A Study on Natural Plant Fiber Selection Using Multi-Criteria Decision Making Techniques

Natural plant fibers are primarily composed of cellulose, hemicelluloses, lignin, pectin, and wax, with naturally available minor amounts of other constituents. These constituents have an impact on the fiber’s physical, mechanical, thermal, and other characteristics. The researchers’ estimations or limited evaluation perspectives still govern the selection of natu-ral fibers for composite fabrication. By applying Multi-Criteria Decision-Making (MCDM) methods to the properties of natural fibers, one can make a statistically sound decision about which fiber to use. However, this can be a disadvantage in terms of the complex-ity of testing for determining fiber properties and manufacturing natural fiber composites when introducing a new fiber. Whereas, the determination of chemical constituents is an easy and straightforward procedure. This paper describes a novel technique designed in MATLAB for natural plant fiber selection study based on the chemical constituents of the fibers as well as the correlation between the properties of the fibers and their chemical con-stituents. The correlation matrix was used to convert the weights given to properties into the weights of chemical constituents by weighted scoring model. The best suitable method among the MCDM’s was also determined. The high degree of agreement between the tra-ditional method and the proposed method indicates that the proposed technique can be used as a tool for the selection of natural plant fiber and composite fabrication.