Evaluation of Desirability Function Approach and Genetic Algorithm optimization of drilling characteristics on Duplex 2205
| Autor: | N. Baskar, G. Jayaprakash, M. Varatharajulu, S. Kannan, B. Suresh Kumar, A. Haja Maideen |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
010302 applied physics
Variables media_common.quotation_subject Process (computing) Duplex (telecommunications) Drilling 02 engineering and technology 021001 nanoscience & nanotechnology 01 natural sciences Desirability function Control theory 0103 physical sciences Genetic algorithm Surface roughness Response surface methodology 0210 nano-technology Mathematics media_common |
| Zdroj: | Materials Today: Proceedings. 22:589-600 |
| ISSN: | 2214-7853 |
| DOI: | 10.1016/j.matpr.2019.08.225 |
| Popis: | This work deals with the development of an empirical model using Response Surface Methodology (RSM) for the independent parameters of drilling operation using Duplex 2205 using solid carbide tool in the CNC milling machine. The considered independent variables are spindle speed, feed rate and dependent variables are drilling time, entry burr height, entry burr thickness, exit burr height, exit burr thickness, surface roughness. After successful development of an empirical model, the process parameters are optimized with two different techniques named Desirability Function Approach (DFA) and Genetic Algorithm (GA). The spindle speed and feed rate were optimized as 270 rpm and 0.073 mm/rev. respectively through DFA and 468.85715 rpm and 0.13684 mm/rev., respectively through GA to minimize the responses. Later, the evaluation made between the optimization techniques to achieve the best responses which emphasize the superiority of GA over DFA. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect