Multi Objective Optimization of machining parameters for Hard Turning OHNS/AISI H13 material, Using Genetic Algorithm
| Autor: | N. Sathiya Narayanan, N. Baskar, M. Ganesan |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Design–Expert business.industry Machinability Mechanical engineering 02 engineering and technology Thread (computing) Multi-objective optimization 020303 mechanical engineering & transports 020901 industrial engineering & automation Software 0203 mechanical engineering Machining Surface roughness Orthogonal array business Mathematics |
| Zdroj: | Materials Today: Proceedings. 5:6897-6905 |
| ISSN: | 2214-7853 |
| DOI: | 10.1016/j.matpr.2017.11.351 |
| Popis: | Oil Hardened Non-Shrinking Die Steel (OHNS/AISI H13) are employed in the production of callipers, plug gauges, thread gauge, punches and milling cutters for its hardness and good machinability performance. This experimental works focused on maximizing metal removal rate (MRR) and minimizing surface roughness (Ra) by choosing the optimal turning parameters. L27 Orthogonal array based experiments were conducted in CNC Supertech 6.2 turning centre using carbide insert CNMG 120408. The individual and interaction effects of cutting speed (v), feed rate (f) and depth of cut (ap) on MRR and Ra is analyzed in Design Expert 9.0 Software. Empirical models are framed which reveals the relationship between the turning parameters and output responses. Non-Traditional optimization technique genetic algorithm is used with multi objective function to find the optimum parameters in turning AISI H13 steel materials. Confirmation experiments are performed to validate the optimum results of genetic algorithm and it is within the acceptance limit. |
| Databáze: | OpenAIRE |
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