Split Plot Mixture Process Variable Experiment on Steel Slag Concrete

• Published in: IOP conference series. Earth and environmental science 2018-11, Vol.187 (1), p.12049
• Main Authors: Arina, Faula, Wigena, Aji Hamim, Made Sumertajaya, I, Syafitri, Utami
• Format: Article
• Language: English
• Subjects: Algorithms; Apexes; Concrete; Constraint modelling; Design of experiments; Experimental design; Experiments; Extreme values; Mathematical models; Process variables; Slag; Statistical models; Steel
• ISSN: 1755-1307; 1755-1315; 1755-1315
• DOI: 10.1088/1755-1315/187/1/012049

In many such mixture-process variable experiments, constraints such as cost or time prohibit the selection of treatments completely at random. This leads to a split-plot structure of the data and affects both the experimental design and the statistical modelling. The constraints of the mixture component affect the experimental region. The experimental region could be a regular or irregular shape. For the irregular shape, the design points are difficult to identify by hand. XVERT algorithm is one algorithm in mixture experiments to define the design points of mixture experiment. An algorithm used for selecting a subset of extreme vertices when the number of candidate vertices is large. This research a new split-plot designs of mixture experiments with process variables was developed. The study case was on cementitious mixture components for steelslag concrete. The five mixture components were cement, aggregate fine, aggregate coarse, percentage steel slag replaced the aggregate fine and water. The process variable was size of steel slag. The steel slag concrete experiment was run using a split plot mixture process variable design with 23 whole plots of three observations. The final design consisted of {8 7 8} and experiment design with 69 observations.