This study explores the production process and mechanical properties of biocomposites reinforced with pineapple leaf fibres. The biocomposite fabrication involves the use of various techniques, including compression moulding, to integrate the natural fibres into a polyester matrix. The mechanical performance of the resulting composites is evaluated through a comprehensive set of tests, including tensile strength measurements and Energy Dispersive X-Ray Spectroscopy (EDX). Key factors influencing mechanical behaviour, such as fibre content, orientation, and production variables, are systematically examined. Additionally, the chemical composition of the composites is assessed to understand its role in their performance. The findings provide valuable insights into the potential applications of pineapple leaf fibre-based biocomposites in industries requiring lightweight, sustainable materials with enhanced mechanical properties. This paper aims to establish a clear link between production techniques and mechanical performance, highlighting the practical potential of these biocomposites for environmentally-conscious material solutions.

The primary objective of this study is to determine the Coir fibres (CF) utilization in solar stills (SS) to boost the quantity of freshwater production. By placing dry CF fibres in the absorber basin, researchers were able to accelerate the rate at which water evaporated from the SS. Under various CF densities, the freshwater production of the absorber basin was measured (8, 11, 14, 18, 20, 23, and 26). The outcomes demonstrated that yield was raised by 27.23 percent after 18-fiber SSCF was added to the absorber basin. There were 14.27 percent, 19.40 percent, 24.57 percent, 25.00 percent, 16.28 percent, and 6.23 percent yield improvements for solar stills with 8, 11, 14, 18, 20, 23, and 26 fibres in the absorber basin, respectively, as compared to a CSS. The results demonstrate that compared to CSS, the cost to produce one litre of freshwater with SSCF is reduced by 23.1%. The return of investment for SSCF is much more immediate than it is for CSS. An estimated ₹242 was needed to produce 1 litre of freshwater using CSS, while an estimated ₹199 was needed to produce 1 litre of freshwater using SSCF. The payback time for SS was only 6.23 months, which was significantly less than that of solar panels. CF are preferable to other materials for use in the solar still due to their lower cost and higher energy efficiency.

Biocompatibility, affordability, and broad availability are three reasons why natural-based composites are gaining popularity among both producers and consumers. The possibility of forming a composite with Alumina (Al2O3) a cost-effective nano filler material, natural fibers, and an epoxy matrix is explored in this study. In particular, it investigates the effects of three different Al2O3 concentrations on the mechanical properties of a hybrid composite made of hemp and kenaf, including hardness, impact resistance, flexural strength, and inter-laminar shear strength (ILSS). Hand layup followed by hot pressing was used to produce the composites. The composite containing 6 wt% Al2O3 (C3) outperformed the other configurations by a margin of 2% to 36 % in terms of tensile, flexural, ILSS, and impact strengths. Adding 6 wt% Al2O3 increased the mechanical properties of the composite by increasing fiber-matrix adhesion, according to scanning electron microscopy (SEM) study of the cracked surfaces.

The evolution of digital supply chains is one of the most significant transformations within modern business operations. As global markets and technological capabilities continue to evolve, businesses have been forced to adapt to new demands, operational complexities, and technological advancements. Initially, supply chains were traditionally managed through manual processes, spreadsheets, and basic Enterprise Resource Planning (ERP) systems. These systems offered limited automation, often leading to inefficiencies, delays, and a lack of visibility across the entire supply chain. However, the rise of digital technologies in the late 20th and early 21st centuries introduced a paradigm shift in how supply chains functioned. These early advancements laid the foundation for a new era in supply chain management—one driven by interconnected, real-time systems that could monitor and manage the flow of goods, services, and information with greater precision and efficiency.

Bio-composite materials are gaining momentum as eco-friendly substitutes for synthetic fiber-reinforced composites across various sectors. This study investigates how varying fine powder loads affect the tensile, transverse, and compressive properties of hybrid composites comprising Malabar Ironwood sawdust and COCO dust particles. A hybrid composite formulation was devised using a 1:1 ratio of sawdust and COCO dust particles as fillers. Different levels of reinforcement, ranging from 20% to 60%, were examined. ASTM testing was performed on the produced composites, revealing a notable influence of filler reinforcement on their mechanical characteristics. The elongation at fracture increased until 40% filler loading before declining, whereas tensile strength, transverse rupture strength, transverse modulus, and compressive strength consistently improved up to 50% filler loading. These results underscore the potential of composites integrating Malabar Ironwood, COCO dust, and epoxy for lightweight applications, thereby catering to diverse industries seeking sustainable alternatives to traditional materials. Ultimately, such initiatives contribute to solid waste management efforts, offering sustainable alternatives to conventional materials in diverse industries.

This scientific research investigates the multi-objective drilling optimization of a novel flax/kenaf/epoxy biocomposites reinforced with abrasive magnesium hydroxide (Mg(OH) ₂ ) fillers, employing a comparative statistical and machine learning framework to bridge the gap between predictive modeling and physical tool-wear mechanisms. A Face-Centered Central Composite Design (FCCCD) evaluated the effects of spindle speed, feed rate, and tool material (HSS, M35, M42) on delamination, surface roughness, and circularity error. Models were developed using Response Surface Methodology (RSM) and a Bayesian-regularized Artificial Neural Network (ANN). The results quantitatively identify feed rate as the dominant parameter, explaining over 86.5% of the variance in surface roughness. Furthermore, the M42 cobalt-alloyed drill successfully resisted abrasive filler adhesion, reducing maximum delamination by nearly 30% compared to baseline HSS tools. From a modeling perspective, the ANN demonstrated superior capability in capturing non-linear dynamic machining behavior, outperforming RSM prediction accuracy by 12.3% for circularity error and 5.7% for delamination. Desirability-based multi-objective optimization established a highly robust industrial process window (1296 rpm, 0.20 mm/rev, M42 tool) that simultaneously minimized all defects. This experimentally validated framework provides actionable guidelines for the high-quality, sustainable machining of mineral-filled hybrid biocomposites in structural automotive and aerospace assemblies.