Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/270794
Title: Minimizing the sand casting defects by predicting and analyzing the process parameters
Researcher: Parekh, P.V.
Guide(s): Vadher, J.A.
Keywords: AFS test
ANN
Engineering and Technology,Engineering,Engineering Mechanical
Genetic Algorithm
Green Sand Casting Process
Taguchi method
University: RK University
Completed Date: 20/01/2020
Abstract: quotMinimizing the Sand Casting Defects by Predicting and Analyzing the Process Parameters newlineSubmitted by: Parekh Priyank Vinodray newlinePhD scholar of Mechanical Engineering, newlineSchool of Engineering, R K University newlineSupervised by: Dr. Jeetendra A.Vadher newlineProfessor newlineMechanical Engineering Department, newlineGovernment Engineering College newlinePalanpur newline newlineKeywords: AFS test, Green Sand Casting Process, Taguchi method, Genetic Algorithm, ANN newline newlineBackground: Indian Foundries are facing the problem of scrap castings and more rejection due to some of the major defects like blowholes, porosity, slag inclusions and misrun. This research focuses on the identification of various casting defects, data collection of defects, critical parameters identification and optimization of identified parameters. newline newlineAim: The prime objective of the present work is to minimize the sand casting defects and prediction of defects. This work also focuses on the optimization of controllable critical process parameters using various optimization methods. newline newlineMaterials and Methods: newlineFor optimization of critical controllable process parameters various defects data are collected from the shop floor. Based on defects data Cause and Effect matrix is prepared for both green sand casting process and CO2 casting process. From the Cause and Effect matrix, various controllable factors are identified for both the processes. For green sand casting process critical process parameters are moisture, permeability, loss on ignition, compressive strength, volatile content, vent holes, pouring time, pouring temperature and mould hardness are identified and for CO2 casting process AFS, clay, pouring time, moisture and pouring temperature are identified as critical parameters. Various methods like Taguchi method, Genetic algorithm and simulated annealing are used for finding the optimum values of parameters. For the prediction of defects, ANN is used. For CO2 casting process, most of the rejections are due to sand related problems. Different types of sands like silica sand, chromite sand, Ceracota,
Pagination: -
URI: http://hdl.handle.net/10603/270794
Appears in Departments:Faculty of Technology

Files in This Item:
File Description SizeFormat 
01_cover page.pdfAttached File178.91 kBAdobe PDFView/Open
02_certificate.pdf272.2 kBAdobe PDFView/Open
04_acknowledgement.pdf244.21 kBAdobe PDFView/Open
05_table of contents.pdf281.4 kBAdobe PDFView/Open
06_list of tables.pdf266.25 kBAdobe PDFView/Open
07_list of figures.pdf255.66 kBAdobe PDFView/Open
08_ list of abbreviations.pdf258.63 kBAdobe PDFView/Open
09_abstract.pdf345.44 kBAdobe PDFView/Open
10_graphical abstract.pdf253.47 kBAdobe PDFView/Open
11_chapter 1.pdf596.3 kBAdobe PDFView/Open
12_chapter 2.pdf499.48 kBAdobe PDFView/Open
13_chapter 3.pdf580.44 kBAdobe PDFView/Open
14_chapter 4.pdf1.04 MBAdobe PDFView/Open
15_chapter 5.pdf1.35 MBAdobe PDFView/Open
16_chapter 6.pdf227.26 kBAdobe PDFView/Open
17_list of publications.pdf177.48 kBAdobe PDFView/Open
18_references.pdf213.62 kBAdobe PDFView/Open
19_appendix.pdf7.37 MBAdobe PDFView/Open
3_declaration signed.pdf289.61 kBAdobe PDFView/Open
Show full item record


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: