Lightweight Expanded Clay Aggregate Composite Kasgot Production Optimization Using The Taguchi Method to Promote Agroindustrial Technology

Abstract

This research focuses on optimizing the manufacturing process of Lightweight Expanded Clay Aggregate (LECA) made from a mixture of kasgot composites by integrating the Taguchi method, regression analysis, and Anova. The main problem of this research is the uncertainty of the quality of LECA made from kasgot composites due to less than ideal production process parameters. In addition, the increase in kasgot waste also encourages the need for more valuable utilization so that the LECA production process must be efficient to be optimal, consistent, and environmentally friendly. The Taguchi method is used to determine the most effective combination of production parameters, including firing temperature, firing duration, and LECA grain diameter using the L9 experimental design. The results of the analysis show that firing temperature is the most dominant factor, especially on production costs and surface roughness values. The findings of the Anova analysis confirm that temperature has a significant effect on most responses, while diameter has a strong effect on the LECA mass parameter. A regression model is then built to predict the behavior of each response based on process factors. Based on the research of these two methods, the most optimal is the Anova method with a firing temperature of 200°C, a firing time of 2 hours, and a diameter of 2 cm. The standard error obtained for cost is 0, for roughness is 0.178, for mass is 53.7, for permeability is 0.235 with a composite desirability value of 0.607448.