A Soft Computing System to Perform Face Milling Operations

  • Raquel Redondo
  • Pedro Santos
  • Andres Bustillo
  • Javier Sedano
  • José Ramón Villar
  • Maritza Correa
  • José Ramón Alique
  • Emilio Corchado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5518)


In this paper we present a soft computing system developed to optimize the face milling operation under High Speed conditions in the manufacture of steel components like molds with deep cavities. This applied research presents a multidisciplinary study based on the application of neural projection models in conjunction with identification systems, in order to find the optimal operating conditions in this industrial issue. Sensors on a milling centre capture the data used in this industrial case study defined under the frame of a machine-tool that manufactures industrial tools. The presented model is based on a two-phase application. The first phase uses a neural projection model capable of determine if the data collected is informative enough. The second phase is focus on identifying a model for the face milling process based on low-order models such as Black Box ones. The whole system is capable of approximating the optimal form of the model. Finally, it is shown that the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples, is the most appropriate model to control such industrial task for the case of steel tools.


Spindle Speed High Speed Machine Deep Cavity Face Milling Final Prediction Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Raquel Redondo
    • 1
  • Pedro Santos
    • 1
  • Andres Bustillo
    • 1
  • Javier Sedano
    • 2
  • José Ramón Villar
    • 3
  • Maritza Correa
    • 4
  • José Ramón Alique
    • 4
  • Emilio Corchado
    • 1
  1. 1.Department of Civil EngineeringUniversity of BurgosBurgosSpain
  2. 2.Department of Electromechanical EngineeringUniversity of BurgosBurgosSpain
  3. 3.Department of Computer ScienceUniversity of OviedoOviedoSpain
  4. 4.Department of Industrial InformaticInstituto de Automática Industrial, Spanish National Research CouncilMadridSpain

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