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A Comparison of Neural Network and DOE Regression Analysis for Predicting Resource Consumption of Manufacturing Processes

  • Frank Kübler
  • Rolf Steinhilper
Chapter
Part of the EcoProduction book series (ECOPROD)

Abstract

Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies these models need to be extended to predict resource consumption of manufacturing processes. This chapter describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords

Resource efficiency Artificial neural network Design of experiments 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Fraunhofer-Project Group Process Innovation, Chair for Manufacturing and Remanufacturing TechnologyUniversity of BayreuthBayreuthGermany

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