Call for Papers:Vol.12 Issue.2

Submission
Last date		 28-Apr-2026
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-12,Issue-2. 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
Design And Analysis Of An Electric Go-Kart Considering AerodynamicsMechanical EngineeringRitesh Sharad Kadu Download
Design and Fabrication Of Carbon Collector From Atmosphere Using Cyclone SeperatorMechanical Engineering Badve Kunal Krushnaji Download
Design and Analysis of 3d Printer Using Reinforced Natural Fiber FilamentMechanical EngineeringGunjal Pavan Kailas Download
Influence of Profile Modification on the Reduction of Root Fillet Stress in Spur Gear by Alternative Root Fillet Profile by using Finite Element MethodMechanical EngineeringMs. Jayshri Murkute Download
Thermal Buckling Analysis of Cross-Ply and Angle-Ply Laminated Composite Beam using Finite Element MethodMechanical EngineeringMs. Payal S. Shelke Download
Kevlar-Basalt Hybrid Nanocomposites Reinforced with Multi-Scale Nanoparticles: Mechanical and Thermal CharacterizationHYBRID POLYMERSSiva Prasad Mattaparthi Download
Design Solar Module For A Measurement Of different parameters Different Inclination Angles.Mechanical EngineeringSumit Shivaji Narsale Download
ONION VENTILATION MACHINEDiploma In Mechanical Engineering Bhushan Deshmukh Download
Multipurpose Agriculture ProcessDiploma Mechanical Engineering Yogesh halde Download
Digitalization of Welding Safety Equipment for Workers SafetyDiploma Mechanical Engineering Shilpa Boraste Download
Heat Transfer Enhancement of Solar Air Heaters Using Artificial RoughnessMechanicalRagini Arjariya Download
PERFORMANCE AND EMISSION CHARACTRISTICS OF JATROPHA BIODIESEL BLENDS IN DIESEL ENGINES: A NUMARICAL SIMULATION STUDYMechanical EngineeringMusaab O. El-Faroug Download
Role of AI in Optimization of MIG Welding ParametersMechanical EngineeringProf. Saurabh Gandhe Download
Thermal Energy Storage: A clean, sustainable, and environmentally friendly way of harnessing Solar energyMechanicalNeeraj Shukla Download
Waste Agricultural Biomass as a Renewable and Sustainable Source of EnergyMechanicalSonali Shukla Download
12