| Title: | A Hybrid analytical-neural network approach to the determination of optimal cutting conditions |
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| Authors: | ID Župerl, Uroš (Author)
ID Čuš, Franc (Author)
ID Muršec, Bogomir (Author)
ID Ploj, Anton (Author) |
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| Files: |  http://dx.doi.org/10.1016/j.jmatprotec.2004.09.019
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| Language: | English |
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| Work type: | Unknown |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | In the contribution, a new hybrid optimization technique for complex optimization of cutting parameters is proposed. The developed approach is based on the maximum production rate criterion and incorporates 10 technological constrains. It describes the multi-objective techniqueof optimization of cutting conditions by means of the artificial neural network (ANN) and OPTIS routine by taking into consideration the technological, economic and organization limitations. The analytical module OPTIS selects theoptimum cutting conditions from commercial databases with respect to minimum machining costs. By selection of optimum cutting conditions, it is possible to reach a favourable ratio between the low machining costs and high productivity taking into account the given limitation of the cutting process. To reach higher precision of the predicet results, a hybrid optimization algorithm is developed and presented to ensure sample, fast and efficient optimization of all important turning parameters. _ |
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| Keywords: | optimization, cutting conditions, turning, analytical-neural routine, database |
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| Year of publishing: | 2004 |
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| PID: | 20.500.12556/DKUM-27481  |
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| UDC: | 621.9:004 |
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| ISSN on article: | 0924-0136 |
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| COBISS.SI-ID: | 2170924 |
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| NUK URN: | URN:SI:UM:DK:75Q7DLVX |
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| Publication date in DKUM: | 01.06.2012 |
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| Views: | 2474 |
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| Downloads: | 94 |
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| Metadata: |    |
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| Categories: | Misc.
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