A TOPSIS-based Taguchi optimization to determine optimal mixture proportions of the high strength self-compacting concrete

Simsek B., İÇ Y. T., ŞİMŞEK E. H.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, cilt.125, ss.18-32, 2013 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 125
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1016/j.chemolab.2013.03.012
  • Dergi Adı: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.18-32
  • Anahtar Kelimeler: High strength self-compacting concrete (HSSCC), Multi-response optimization, TOPSIS, Taguchi method, RESPONSE-SURFACE METHODOLOGY, MECHANICAL-PROPERTIES, DECISION-MAKING, HEAT-TRANSFER, SILICA FUME, FLY-ASH, FIBER, PARAMETERS, DESIGN
  • Ankara Üniversitesi Adresli: Evet

Özet

In general, the optimization problems contain more than one response, which often conflict with each other. This paper proposes the TOPSIS-based Taguchi optimization approach to determine the optimal mixture proportions of the high strength self-compacting concrete (HSSCC) in a ready-mixed concrete plant The performance criteria are identified for the following: the average convective heat transfer coefficient, the percentage of air content, the slump flow, the T-50 time, the water absorption, the compressive strength, the splitting tensile strength, and the production cost. Five factors having three control levels and one factor having two control levels affect these identified performance criteria. The data of the HSSCC quality criteria are obtained by running scenarios that combine factor levels in Taguchi design, while signal to noise (S/N) ratios are calculated for the data. After a decision matrix is generated by the S/N ratios, the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method is then used to transform the multi-response problem into a single-response problem. The anticipated improvement rate is also determined by finding the levels of the factors in order to optimize the system which uses Taguchi's single response optimization methodology. (c) 2013 Elsevier B.V. All rights reserved.