Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/225873
Title: Optimal solution of parameters for machining of INCONEL 718
Researcher: Shrivastava, Prashant Kumar
Guide(s): Singh, Bhagat,Norkey Gavendra and Pandey Arun Kumar
Keywords: Artificial Neural Network
Engineering and Technology,Engineering,Engineering Mechanical
Laser Cutting
Unconventional Materials
University: Jaypee University of Engineering and Technology, Guna
Completed Date: 27/12/2018
Abstract: It is a desirable need to evaluate the machining parameters for effective utilization of a process and the material such as Inconel-718. Selection of an appropriate optimal range of cutting parameters is quite essential to achieve high-quality cut and is a challenging task within this domain of study. The aim of this research is to develop a robust prediction model which can suggest the desired range of cutting parameters for accomplishing better cutting quality, precision and geometrical accuracy. Experiments have been performed on a 300W (CNC-PCT 300) pulsed Nd: YAG laser cutting system at various levels of input cutting parameters viz.: gas pressure, standoff distance, cutting speed and laser power. Thereafter, regression analysis, response surface methodology (RSM) and artificial neural network (ANN) techniques have been adopted to develop mathematical models in terms of aforementioned input cutting parameters for geometrical quality characteristics: Top Kerf Width (TKW), Bottom Kerf Width (BKW) and Kerf Taper (KT). These developed models have been validated by comparing the predicted values with the experimental ones. Further, these models have been optimized using multi-objective genetic algorithm and particle swarm optimization techniques, in order to ascertain the optimal range of cutting parameters pertaining to better quality cut with high precision and geometrical accuracy. newline newline
Pagination: xii,174p.
URI: http://hdl.handle.net/10603/225873
Appears in Departments:Department of Mechanical Engineering

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01_title.pdfAttached File292.21 kBAdobe PDFView/Open
02_certificate.pdf140.85 kBAdobe PDFView/Open
03_declaration.pdf139.88 kBAdobe PDFView/Open
04_acknowledgement.pdf201.41 kBAdobe PDFView/Open
05_abstract.pdf176.14 kBAdobe PDFView/Open
06_table of contents.pdf199 kBAdobe PDFView/Open
07_list of figures.pdf264.27 kBAdobe PDFView/Open
08_list of tables.pdf183.08 kBAdobe PDFView/Open
09_list of abbreviations.pdf254 kBAdobe PDFView/Open
10_list of symbols.pdf246.34 kBAdobe PDFView/Open
11_chapter 1.pdf605.43 kBAdobe PDFView/Open
12_chapter 2.pdf834.11 kBAdobe PDFView/Open
13_chapter 3.pdf1.07 MBAdobe PDFView/Open
14_chapter 4.pdf10.86 MBAdobe PDFView/Open
15_chapter 5.pdf1.23 MBAdobe PDFView/Open
16_chapter 6.pdf1.13 MBAdobe PDFView/Open
17_chapter7.pdf325.15 kBAdobe PDFView/Open
18_conclusions.pdf279.65 kBAdobe PDFView/Open
19_bibliograpgy.pdf571.87 kBAdobe PDFView/Open
20_synopsys.pdf1.04 MBAdobe PDFView/Open
21_list of publications.pdf394.66 kBAdobe PDFView/Open
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