Optimizing performance of rigid polyurethane foam using FGP models

Abbas Al-Refaie*, Raghed Aldwairi, Tin-Chih Chen

*Corresponding author for this work

Research output: Contribution to journalArticle

6 Scopus citations


This research proposes and implements fuzzy goal programming (FGP) models to optimize the performance of rigid polyurethane foam (RPF) for four quality characteristics. At initial process factor settings, the RPF process was found incapable for density, shrinkage ratio, and expanding ratio. However, it was found highly capable for compressive strength at 10% deformation. As a result, costly nonconforming products were produced and delivered. For this reason, fuzzy goal programming models were proposed and implemented to determine the combination of optimal factors settings followed by confirmation experiments. The results showed that: (1) for density the capability index is enhanced from −1.72 to (0.66, 0.62, and 0.85) at lower, middle and upper optimal factor setting levels, respectively, (2) for compressive stress at 10% deformation, the capability index is improved from 5.32, to (6.98, 5.45, and 6.02), (3) for shrinkage ratio the process capability is highly capable; C^ p u becomes (4.56, 4.62, and 5.91), and (4) for expanding ratio the capability index becomes highly capable; C^ p u, equals to (6.37, 6.30, and 6.88). Such improvements in process capability result in significant savings in quality, maintenance, and production costs. In conclusions, implementing fuzzy goal programming model is found an efficient technique to optimal RPF performance for four quality responses.

Original languageEnglish
Pages (from-to)351-366
Number of pages16
JournalJournal of Ambient Intelligence and Humanized Computing
Issue number2
StatePublished - 1 Apr 2018


  • Fuzzy goal programming
  • Optimization
  • Process capability
  • Rigid polyurethane foam

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