Employing Explainable Artificial Intelligence (XAI) Methodologies to Analyze the Correlation between Input Variables and Tensile Strength in Additively Manufactured Samples

TL;DR

This study uses Explainable AI techniques, specifically SHAP, to analyze how input parameters like Infill percentage and Extrusion Temperature influence Tensile Strength in additive manufacturing, revealing complex nonlinear relationships.

Contribution

It introduces the application of XAI methodologies, particularly SHAP, to interpret the influence of manufacturing parameters on Tensile Strength, providing new insights into process optimization.

Findings

Infill percentage and Extrusion Temperature are the most influential factors.

The relationship between parameters and Tensile Strength is highly nonlinear.

Simple linear models are insufficient to describe the parameter effects.

Abstract

This research paper explores the impact of various input parameters, including Infill percentage, Layer Height, Extrusion Temperature, and Print Speed, on the resulting Tensile Strength in objects produced through additive manufacturing. The main objective of this study is to enhance our understanding of the correlation between the input parameters and Tensile Strength, as well as to identify the key factors influencing the performance of the additive manufacturing process. To achieve this objective, we introduced the utilization of Explainable Artificial Intelligence (XAI) techniques for the first time, which allowed us to analyze the data and gain valuable insights into the system's behavior. Specifically, we employed SHAP (SHapley Additive exPlanations), a widely adopted framework for interpreting machine learning model predictions, to provide explanations for the behavior of a machine learning model trained on the data. Our findings reveal that the Infill percentage and Extrusion Temperature have the most significant influence on Tensile Strength, while the impact of Layer Height and Print Speed is relatively minor. Furthermore, we discovered that the relationship between the input parameters and Tensile Strength is highly intricate and nonlinear, making it difficult to accurately describe using simple linear models.