Explainable AI Platform for Quality Management in Manufacturing

Explainable artificial intelligence for quality management in manufacturing

Objective

• The goal is to develop a scaleable quality management platform using explainable AI models like SHAP, which can provide decision support to engineers to eliminate the root causes of yield loss.

Description

• We are in the midst of artificial intelligence (AI) spring. Machine learning (ML) is driving this revolution, and to capture intricate patterns and complexity in data, ML models are becoming increasingly complex., Interpretability and explainability are two important criteria for understanding the model and the predictions. Both are important for accurately modeling the relationship between the dependent and independent variables., In this project, we focus on quality management in manufacturing processes using explainable AI models. One such model is SHAP (SHapley Additive exPlanations), It is a powerful concept based on the Shapley value, an important solution concept for cooperative games.

Impact

• It is a powerful concept based on the Shapley value, an important solution concept for cooperative games.