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Title: INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS

Abstract

Manufacturing cost of resin transfer molded composite parts is significantly influenced by the cycle time, which is strongly related to the time for both filling and curing of the resin in the mold. The time for filling can be optimized by various injection strategies, and by suitably reducing the length of the resin flow distance during the injection. The curing time can be reduced by the usage of faster curing resins, but it requires a high pressure injection equipment, which is capital intensive. Predictive manufacturing simulation tools that are being developed recently for composite materials are able to provide various scenarios of processing conditions virtually well in advance of manufacturing the parts. In the present study, we integrate the cost models with process simulation tools to study the influence of various parameters such as injection strategies, injection pressure, compression control to minimize high pressure injection, resin curing rate, and demold time on the manufacturing cost as affected by the annual part volume. A representative automotive component was selected for the study and the results are presented in this paper

Authors:
 [1];  [1]; ORCiD logo [1];  [1];  [2];  [3]
  1. General Motors
  2. ESI, Group.
  3. ESI Group
Publication Date:
Research Org.:
General Motors
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1430237
Report Number(s):
DOE-GM-CarbonFiber-ICME
DOE Contract Number:
EE0006826
Resource Type:
Conference
Resource Relation:
Conference: SPE Automotive Composites Conference & Exhibition (ACCE), Detroit
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; cost models, composites, high-pressure resin transfer molding

Citation Formats

Pack, Seongchan, Wilson, Daniel, Aitharaju, Venkat, Kia, Hamid, Yu, Hang, and Doroudian, Mark. INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS. United States: N. p., 2017. Web.
Pack, Seongchan, Wilson, Daniel, Aitharaju, Venkat, Kia, Hamid, Yu, Hang, & Doroudian, Mark. INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS. United States.
Pack, Seongchan, Wilson, Daniel, Aitharaju, Venkat, Kia, Hamid, Yu, Hang, and Doroudian, Mark. Tue . "INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS". United States. doi:. https://www.osti.gov/servlets/purl/1430237.
@article{osti_1430237,
title = {INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS},
author = {Pack, Seongchan and Wilson, Daniel and Aitharaju, Venkat and Kia, Hamid and Yu, Hang and Doroudian, Mark},
abstractNote = {Manufacturing cost of resin transfer molded composite parts is significantly influenced by the cycle time, which is strongly related to the time for both filling and curing of the resin in the mold. The time for filling can be optimized by various injection strategies, and by suitably reducing the length of the resin flow distance during the injection. The curing time can be reduced by the usage of faster curing resins, but it requires a high pressure injection equipment, which is capital intensive. Predictive manufacturing simulation tools that are being developed recently for composite materials are able to provide various scenarios of processing conditions virtually well in advance of manufacturing the parts. In the present study, we integrate the cost models with process simulation tools to study the influence of various parameters such as injection strategies, injection pressure, compression control to minimize high pressure injection, resin curing rate, and demold time on the manufacturing cost as affected by the annual part volume. A representative automotive component was selected for the study and the results are presented in this paper},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Sep 05 00:00:00 EDT 2017},
month = {Tue Sep 05 00:00:00 EDT 2017}
}

Conference:
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