Genetic equation for the prediction of tool-chip contact length in orthogonal cutting

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@Article{Zadshakoyan:2013:EAAI,

• author = "M. Zadshakoyan and V. Pourmostaghimi",
• title = "Genetic equation for the prediction of tool-chip contact length in orthogonal cutting",
• journal = "Engineering Applications of Artificial Intelligence",
• volume = "26",
• number = "7",
• pages = "1725--1730",
• year = "2013",
• month = aug,
• keywords = "genetic algorithms, genetic programming, Cutting parameters, Machining, Tool-chip contact length",
• ISSN = "0952-1976",
• DOI = "doi:10.1016/j.engappai.2012.10.016",
• URL = "http://www.sciencedirect.com/science/article/pii/S0952197612002850",
• abstract = "In metal cutting, it has been acknowledged that the tool-chip contact length significantly affects many aspects of machining such as chip formation, cutting forces, cutting temperatures, tool wear and tool life. Important decrease in the tool-chip contact length, decreases the thickness of the secondary shear zone, which leads to a decrease of the cutting temperature and cutting force. As a result, it has a great effect on finish surface and tool life. Several ways have been proposed in different works to find its value, which have given discordant results for the same set of cutting conditions. In this paper, the genetic equation for the tool-chip contact length is developed with the use of the experimentally measured contact length values and genetic programming. The suggested equation has shown to correspond well with experimental data in various machining conditions with associated cutting parameters and this model predicts tool-chip contact length better than other known solutions.",

}

Genetic Programming entries for Mohammad Zadshakoyan Vahid Pourmostaghimi

Citations