SELECTION METHOD OF MOLDING CONDITION FOR SELF-ADHESIVE PRODUCTS USING ONLY BAMBOO FIBERS EXTRACTED WITH A MACHINING CENTER BASED ON BAYESIAN OPTIMIZATION

Bamboo grows naturally in Japan as an underutilized forest resource, and its fibers have high specific strength and stiffness, so much so that they are called natural glass fibers. In this study, a method for manufacturing a self-adhesive compact material by pressurizing and heating 100% bamboo fiber after extraction using a machining center, without losing the composition of bamboo, is proposed. This molded body is made of a 100% natural material and has a low environmental impact even when landfilled, contributing to the growth of bamboo for use as a raw material. In this study, the formation conditions for maximizing the tensile properties when forming platelets were investigated. First, an analysis of the variance was conducted using the orthogonal array test design to identify the factors affecting the objective variable and determine the contribution of each factor. In addition, estimates of the objective variable for the molding conditions were obtained from the Gaussian process regression model in a Bayesian optimization. Furthermore, as a result of comparing the maximum values of the properties of the molding conditions between the analysis of variance and the Gaussian process regression model, the values of the tensile properties were improved in the Gaussian process regression model.