Using regression models for predicting the product quality in a tubing extrusion process

  • Vicente García
  • J. Salvador Sánchez
  • Luis Alberto Rodríguez-Picón
  • Luis Carlos Méndez-González
  • Humberto de Jesús Ochoa-Domínguez
Article
  • 30 Downloads

Abstract

Quality in a manufacturing process implies that the performance characteristics of the product and the process itself are designed to meet specific objectives. Thus, accurate quality prediction plays a principal role in delivering high-quality products to further enhance competitiveness. In tubing extrusion, measuring of the inner and outer diameters is typically performed either manually or with ultrasonic or laser scanners. This paper shows how regression models can result useful to estimate both those physical quality indices in a tube extrusion process. A real-life data set obtained from a Mexican extrusion manufacturing company is used for the empirical analysis. Experimental results demonstrate that k nearest-neighbor and support vector regression methods (with a linear kernel and with a radial basis function) are especially suitable for predicting the inner and outer diameters of an extruded tube based on the evaluation of 15 extrusion and pulling process parameters.

Keywords

Regression models Extrusion process Product quality prediction Support vector regression K nearest-neighbor 

Notes

Acknowledgements

The authors would like to acknowledge the financial support from the Spanish Ministry of Economy, Industry and Competitiveness [TIN2013-46522-P], and the Generalitat Valenciana [PROMETEOII/2014/062].

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.División Multidisciplinaria en Ciudad Universitaria, Departamento de Ingeniería Eléctrica y ComputaciónUniversidad Autónoma de Ciudad JuárezCiudad JuárezMexico
  2. 2.Institute of New Imaging TechnologiesUniversitat Jaume ICastelló de la PlanaSpain
  3. 3.Departamento de Ingeniería Industrial y ManufacturaUniversidad Autónoma de Ciudad JuárezCiudad JuárezMexico
  4. 4.Departamento de Ingeniería Eléctrica y ComputaciónUniversidad Autónoma de Ciudad JuárezCiudad JuárezMexico

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