Multi-objective optimization of bio-base grease using hybrid taguchi-grey relational analysis - Mohd Noh, Azhari (2023)
Bio grease has gained increasing attention in recent years due to its promising benefits, which include being environmentally friendly, renewable, less toxic, and readily biodegradable. In recent years, numerous studies have been conducted to explore the potential of bio-based greases for industrial applications. This study aimed to create a novel bio-based gease with.a viscosity comparable to a commercial, industrial lubricant. A multi-optimization strategy was utilized to achieve this goal, specifically the Taguchi methodology with grey relational analysis. A total of nine different samples were produced by combining non-edible base oils and different percentages of beeswax thickener and hBN. additives. The optimal blend was then tested for its coefficient of friction and time durability. A greater endurance over time will reflect reliability for application, especially in robust industries. The study employed the Taguchi optimization technique with grey relational analysis to evaluate how diverse design parameters influenced the friction coefficient. According to the findings, the optimal blend of ingredients was 92.5% castor oil, 5% beeswax thickener, and 2.5% hBN additives, resulting in the highest friction coefficient that falls within the range of conventional industrial lubricants. This study contributes to the growing body of research on bio base greases and their potential for industrial applications and demonstrates the effectiveness of a multi-optimization approach using Taguchi with Grey relational analysis. By pursuing this effort, developing and implementing innovative approaches centred on resource conservation will lead to a sustainable future where we can thrive without depleting our planet's limited resources.