Golshan, Abolfazl and Ghodsiyeh, Danial and Gohari, Soheil and Ayob, Amran and Baharudin, B. T. Hang Tuah (2013) Computational inteligence in optimization of machining operation parameters of st-37 steel. In: 2012 International Conference on Mechanical Materials and Manufacturing Engineering, ICMMME 2012, 5 October 2012 through 6 October 2012, Dalian; China.
Full text not available from this repository.
Official URL: https://www.researchgate.net/publication/256294910...
Abstract
Optimal selection of cutting parameters is one of the significant issues in achieving high quality machining. In this study, a method for the selection of optimal cutting parameters during lathe operation is presented. The present study focuses on multiple-performance optimization on machining characteristics of St-37 steel. The cutting parameters used in this experimental study include cutting speed, feed rate, depth of cut and rake angle. Two output parameters, namely, surface roughness and tool life are considered as process performance. A statistical model based on linear polynomial equations is developed to describe different responses. For optimal conditions, the Non-dominated Sorting Genetic Algorithm (NSGA) is employed in achieving appropriate models. The optimization procedure shows that the proposed method has a high performance in problem-solving.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | optimization, surface roughness, tool life, statistical model, non-dominated,sorting genetic algorithm |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Mechanical Engineering |
| ID Code: | 50955 |
| Deposited By: | Haliza Zainal |
| Deposited On: | 27 Jan 2016 01:53 |
| Last Modified: | 26 Sep 2017 01:30 |
Repository Staff Only: item control page
