A New Sparse-Learning Model for Maximum Gap Reduction of Composite Fuselage Assembly

Abstract

Natural dimensional variabilities of incoming fuselages affect the assembly speed and quality of fuselage joins in composite fuselage assembly processes. This paper introduces a new sparse-learning model for optimal shape control to minimize the maximum gap between fuselages, significantly improving assembly quality and efficiency.

Juan Du

Assistant Professor

My research interests include knowledge-infused data science for quality improvement, industrial data analytics and machine learning, and system informatics and control for manufacturing applications.