Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach / Muhammad Safwan Azmi

By: Material type: TextTextPublication details: Kuantan, Pahang : UMP, 2012Description: xvi, 54 p. : ill. ; 30 cm. + 1 CD-ROMISBN:
  • THE0006648(Local)
Subject(s): Dissertation note: Project paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang – 2012 Abstract: This project was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this project is to study the effect of nanocoolant on precision surface grinding, to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial neural network technique. The abrasive machining process selected was surface grinding and it was carried out two different coolants which are conventional coolant and titanium dioxide nanocoolant. The selected inputs variables are table speed, depth of cut and type of grinding pattern which are single pass and multiple pass. The selected output parameters are temperature rise, surface roughness and material removal rate. The ANOVA test has been carried out to check the adequacy of the developed mathematical model. The second order mathematical model for MRR, surface roughness and temperature rise are developed based on response surface method. The artificial neural network model has been developed and analysis the performance parameters of grinding processes using two different types of coolant including the conventional as well as TiO2nanocoolant. The obtained results shows that nanofluids as grinding coolants produces the better surface finish, good value of material removal rate and acts effectively on minimizing grinding temperature. The developed ANN model can be used as a basis of grinding processes.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Copy number Status Date due Barcode
Final Year Report Final Year Report UMPLIB PEKAN TJ1280 .S34 2012 rs Bc. (Browse shelf(Opens below)) 1 Not for loan 0000076055
Final Year Report Final Year Report UMPLIB PEKAN CD 7289 | TJ1280 .S34 2012 rs Bc. (Browse shelf(Opens below)) 1 Not for loan 0000076056

Project paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang – 2012

Bibliography : p. 53-54

This project was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this project is to study the effect of nanocoolant on precision surface grinding, to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial neural network technique. The abrasive machining process selected was surface grinding and it was carried out two different coolants which are conventional coolant and titanium dioxide nanocoolant. The selected inputs variables are table speed, depth of cut and type of grinding pattern which are single pass and multiple pass. The selected output parameters are temperature rise, surface roughness and material removal rate. The ANOVA test has been carried out to check the adequacy of the developed mathematical model. The second order mathematical model for MRR, surface roughness and temperature rise are developed based on response surface method. The artificial neural network model has been developed and analysis the performance parameters of grinding processes using two different types of coolant including the conventional as well as TiO2nanocoolant. The obtained results shows that nanofluids as grinding coolants produces the better surface finish, good value of material removal rate and acts effectively on minimizing grinding temperature. The developed ANN model can be used as a basis of grinding processes.

Perpustakaan Universiti Malaysia Pahang Al-Sultan Abdullah
26600 Pekan, Pahang Darul Makmur
Phone: +609 431 5063 (Gambang) / +609 431 5035 (Pekan)
Email: umplibrary@umpsa.edu.my

Connect With Us