Multi-objective optimization of carbon/glass hybrid composites with newly developed resin (NDR) using gray relational analysis

Abstract

Purpose

It is seen that little amount of work on optimization of mechanical properties taking into consideration the combined effect of design variables such as stacking angle, stacking sequence, different resins and thickness of composite laminates has been carried out. The focus of this research work is on the optimization of the design variables like stacking angle, stacking sequence, different resins and thickness of composite laminates which affect the mechanical properties of hybrid composites. For this purpose, the Taguchi technique and the method of gray relational analysis (GRA) are used to identify the optimum combination of design variables. In this case, the effect of the abovementioned design variables, particularly of the newly developed resin (NDR) on mechanical properties of hybrid composites has been investigated.

Design/methodology/approach

The Taguchi method is used for design of experiments and with gray relational grade (GRG) approach, the optimization is done.

Findings

From the experimental analysis and optimization study, it was seen that the NDR gives excellent bonding strength of fibers resulting in enhanced mechanical properties of hybrid composite laminates. With the GRA method, the initial setting (A3B2C4D2) was having GRG 0.866. It was increased by using a new optimum combination (A2B2C4D1) to 0.878. It means that there is an increment in the grade by 1.366%. Therefore, using the GRA approach of analysis, design variables have been successfully optimized to achieve enhanced mechanical properties of hybrid composite laminates.

Originality/value

This is an original research work.

Citation

Dnyandev Patil, S. and Bhalerao, Y.J. (2020), "Multi-objective optimization of carbon/glass hybrid composites with newly developed resin (NDR) using gray relational analysis", Multidiscipline Modeling in Materials and Structures, Vol. 16 No. 6, pp. 1709-1729. https://doi.org/10.1108/MMMS-08-2019-0141

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