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Computer-aided manufacturing (CAM) software allows for the generation of toolpaths for computer numerical control (CNC) machine tools and enables the creation of sophisticated parts that would not otherwise be possible with conventional manual machining methods. Voxel-based CAM is a recent approach to toolpath planning that enables creation of paths for parts that would be difficult to create with traditional CAM software. However, the use of voxel-based CAM necessitates the presence of powerful hardware (specifically, graphics processing units) in order to perform the necessary computations for creating toolpaths. The concepts of virtualization and desktop-as-a-service offer a promising solution to this challenge, as they allow for many users to access computer hardware that is hosted on a single server. This work investigates the performance impact caused by multiple simultaneous users on voxel-based CAM deployed in a virtualized environment. The implementation of a Python application for multi-user simulation on the virtualized platform is described and timing results gathered from a sequence of simulations are presented and analyzed as the number of users is varied. The results from these simulations demonstrate consistent operational times for a low number of simultaneous users before a period of high performance variation due to resource sharing.
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Realization of the 5-Axis Machine Tool Digital Twin Using Direct Servo Control from CAM
This paper describes an architecture for control and monitoring of a 5-axis computer numerical control (CNC) machine tool directly from a computer-aided manufacturing (CAM) system without reliance on the text-based G-Code toolpath definition format that is currently standard in industrial practice. Instead of defining a toolpath as a set of geometric primitives as is done with G-Code, this architecture utilizes a high-speed bidirectional data pathway between the CAM system and the CNC machine to transfer dense time samples of axis position information between the CAM system and the servo controllers of the machine tool’s motion control system in near-realtime. Time samples of axis position are created using a time-optimal trajectory planning algorithm instead of a proprietary trajectory planning strategy that is common in industrial CNC systems. The developed architecture is machine agnostic, and can be used both for enhanced control of machine tool motion and powerful visualization and analysis tasks. An implementation of the system using an open-source machine tool controller known as Machinekit is presented, and a Digital Twin of the machine tool is constructed in the CAM system and shown to be capable of visualizing the as-executed toolpath during machine operation.
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- PAR ID:
- 10066755
- Date Published:
- Journal Name:
- NIST Model Based Enterprise (MBE) Summit 2018
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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