Real-time Process Authentication for Additive Manufacturing Processes based on In-situ Video Analysis

Abstract

Additive manufacturing (AM) processes are subject to cyber-physical attacks during all the three stages including design, slicing, and manufacturing phases. In-situ process authentication is crucial for AM to ensure that the manufacturing is performed as intended. Since most of the cyber-physical attacks aiming to alter AM processes can be manifested in the change of printing path, an in-situ optical imaging system is capable of detecting alteration in printing path in real time through texture analysis. This will prevent catastrophic geometric changes and mechanical property compromises in the AM parts, and hence improving the AM process security. In this paper, a new part authentication framework is proposed by leveraging layer-wise in-situ videos. The distribution of the segmented textures’ geometric features is extracted from the layer-wise videos, and the multilinear principal component analysis (MPCA) algorithm is used to extract low-dimensional features from the joint distribution of geometric features. A case study based on a fused filament fabrication (FFF) process is used to validate the proposed framework.