Integration of data envelopment analysis and Al-Refaie and Al-Tahat model in Taguchi method for the optimisation of additives in expansive soil treatment

ABSTRACT

The effectiveness of the incorporation of data envelopment analysis (DEA) and Al-Refaie and Al-Tahat (AA) model to solve the intrinsic multiple response problem in Taguchi optimisation method was assessed in this study. Charnes, Cooper and Rhodes model, which is a variant of the DEA method, was employed in the optimisation of additives for expansive soil treatment. The additives, which were sawdust ash (SDA), quarry dust (QD) and Portland cement (CM), were assigned various levels in the designed Taguchi mixed level L18 (6^1 × 3^2) orthogonal array experiment. SDA was assigned six levels while CM and QD were assigned three levels each. Multiple responses, which included the unconfined compressive strength, California bearing ratio and differential free swell, were determined with the designed experiment and later optimised concurrently with the DEA and AA model. Optimum combination of the additives (20% SDA + 20%QD + 5% CM) obtained with the models and validated by performing confirmatory tests on the soil admixed with it proved that DEA and AA model can be integrated in Taguchi method to optimise multiple responses simultaneously. Finally, scanning electron microscope of the expansive soil treated with the optimum combination of additives revealed the formation of cementation compound in the mixture.

KEYWORDS:

• Additives optimisation
• data envelopment analysis
• expansive soil
• stabilisation
• Taguchi approach

Acknowledgments

The authors wish to acknowledge the immense contributions of the anonymous reviewers that improved the clarity of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).