Artificial Intelligence/Machine Learning, Industrial Internet of Things (IIoT), and Cloud Manufacturing technologies, along with rapidly evolving computing infrastructure, require that the fifty-year-old CNC architecture be reexamined to better address the changing needs of manufacturing automation as it evolves from programmed to perceptual automation. This paper introduces Cloud-Direct Numerical Control (C-DNC), an architecture that recruits the services of different computing (cloud, edge, and embedded/real-time) resources, matched to different tasks in the NC workflow. It introduces the concept of a ‘compiled motion program’ to reduce the workload on real-time computing resources by eliminating the repetitive tasks of interpreting G-codes and performing real-time trajectory interpolation. A portion of the freed-up real-time resource bandwidth is used to demonstrate NC-embedded monitoring and IIoT services that not only provide high-bandwidth data collection but also ensure tight temporal alignment of this data with machine instructions. The remaining bandwidth can be used for real-time inferencing and advanced controls to realize truly intelligent NC systems. Finally, this cloud-integrated version of Direct Numerical Control reduces investment costs through the efficient shared use of computing resources, enables new modes for the democratization of NC via subscription and pay-per-use models, and integrates with upstream design and planning software tools. • Proposes Cloud-Direct NC (C-DNC), a distributed cloud–edge architecture for next-generation CNC systems. • Introduces compiled motion programs (bytecode) to eliminate real-time G-code interpretation and interpolation. • Reduces real-time bandwidth requirements, enabling embedded IIoT monitoring, data alignment, and real-time inference. • Demonstrates high-bandwidth, temporally aligned data acquisition at the NC instruction level. • Enables NC-as-a-Service (NCaaS) through scalable, API-driven, cloud-integrated manufacturing workflows.
Garg et al. (Mon,) studied this question.