Factorial design of experiments for polymer-metal joining

Lucian Attila Blaga, Gonçalo P. Cipriano, Arnaldo R. Gonzalez, Sergio T. Amancio-Filho

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

This chapter presents the basics of design of experiments (DoE) and emphasizes on its utility for the development, deeper understanding, and optimization of metal-polymer joining technologies. Factorial designs are the basis of the most commonly used experimental designs. Recently, DoE and analysis of variance (ANOVA) have been increasingly applied in welding and joining as a tool for weld or joint optimization. The use of a DoE allows cause-effect correlations to be established between the process input factors and the process responses. Although a limited number of DoE and ANOVA studies on similar joints and welds were published, very few studies on metal-polymer joints have been published. The chapter also presents case studies presented that are examples from research works within the Advanced Polymer-Metal Hybrid Structures Group at the Helmholtz-Zentrum Geesthacht, Germany, and its international cooperation projects.

Original languageEnglish
Title of host publicationJoining of Polymer-Metal Hybrid Structures
Subtitle of host publicationPrinciples and Applications
PublisherWiley
Pages337-364
Number of pages28
ISBN (Electronic)9781119429807
ISBN (Print)9781118177631
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Analysis of variance
  • Cause-effect correlations
  • Design of experiments
  • Factorial designs
  • International cooperation projects
  • Metal-polymer joining technologies

ASJC Scopus subject areas

  • Engineering(all)
  • Chemical Engineering(all)

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  • Cite this

    Blaga, L. A., Cipriano, G. P., Gonzalez, A. R., & Amancio-Filho, S. T. (2018). Factorial design of experiments for polymer-metal joining. In Joining of Polymer-Metal Hybrid Structures: Principles and Applications (pp. 337-364). Wiley. https://doi.org/10.1002/9781119429807.ch12