The disposal of plastic waste is a significant eco-technological issue that addresses global environmental degradation and climate change and produces poisonous byproducts that contribute to global pollution. Ethiopia is reporting an increasing number of problems related to the growing use of plastics and their disposal, which has increased the demand for biodegradable polymers. The objective of this study was to optimize the process parameters of sisal fiber-reinforced thermoplastic starch biocomposites for sustainable packaging applications. This study examined the effects of alkaline treatment (6% wt, 12% wt, and 18% wt) and fiber content (10% wt, 20% wt, and 30% wt) on the tensile strength, water absorption, and biodegradability of biocomposites. The composite sample test was prepared according to ASTM D638 for tensile strength, which is crucial for packaging materials as it determines their ability to withstand forces during handling, storage, and transportation; ASTM D570 for water absorption, which can degrade material properties and compromise package durability; and ASTM D5338 for the biodegradability test, which is a key feature for eco-friendly packaging materials, especially in response to environmental concerns regarding plastic waste. The combination of process parameters that optimizes tensile strength, water absorption and biodegradability simultaneously was obtained using Taguchi-based grey relational analysis. The results demonstrated that a biocomposite with optimal properties was fabricated with 30% wt fiber content and 18% wt alkali treatment. The biocomposite fabricated at the optimal process parameters achieved better water absorption, biodegradability, and tensile strength values of 40.22% wt, 64.78% wt, and 4.24 MPa, respectively. These results represent the best properties for intended sustainable packaging applications.

The use of natural fibers (NFs) in polymer composites is a modern trend aimed at developing materials with numerous benefits, including low cost, environmental friendliness, biodegradability, and high specific mechanical performance. Ethiopia is abundant in NFs such as palm trees, sisal, water hyacinth, and the newly emerging water lilies. In areas like Lake Tana, Ethiopia, water lilies, much like water hyacinths, negatively impact water surfaces by covering them and reducing their surface area. Therefore, analyzing the mechanical and physical properties of composites reinforced with these fibers is crucial for diverse structural and industrial applications, considering factors such as tensile strength, flexural strength, and hardness. In this study, a composite material consisting of a water lily–polyester resin matrix was prepared with varying matrix‐to‐fiber weight ratios (90/10 wt%, 80/20 wt%, 70/30 wt%, 60/40 wt%, 50/50 wt%, and 40/60 wt%). The experimental data revealed that the optimal mechanical properties, including maximum tensile strength, flexural strength, and hardness, were achieved with a composition of 60% matrix material and 40% reinforcing material. These chopped water lily fiber–reinforced polyester composites demonstrate promising mechanical and physical properties, making them suitable for various applications, similar to other NFs like sisal and palm. Further studies, such as thermal analysis, could enhance the understanding and utilization of these composites. The fabricated water lily composite can serve as a viable alternative material for applications in automobile interior parts, building components, and electronic packages.

This study applies an integrated Taguchi-Gray Relational Analysis (GRA) method to optimize CNC end milling parameters for AISI 4130 low-alloy steel, aiming to simultaneously maximize Material Removal Rate (MRR) and minimize surface roughness (Ra). Experiments were designed using an L9 orthogonal array, varying spindle speed (1200, 1400, 1600 rpm), feed rate (0.009, 0.014, 0.019 mm/tooth), and depth of cut (0.1, 0.15, 0.2 mm) under dry conditions with a high-speed steel end mill. The multi-response data were converted into a single Gray Relational Grade (GRG) for optimization. Analysis identified the optimal parameter set as 1600 rpm spindle speed, 0.019 mm/tooth feed rate, and 0.2 mm depth of cut. Analysis of Variance (ANOVA) on the GRG indicated spindle speed as the most statistically significant factor, accounting for 83.73% of the performance variation, followed by feed rate (10.11%) and depth of cut (2.25%). Confirmation experiments at the optimal settings validated the results, achieving a GRG improvement of 10.7% over the initial best run, with MRR of 31.65 cm ³ /min and Ra of 0.37 µm. The findings provide a practical framework for enhancing productivity and surface finish in the machining of AISI 4130 steel components.