3D Printer Using Bayesian Optimization —Optimization of Molding Resin Strength and Molding Time—

User Benefits

- Excellent results can be achieved with fewer trials with Bayesian optimization. - When the AGS-V is used, tensile tests can be conveniently performed with excellent precision.

Introduction

3D printer technology is widely used in manufacturing and research and development to efficiently produce parts with complex shapes. However, its quality depends on various factors, such as the material used, the forming conditions, and equipment settings. Optimizing these factors is not easy. In particular, to improve performance indicators, such as forming accuracy, surface quality, and strength, it is necessary to adjust a large number of parameters, so traditional methods based on trial and error require large amounts of time and cost. In recent years, “Bayesian optimization” has been attracting attention as a solution. It is a statistical method that can efficiently search for optimum parameters with a limited number of trials. It is particularly effective for high-dimensional, nonlinear problems. This article introduces an example in which Bayesian optimization was used on a model for manufacturing tensile test specimens using a resin 3D printer to obtain 3D printing conditions (explanatory variables) that optimized tensile strength and manufacturing times (objective variables).

October 7, 2025 GMT