Call for Papers:Vol.11 Issue.3

Submission
Last date		 28-Jun-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-3. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique
PaperId: :  7885
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 4 Issue 2 2018
DUI:    16.0415/IJARIIE-7885
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Navin KumarSSITM Bhilai
Mayur ThombreSSITM Bhilai

Abstract

Mechanical Engineering
Moulding Process, Shrinkage, Artificial Neural Network, Genetic Algorithm.
Injection molding is an important polymer processing operation in the plastic industry. In this process, polymer is injected into a mold cavity, and solidifies to the shape of the mold. Optimizing the parameters of the injection molding process is critical to enhance productivity. Productivity and quality are two important aspects have become great concerns in today’s competitive global market. Every production/manufacturing unit mainly focuses on these areas in relation to the process as well as product developed. Injection moulding process, even now it is an experience process, wherein still the selected parameters are often far from the maximum, and at the same time selecting optimization parameters is costly and time consuming. In this work the sink mark or shrinkage during the process has been considered as productivity estimate with the aim to minimize it. This response requirements have been satisfied by selecting an optimal process environment (optimal parameter setting). The setting data and objective function is obtained by artificial neural network and regression analysis. Then objective function is optimized using Genetic Algorithm technique. The model is shown to be effective percentage shrinkage mark improved using optimized injection moulding process parameters as compared to previous literature.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Navin Kumar, and Mayur Thombre. "Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique" International Journal Of Advance Research And Innovative Ideas In Education Volume 4 Issue 2 2018 Page 1998-2001
MLA Navin Kumar, and Mayur Thombre. "Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique." International Journal Of Advance Research And Innovative Ideas In Education 4.2(2018) : 1998-2001.
APA Navin Kumar, & Mayur Thombre. (2018). Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique. International Journal Of Advance Research And Innovative Ideas In Education, 4(2), 1998-2001.
Chicago Navin Kumar, and Mayur Thombre. "Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique." International Journal Of Advance Research And Innovative Ideas In Education 4, no. 2 (2018) : 1998-2001.
Oxford Navin Kumar, and Mayur Thombre. 'Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique', International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 2, 2018, p. 1998-2001. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/Optimization_of_Injection_Moulding_Process_Parameters_for_Reducing_Shrinkage_by_Using_Genetic_Algorithm_Technique_ijariie7885.pdf (Accessed : ).
Harvard Navin Kumar, and Mayur Thombre. (2018) 'Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique', International Journal Of Advance Research And Innovative Ideas In Education, 4(2), pp. 1998-2001IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/Optimization_of_Injection_Moulding_Process_Parameters_for_Reducing_Shrinkage_by_Using_Genetic_Algorithm_Technique_ijariie7885.pdf (Accessed : )
IEEE Navin Kumar, and Mayur Thombre, "Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique," International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 2, pp. 1998-2001, Mar-App 2018. [Online]. Available: http://ijariie.com/AdminUploadPdf/Optimization_of_Injection_Moulding_Process_Parameters_for_Reducing_Shrinkage_by_Using_Genetic_Algorithm_Technique_ijariie7885.pdf [Accessed : ].
Turabian Navin Kumar, and Mayur Thombre. "Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 4 number 2 ().
Vancouver Navin Kumar, and Mayur Thombre. Optimization of Injection Moulding Process Parameters for Reducing Shrinkage by Using Genetic Algorithm Technique. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2018 [Cited : ]; 4(2) : 1998-2001. Available from: http://ijariie.com/AdminUploadPdf/Optimization_of_Injection_Moulding_Process_Parameters_for_Reducing_Shrinkage_by_Using_Genetic_Algorithm_Technique_ijariie7885.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
PARAMETRIC INVESTIGATION STUDIES OF WELDS MADE BY HYBRID FRICTION WELDING PROCESS FOR HARD STEEL ALLOYSMECHANICAL ENGINEERINGDARSHAN R. MISKIN Download
Evaluation of wear properties of Al 7075 alloy reinforced with herbal extracted SiCMechanical EngineeringSrinivasa rao G Download
FRICTION SURFACING OF AA5083 ON AA7075: INFLUENCE OF PROCESS PARAMETERS ON MECHANICAL PROPERTIESsajjar99@gmail.comYANAMALA NAVEEN KUMAR Download
Performance Analysis Of Ceramic Composite For Bearing ApplicationMechanical EngineeringMr. P. J. Waditke Download
Urban Heat Island Mitigation Using Advanced Reflective Pavement CoatingsM.Tech.Radha Download
Design And Development of Battery Thermal Management System for Electric Vehicle ApplicationMechanical EngineeringSagar Bhandare Download
Analysis of Thermal Enhancement on Spiral Radiator with Different Fin ShapeMechanical EngineeringPintu Kumar Download
Performance and emission analysis of waste cooking oils blended with diethyl ether for variable compression ratioMechanical Chetan B.Satkar Download
Design, Fabrication and Experimental Analysis on Horizontal Axis Rose Profile Wind Turbine.MechanicalDr.P.D.Kabudke Download
A Comprehensive Review of Hydrogen Fuel Cell Technology: Developments, Applications, and Future ProspectsMECHANICAL ENGINEERINGMr. AMOL DILIPRAO PATIL Download
To design and develop pedal operated turnstile power generation systemMechanical EngineeringNagare Abhijit Ramkrushna Download
Development of a biomass digester for domestic useRenewable energy systemsObadiegwu Bright Nnebuike Download
Investigation of Metal inert Gas welding process through different parameter for Chromium Nickel Stainless Steel and Hot Rolled Medium and High Tensile Structural SteelEngineeringMr. Vikrant Khandare Download
Review on Design and development of air cooler with integrated air conditioningMechanical Engineering Rahul Bhosale Download
REVIEW ON CIRCULAR PIN FINS IN FORCED CONVECTIONMechanical EngineeringSalunke Sopan Download
12