Volume :
184
Database :
Directory of Open Access Journals
Journal :
E3S Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.b49ba7774785437f980434b3ea86a219
Document Type :
article
Full Text :
https://doi.org/10.1051/e3sconf/202018401008