Modeling of cutting forces in a face-milling operation with Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Yang Yang and Xinyu Li and Ping Jiang and Long Wen",
  title =        "Modeling of cutting forces in a face-milling operation
                 with Gene Expression Programming",
  booktitle =    "IEEE 16th International Conference on Computer
                 Supported Cooperative Work in Design (CSCWD 2012)",
  year =         "2012",
  month =        "23-25 " # may,
  pages =        "769--774",
  size =         "6 pages",
  abstract =     "Cutting forces is one of the most fundamental elements
                 that affect the performance of cutting operation.
                 Finding the rules that how process and environment
                 factors affect the values of cutting forces will help
                 to set the process parameters of the future cutting
                 operation and further improve production quality and
                 efficiency. Since cutting forces is impacted by
                 different machining parameters and the inherent
                 uncertainties in the machining process, how to predict
                 the cutting forces becomes a challengeable problem for
                 the researchers and engineers. Gene Expression
                 Programming (GEP) combines the advantages of the
                 genetic algorithm (GA) and genetic programming (GP),
                 and has been successfully applied in function mining
                 and formula finding, so it should be suitable to solve
                 the above problem. In this paper, a method based on GEP
                 has been proposed to construct the prediction model of
                 cutting forces in a face-milling operation. At the
                 basis of defining a GEP environment for the problem and
                 improving the method of constant creation, an explicit
                 prediction model of cutting forces has been
                 constructed. To verify the feasibility and performance
                 of the proposed approach, experimental studies have
                 been conducted to compare this approach with some
                 previous works. The obtained results show that the
                 constructed prediction model fits very well with the
                 experimental data, and can be used to estimate the
                 cutting forces and optimise the cutting parameters. The
                 proposed method will lead to the reduction in
                 production costs and production time, and improvement
                 of product quality.",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, GEP, cutting forces, face
                 milling operation, machining parameters, product
                 quality improvement, production cost reduction,
                 production efficiency improvement, production quality
                 improvement, cost reduction, cutting, milling, product
  DOI =          "doi:10.1109/CSCWD.2012.6221907",
  notes =        "Also known as \cite{6221907}",

Genetic Programming entries for Yang Yang Xinyu Li Ping Jiang Long Wen