Predict the modelling of cement concrete strength using Taguchi and ANOVA method

被引：0
|
作者：
Venkatesh, Butti. [1 ]
Sivakumar, R. [2 ]
Vijayakumar, S. [3 ]
Satheesh kumar, P.S. [4 ]
Sri, M. Naga Swapna [5 ]
Pradeep, A. [6 ]
机构：
[1] Department of Civil Engineering, Shri Vishnu Engineering College for Women (Autonomous), Andhra Pradesh, Bhimavaram, West Godavari
[2] Department of Chemistry, PSNA College of Engineering and Technology, Dindigul
[3] Department of Mechanical Engineering, Bonam Venkata Chalamayya Engineering College (Autonomous), Andhra Pradesh, Odalarevu
[4] Department of Physics, NPR College of Engineering and Technology, Tamilnadu, Natham, Dindigul
[5] Department of Mechanical Engineering, P V P Siddhartha Institute of Technology, Vijayawada
[6] Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai
来源：
Interactions | 2024年 / 245卷 / 01期
关键词：
And ANOVA; Cement; Concrete; Fly ash; Optimization; Taguchi;
D O I：
10.1007/s10751-024-02133-3
中图分类号：
学科分类号：
摘要：
An experimental study is carried out to the mix proportions of the concrete by using Taguchi method. The experiments have been done using an L9 Orthogonal Array with four parameters having three levels. The selected parameters factors are cement (CE), Mixture of medical waste and fly ash (MF), Water cement ratio (WC) and stone dust (ST). the compressive strength is investigated on the nine prepared samples. Taguchi analysis was employed to find the optimal mix using MINITAB-18 software. Analysis of Variance (ANOVA) results revealed that Cement is best contribution variable (55.1%), followed by Mixture of medical waste and fly ash (29.6%), stone dust (9.1%) and Water cement ratio (4.5%) which improve the compressive strength. A residual analysis was conducted to assess the relationship between the experimental and predicted values for the response variable and regression Equation is used to predict the compressive strength value based on the input factors. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.
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