Search Results (3)

Increasing scientific interest has occurred concerning the utilization of natural fiber-enhanced hybrid composites that incorporate one or more types of natural enhancement. Annual natural fiber production is estimated to be 1,783,965 $\times {10}^3$ tons/year. Extensive studies have been conducted in the domains of natural/synthetic as well as natural/natural hybrid composites. As synthetic fibers have better rigidity and strength than natural fibers, natural/synthetic hybrid composites have superior qualities via hybridization compared to natural composites in fibers. In general, natural fiber compounds have lower characteristics, limiting the use of natural composites reinforced by fiber. Significant effort was spent in enhancing the mechanical characteristics of this group of materials to increase their strengths and applications, especially via the hybridization process, by manipulating the characteristics of fiber-reinforced composite materials. Current studies concentrate on enhancing the understanding of natural fiber-matrix adhesion, enhancing processing methods, and natural fiber compatibility. The optimal and resilient conceptions have also been addressed due to the inherently more significant variabilities. Moreover, much research has tackled natural fiber reinforced hybrid composite costs. In addition, this review article aims to offer a review of the variables that lead to the mechanical and structural failure of natural fiber reinforced polymer composites, as well as an overview of the details and costings of the composites. Full article

Natural fiber such as bamboo fiber, oil palm empty fruit bunch (OPEFB) fiber, kenaf fiber, and sugar palm fiber-reinforced polymer composites are being increasingly developed for lightweight structures with high specific strength in the automotive, marine, aerospace, and construction industries with significant economic benefits, sustainability, and environmental benefits. The plant-based natural fibers are hydrophilic, which is incompatible with hydrophobic polymer matrices. This leads to a reduction of their interfacial bonding and to the poor thermal stability performance of the resulting fiber-reinforced polymer composite. Based on the literature, the effect of chemical treatment of natural fiber-reinforced polymer composites had significantly influenced the thermogravimetric analysis (TGA) together with the thermal stability performance of the composite structure. In this review, the effect of chemical treatments used on cellulose natural fiber-reinforced thermoplastic and thermosetting polymer composites has been reviewed. From the present review, the TGA data are useful as guidance in determining the purity and composition of the composites’ structures, drying, and the ignition temperatures of materials. Knowing the stability temperatures of compounds based on their weight, changes in the temperature dependence is another factor to consider regarding the effectiveness of chemical treatments for the purpose of synergizing the chemical bonding between the natural fiber with polymer matrix or with the synthetic fibers. Full article

The adoption of forecasting approaches such as the multiplicative Holt-Winters (MHW) model is preferred in business, especially for the prediction of future events having seasonal and other causal variations. However, in the MHW model the initial values of the time-series parameters and smoothing constants are incorporated by a recursion process to estimate and update the level (L_T), growth rate (b_T) and seasonal component (SN_T). The current practice of integrating and/or determining the initial value of L_T is a stationary process, as it restricts the scope of adjustment with the progression of time and, thereby, the forecasting accuracy is compromised, while the periodic updating of L_T is avoided, presumably due to the computational complexity. To overcome this obstacle, a fuzzy logic-based prediction model is developed to evaluate L_T dynamically and to embed its value into the conventional MHW approach. The developed model is implemented in the MATLAB Fuzzy Logic Toolbox along with an optimal smoothing constant-seeking program. The new model, proposed as a collaborative approach, is tested with real-life data gathered from a local manufacturer and also for two industrial cases extracted from literature. In all cases, a significant improvement in forecasting accuracy is achieved. Full article