Development of Concrete Mixture Design Process Using MCDM Approach for Sustainable Concrete Quality Management

The development of a concrete mixture design process for high-quality concrete production with sustainable values is a complex process because of the multiple required properties at the green/hardened state of concrete and the interdependency of concrete mixture parameters. A new multicriteria decision making (MCDM) technique based on Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methodology is applied to a fuzzy setting for the selection of concrete mix factors and concrete mixture design methods with the aim towards sustainable concrete quality management. Three objective properties for sustainable quality concrete are adopted as criteria in the proposed MCDM model. The seven most dominant concrete mixture parameters with consideration to sustainable concrete quality issues, i.e., environmental (density, durability) and socioeconomic criteria (cost, optimum mixture ingredients ratios), are proposed as sub-criteria. Three mixture design techniques that have potentiality to include sustainable aspects in their design procedure, two advanced and one conventional concrete mixture design method, are taken as alternatives in the MCDM model. The proposed selection support framework may be utilized in updating concrete design methods for sustainability and in deciding the most dominant concrete mix factors that can provide sustainable quality management in concrete production as well as in concrete construction. The concrete mix factors found to be most influential to produce sustainable concrete quality include the water/cement ratio and density. The outcomes of the proposed MCDM model of fuzzy TOPSIS are consistent with the published literature and theory. The DOE method was found to be more suitable in sustainable concrete quality management considering its applicable objective quality properties and concrete mix factors.

[1]  D. Dubois,et al.  Recent models of uncertainty and imprecision as a basis for decision theory:towards less normative frameworks , 1986 .

[2]  Edmundas Kazimieras Zavadskas,et al.  Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008-2018 , 2019, Symmetry.

[3]  Osman Taylan,et al.  Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies , 2014, Appl. Soft Comput..

[4]  Milan Zelany,et al.  A concept of compromise solutions and the method of the displaced ideal , 1974, Comput. Oper. Res..

[5]  Mohammad Reza Nikoo,et al.  A novel multi criteria decision making model for optimizing time-cost-quality trade-off problems in construction projects , 2015, Expert Syst. Appl..

[6]  Ehab El-Salakawy,et al.  Full factorial optimization of concrete mix design for hot climates , 2001 .

[7]  Mohd Ahmed,et al.  Siliceous Concrete Materials Management for Sustainability Using Fuzzy-TOPSIS Approach , 2019, Applied Sciences.

[8]  H. M. Alhumaidi,et al.  Construction Contractors Ranking Method Using Multiple Decision-Makers and Multiattribute Fuzzy Weighted Average , 2015 .

[9]  Khader M. Hamdia,et al.  Structural damage assessment criteria for reinforced concrete buildings by using a Fuzzy Analytic Hierarchy process , 2018, Underground Space.

[10]  C. Hwang,et al.  Fuzzy Multiple Attribute Decision Making Methods , 1992 .

[11]  Jurgita Antucheviciene,et al.  Sustainability in Construction Engineering , 2018, Sustainability.

[12]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[13]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[14]  Tanmoy Mukhopadhyay,et al.  A multi-attribute decision making approach of mix design based on experimental soil characterization , 2017, Frontiers of Structural and Civil Engineering.

[15]  Mohd Ahmed,et al.  A Comparative Study of Popular Concrete Mix Design Methods from Qualitative and Cost-Effective Point of View for Extreme Environment , 2016 .

[16]  Javed Mallick,et al.  Decision Support Model for Design of High-Performance Concrete Mixtures Using Two-Phase AHP-TOPSIS Approach , 2019 .

[17]  Ezekiel Chinyio,et al.  Multi-criteria evaluation model for the selection of sustainable materials for building projects , 2013 .

[18]  Mao-Jiun J. Wang,et al.  Tool steel materials selection under fuzzy environment , 1995 .

[19]  Solomon Tesfamariam,et al.  A review of multi-criteria decision-making methods for infrastructure management , 2014 .

[20]  Mahmoud Reza Hashemi,et al.  A window-based automatic hardware/software partitioning heuristic , 2007 .

[21]  Gaetano Manfredi,et al.  Comparative Analysis of Multi‐Criteria Decision‐Making Methods for Seismic Structural Retrofitting , 2009, Comput. Aided Civ. Infrastructure Eng..

[22]  Rakesh Govind,et al.  Algebraic characteristics of extended fuzzy numbers , 1991, Inf. Sci..

[23]  Bijan Samali,et al.  Remedial Modelling of Steel Bridges through Application of Analytical Hierarchy Process (AHP) , 2017 .

[24]  Jurgita Antucheviciene,et al.  Sustainable Decision-Making in Civil Engineering, Construction and Building Technology , 2017 .

[25]  Josef Hegger,et al.  Long-Term Durability of Carbon-Reinforced Concrete: An Overview and Experimental Investigations , 2019, Applied Sciences.

[26]  Gwo-Hshiung Tzeng,et al.  Combining grey relation and TOPSIS concepts for selecting an expatriate host country , 2004, Math. Comput. Model..