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.
more »
« less
Multi-Axis Voxel-Based CNC Machining of Centrifugal Compressor Assemblies
The use of computer-aided manufacturing (CAM) software is essential in the rapid production of high-quality computer numerical control (CNC) machining toolpaths for complex parts. Typical CAM software relies on analytical representations of part geometry, where curves and surfaces are described by parametric functions. This paper proposes the use of a novel way to represent part geometry known as a voxel model. A voxel model uses a three-dimensional array of small cubes to represent a part volume; these cubes, or voxels, are the three-dimensional analog of two-dimensional pixels in an image. The use of voxels for a CAM application enables higher surface complexity, simplified collision checking, and more robust analysis of material removal than would be possible with typical parametric CAM. The unique capabilities of the voxel-based CAM approach described in this paper enable rapid production of high-quality 5-axis toolpaths for machining complex parts, such as the centrifugal compressor assembly that is presented in this work.
more »
« less
- NSF-PAR ID:
- 10066759
- Date Published:
- Journal Name:
- American Helicopter Society Forum 74
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Direct digital manufacturing (DDM) is the creation of a physical part directly from a computer-aided design (CAD) model with minimal process planning and is typically applied to additive manufacturing (AM) processes to fabricate complex geometry. AM is preferred for DDM because of its minimal user input requirements; as a result, users can focus on exploiting other advantages of AM, such as the creation of intricate mechanisms that require no assembly after fabrication. Such assembly free mechanisms can be created using DDM during a single build process. In contrast, subtractive manufacturing (SM) enables the creation of higher strength parts that do not suffer from the material anisotropy inherent in AM. However, process planning for SM is more difficult than it is for AM due to geometric constraints imposed by the machining process; thus, the application of SM to the fabrication of assembly free mechanisms is challenging. This research describes a voxel-based computer-aided manufacturing (CAM) system that enables direct digital subtractive manufacturing (DDSM) of an assembly free mechanism. Process planning for SM involves voxel-by-voxel removal of material in the same way that an AM process consists of layer-by-layer addition of material. The voxelized CAM system minimizes user input by automatically generating toolpaths based on an analysis of accessible material to remove for a certain clearance in the mechanism's assembled state. The DDSM process is validated and compared to AM using case studies of the manufacture of two assembly free ball-in-socket mechanisms.more » « less
-
Abstract Digital maskless lithography is gaining popularity due to its unique ability to quickly fabricate high-resolution parts without the use of physical masks. By implementing controlled grayscaling and exposure control, it has the potential to replace conventional lithography altogether. However, despite the existence of a theoretical foundation for photopolymerization, observing the voxel growth process in situ is a significant challenge. This difficulty can be attributed to several factors, including the microscopic size of the parts, the low refractive index difference between cured and uncured resin, and the rapid rate of photopolymerization once it crosses a certain threshold. As such, there is a pressing need for a system that can address these issues. To tackle these challenges, the paper proposes a modified Schlieren-based observation system that utilizes confocal magnifying optics to create a virtual screen at the camera's focal plane. This system allows for the visualization of the minute changes in refractive indices made visible by the use of Schlieren optics, specifically the deflection of light by the changing density-induced refractive index gradient. The use of focusing optics provides the system with the flexibility needed to position the virtual screen and implement optical magnification. The researchers employed single-shot binary images with different pixel numbers to fabricate voxels and examine the various factors affecting voxel shape, including chemical composition and energy input. The observed results were then compared against simulations based on Beer–Lambert's law, photopolymerization curve, and Gaussian beam propagation theory. The physical experimental results validated the effectiveness of the proposed observation system. The paper also briefly discusses the application of this system in fabricating microlenses and its advantages over theoretical model-based profile predictions.more » « less
-
null (Ed.)Abstract Although laser-based additive manufacturing (AM) has enabled unprecedented fabrication of complex parts directly from digital models, broader adoption of the technology remains challenged by insufficient reliability and in-process variations. In pursuit of assuring quality in the selective laser sintering (SLS) AM, this paper builds a modeling and control framework of the key thermodynamic interactions between the laser source and the materials to be processed. First, we develop a three-dimensional finite element simulation to understand the important features of the melt pool evolution for designing sensing and feedback algorithms. We explore how the temperature field is affected by hatch spacing and thermal properties that are temperature-dependent. Based on high-performance computer simulation and experimentation, we then validate the existence and effect of periodic disturbances induced by the repetitive in- and cross-layer thermomechanical interactions. From there, we identify the system model from the laser power to the melt pool width and build a repetitive control algorithm to greatly attenuate variations of the melt pool geometry.more » « less
-
The goal of this work is to predict the effect of part geometry and process parameters on the instantaneous spatiotemporal distribution of temperature, also called the thermal field or temperature history, in metal parts as they are being built layer-by-layer using additive manufacturing (AM) processes. In pursuit of this goal, the objective of this work is to develop and verify a graph theory-based approach for predicting the temperature distribution in metal AM parts. This objective is consequential to overcome the current poor process consistency and part quality in AM. One of the main reasons for poor part quality in metal AM processes is ascribed to the nature of temperature distribution in the part. For instance, steep thermal gradients created in the part during printing leads to defects, such as warping and thermal stress-induced cracking. Existing nonproprietary approaches to predict the temperature distribution in AM parts predominantly use mesh-based finite element analyses that are computationally tortuous—the simulation of a few layers typically requires several hours, if not days. Hence, to alleviate these challenges in metal AM processes, there is a need for efficient computational models to predict the temperature distribution, and thereby guide part design and selection of process parameters instead of expensive empirical testing. Compared with finite element analyses techniques, the proposed mesh-free graph theory-based approach facilitates prediction of the temperature distribution within a few minutes on a desktop computer. To explore these assertions, we conducted the following two studies: (1) comparing the heat diffusion trends predicted using the graph theory approach with finite element analysis, and analytical heat transfer calculations based on Green’s functions for an elementary cuboid geometry which is subjected to an impulse heat input in a certain part of its volume and (2) simulating the laser powder bed fusion metal AM of three-part geometries with (a) Goldak’s moving heat source finite element method, (b) the proposed graph theory approach, and (c) further comparing the thermal trends predicted from the last two approaches with a commercial solution. From the first study, we report that the thermal trends approximated by the graph theory approach are found to be accurate within 5% of the Green’s functions-based analytical solution (in terms of the symmetric mean absolute percentage error). Results from the second study show that the thermal trends predicted for the AM parts using graph theory approach agree with finite element analyses, and the computational time for predicting the temperature distribution was significantly reduced with graph theory. For instance, for one of the AM part geometries studied, the temperature trends were predicted in less than 18 min within 10% error using the graph theory approach compared with over 180 min with finite element analyses. Although this paper is restricted to theoretical development and verification of the graph theory approach, our forthcoming research will focus on experimental validation through in-process thermal measurements.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
