Constructing a framework for selecting natural fibres as reinforcements composites based on grey relational analysis

Abstract

Abstract Material selection is crucial in product development, especially when material from a composites process application is involved. Numerous multi-criteria decision-making (MCDM) tools each have their own set of advantages and disadvantages. Using grey relational analysis (GRA), this research proposes a systematic framework evaluation approach for generating a sensible rank for material selection of natural fibre as reinforcement composites. The framework was created using the GRA technique, a robust evaluation tool that employs the grade of relation to determine the degree of similarity or difference between two sequences. The MCDM approach can be straightforward for the material selection problem. A GRA technique is used to investigate the performance of the potential material, which includes grey relational sequence creation, reference sequence definition, grey relational coefficient calculation and grey relational grade determination. This framework is applied with a case study to identify the optimum natural fibres composites material for a bike helmet. End results revealed that pineapple is the best candidate for construction of safety gear (cyclist helmet). The best possible evaluation model for material selection of the composite can be referred by design engineer in composite industry for multiple applications. Moreover, the proposed framework is an aid to help engineers and designers to choose most suitable material.