Development of energy consumption model of abrasive machining process by a combined evolutionary computing approach

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@Article{Vijayaraghavan:2015:Measurement,

• author = "R. Vijayaraghavan and A. Garg and V. Vijayaraghavan and Liang Gao",
• title = "Development of energy consumption model of abrasive machining process by a combined evolutionary computing approach",
• journal = "Measurement",
• volume = "75",
• pages = "171--179",
• year = "2015",
• ISSN = "0263-2241",
• DOI = "doi:10.1016/j.measurement.2015.07.055",
• URL = "http://www.sciencedirect.com/science/article/pii/S0263224115004066",
• abstract = "Abrasive machining is employed for improving surface characteristics of components used in oil and gas applications. Optimization of power consumed in abrasive machining process is vital from environmental standpoint that requires the formulation of the generalized and an explicit mathematical model. In the present work, we propose to study the power consumption in abrasive machining process using a combined evolutionary computing approach based on Multi-Adaptive Regression Splines (MARS) and Genetic Programming (GP) techniques. Sensitivity and parametric analysis have also been conducted to capture the dynamics of process by unveiling dominant input variables and hidden non-linear relationships. It is concluded that selection of optimal machining time and abrasive is necessary for achieving better environmental performance of abrasive machining process.",
• keywords = "genetic algorithms, genetic programming, Abrasive machining, MARS, Energy consumption, Modelling",

}

Genetic Programming entries for R Vijayaraghavan Akhil Garg Venkatesh Vijayaraghavan Liang Gao

Citations