A new approach for predicting and collaborative evaluating the cutting force in face milling based on gene expression programming

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@Article{Yang:2013:JNCA,
  author =       "Yang Yang and Xinyu Li and Liang Gao and Xinyu Shao",
  title =        "A new approach for predicting and collaborative
                 evaluating the cutting force in face milling based on
                 gene expression programming",
  journal =      "Journal of Network and Computer Applications",
  year =         "2013",
  volume =       "36",
  number =       "6",
  pages =        "1540--1550",
  keywords =     "genetic algorithms, genetic programming, Cutting force
                 modelling, Gene expression programming, Face milling,
                 Collaborative model evaluation",
  ISSN =         "1084-8045",
  DOI =          "doi:10.1016/j.jnca.2013.02.004",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1084804513000428",
  size =         "11 pages",
  abstract =     "Cutting force is one of the fundamental elements that
                 can provide valuable insight in the investigation of
                 cutter breakage, tool wear, machine tool chatter, and
                 surface finish in face milling. Analysing the
                 relationship between process factors and cutting force
                 is helpful to set the process parameters of the future
                 cutting operation and further improve production
                 quality and efficiency. Since cutting force is impacted
                 by the inherent uncertainties in the machining process,
                 how to predict the cutting force presents a significant
                 challenge. In the meantime, face milling is a complex
                 process involving multiple experts with different
                 domain knowledge, collaborative evaluation of the
                 cutting force model should be conducted to effectively
                 evaluate the constructed predictive model. 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. In this paper, a new
                 approach to predict the face milling cutting force
                 based on GEP is proposed. At the basis of defining a
                 GEP environment for the cutting force prediction, an
                 explicit predictive model has been constructed. To
                 verify the effectiveness of the proposed approach, a
                 case study has been conducted. The comparisons between
                 the proposed approach and some previous works show that
                 the constructed model fits very well with the
                 experimental data and can predict the cutting force
                 with a high accuracy. Moreover, in order to better
                 apply the constructed predictive models in actual face
                 milling process, a collaborative model evaluation
                 method is proposed to provide a distributed environment
                 for geographical distributed experts to evaluate the
                 constructed predictive model collaboratively, and four
                 kinds of collaboration mode are discussed.",
}

Genetic Programming entries for Yang Yang Xinyu Li Liang Gao Xinyu Shao

Citations