Robot selection using a fuzzy regression-based decision-making approach

KARSAK E. E., ŞENER Z., DURSUN M.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, vol.50, no.23, pp.6826-6834, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 50 Issue: 23
  • Publication Date: 2012
  • Doi Number: 10.1080/00207543.2011.627886
  • Journal Name: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.6826-6834
  • Keywords: decision support systems, advanced manufacturing technology, robot selection, fuzzy regression, DATA ENVELOPMENT ANALYSIS, LINEAR-REGRESSION, MODELS, MCDM
  • Galatasaray University Affiliated: Yes

Abstract

Industrial robots, which enable manufacturing firms to produce high-quality products in a cost-effective manner, are important components of advanced manufacturing technologies. The performance of industrial robots is determined by multiple and conflicting criteria that have to be simultaneously considered in a robust selection study. In this study, a decision model based on fuzzy linear regression is presented for industrial robot selection. Fuzzy linear regression provides an alternative approach to statistical regression for modelling situations where the relationships are vague or the data set cannot satisfy the assumptions of statistical regression. The results obtained by employing fuzzy linear regression are compared with those of earlier studies applying different analytical methods to a previously reported robot selection problem.