Abstract: Machining is a fundamental processing capability critical to production of end-user goods and systems, as well as components used in virtually every industrial process. Machine tool programming to support these processes is critical for production and cost estimation. Unfortunately, currently available automated process planning methods constrain the process along geometrically simple trajectories due to computational constraints, this at the sacrifice of final processing efficiency.

This research assesses the threat of cyber-physical attacks to manufacturing systems that change the design of a physical part, elude quality control measures, and result in part failure. This goal is achieved through the development of: a cyber-physical attack taxonomy, framework to assess levels of cyber-physical vulnerability, models to detect and diagnose the presence of attacks in real-time, and side-channel detection techniques specific to manufacturing.

Abstract: This grant provides funding for the formulation of a data model, and trajectory planning platform and methodology to execute a fully digital 3D, 5-axis machining capability. Research will be performed on methods for utilizing multiple Graphical Processor Units (GPUs), which are readily available, parallel digital processing hardware in these calculations.