کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1179846 1491553 2013 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A TOPSIS-based Taguchi optimization to determine optimal mixture proportions of the high strength self-compacting concrete
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
A TOPSIS-based Taguchi optimization to determine optimal mixture proportions of the high strength self-compacting concrete
چکیده انگلیسی


• A TOPSIS–Taguchi optimization is used to determine mixture optimization of HSSCC.
• In order to convert multi-response problem to a single one, TOPSIS is applied.
• A Taguchi's L18 array is used to reduce testing time and experimental costs.
• The result of TOPSIS–Taguchi approach is also compared with the RSM.

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 T50 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 125, 15 June 2013, Pages 18–32
نویسندگان
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