Optimised Tool Life by Partial Swarm Optimisation
The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and find the optimisation values with partial swarm optimisation (PSO), using coated carbide cutting tool. By using Response Surface Method (RSM), first and second order models we...
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| Pengarang-pengarang Utama: | , , , |
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| Format: | Artikel |
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2010
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| Subjek-subjek: | |
| Capaian Atas Talian: | http://www.springerlink.com/content/8727173k5373161p/ http://www.springerlink.com/content/8727173k5373161p/ http://umpir.ump.edu.my/2233/1/Optimised_Tool_Life_By_Partial_Swarm_Optimisation.pdf |
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| Ringkasan: | The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and find the optimisation values with partial swarm optimisation (PSO), using coated carbide cutting tool. By using Response Surface Method (RSM), first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, axial depth and radial depth, using RSM. It was found that the feedrate, cutting speed, axial depth and radial depth played a major role. Tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions obtained from PSO are: cutting speed of 100 m/s, federate of 0.1 mm/tooth, axial depth of 1.9596 mm and radial depth of 2 mm. Using these parameters, a tool life of 40.52 min was obtained. |
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