CPS: Synergy: CNC Process Plan Simulation, Automation and Optimization

CPS：协同：CNC 工艺计划仿真、自动化和优化

• 批准号: 1646013
• 负责人: Thomas Kurfess
• 金额: $ 70.13万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646013&HistoricalAwards=false
• 关键词: CPS; Synergy; CNC; Process; Plan

Machining is a fundamental manufacturing capability critical to the production of end-user goods and systems, as well as the tooling and equipment used in virtually every industrial process. Machine tool programming to support these processes is critical for both production and cost estimation. However, currently available automated process planning methods constrain the tool to follow geometrically simple paths to minimize computational requirements, limit the tool velocity and/or tool orientation during a simple path to constant values, also to save computational burden, and/or process one geometrical feature at a time without attempting to optimize the entire process. This award supports fundamental research to provide knowledge needed for development of a novel computer-aided process planning and control architecture for integrated complex tool path generation and optimization. The resulting new mathematical algorithms will drive effective real-time control and optimization of manufacturing processes and enable substantial increases in machine productivity. These capabilities will have potential for broad-ranging impact on the domestic economy, which uses machining in the vast majority of products, due to its flexibility, speed, cost, and accuracy advantages relative to other processes. The research integrates several complementary technical domains, including advanced manufacturing, geometric computing, and high performance parallel computing. Conventional computer-aided manufacturing approaches for toolpath optimization are inherently post-hoc methods that are not well integrated for supporting simultaneous generation and optimization of the process plan. This research will investigate generic optimization and control architectures for automated toolpath optimization, which require global solutions to highly non-linear, constrained optimization problems in high-dimensional search spaces of tool motions with time-varying positions and orientations. To address this challenge, the research approach will utilize a bi-directional optimization scheme that consists of: (l) a top-down, multi-level decomposition of the problem into fundamental model motions (e.g., curved blocks, peel layers, tool swipes) and (2) a bottom-up optimization of these fundamental geometric model motions. The latter schema element will fully support the option of selecting cutting tools to maximize material removal rate and/or surface finish and will build upon theoretical formulations and efficient computing implementations of volume preserving offsetting, steady motion interpolation, and ball morphing surface interpolation. The resulting fundamental motion models and associated fast, parallel computing algorithms will provide for rapid analysis of swept regions, collision avoidance and computing material removal rates that are critical for facilitating rapid toolpath optimization.

机械加工是一种基本的制造能力，对最终用户的产品和系统的生产至关重要，也是几乎每个工业过程中使用的工具和设备。支持这些过程的机床编程对生产和成本估算都至关重要。然而，目前可用的自动化工艺规划方法将刀具限制在几何上简单的路径上，以最大限度地减少计算需求，在简单的路径上限制刀具速度和/或刀具方向为恒定值，也可以节省计算负担，或者一次处理一个几何特征而不试图优化整个过程。该奖项支持基础研究，为开发用于集成复杂刀具路径生成和优化的新型计算机辅助工艺规划和控制体系结构提供所需的知识。由此产生的新的数学算法将推动制造过程的有效实时控制和优化，并使机器生产率大幅提高。这些能力将对国内经济产生广泛的潜在影响，由于其相对于其他工艺的灵活性、速度、成本和精度优势，绝大多数产品都使用机械加工。该研究整合了几个互补的技术领域，包括先进制造、几何计算和高性能并行计算。传统的用于刀具路径优化的计算机辅助制造方法是固有的事后方法，不能很好地集成以支持同时生成和优化工艺计划。本研究将研究自动化刀具路径优化的通用优化和控制体系结构，这需要在具有时变位置和方向的刀具运动的高维搜索空间中解决高度非线性约束优化问题的全局解决方案。为了应对这一挑战，研究方法将利用双向优化方案，该方案包括：(1)自上而下、多层次地将问题分解为基本模型运动（例如，弯曲块、剥离层、工具滑动）和(2)自下而上地优化这些基本几何模型运动。后一种模式元素将完全支持选择切削工具的选项，以最大限度地提高材料去除率和/或表面&amp；#64257；并将建立在理论公式和ef&amp；#64257；体积保持偏移，稳定运动插值和球变形曲面插值的客户端计算实现。由此产生的基本运动模型和相关的快速并行计算算法将提供快速分析扫描区域，避免碰撞和计算材料去除率，这对于促进快速刀具路径优化至关重要。

项目成果

Multi-Axis Voxel-Based CNC Machining of Centrifugal Compressor Assemblies

基于多轴体素的离心压缩机组件 CNC 加工

• 发表时间: 2018
• 期刊: American Helicopter Society Forum 74
• 作者: Kurfess, T.R.

Thin wall deposition of IN625 using directed energy deposition

• DOI: 10.1016/j.jmapro.2020.04.032
• 发表时间: 2020-08-01
• 期刊: JOURNAL OF MANUFACTURING PROCESSES
• 影响因子: 6.2
• 作者: Kim, Myong Joon;Saldana, Christopher
• 通讯作者: Saldana, Christopher

Effects of spatial energy distribution-induced porosity on mechanical properties of laser powder bed fusion 316L stainless steel

• DOI: 10.1016/j.addma.2021.101875
• 发表时间: 2021-03-01
• 期刊: ADDITIVE MANUFACTURING
• 影响因子: 11
• 作者: Jost, Elliott W.;Miers, John C.;Saldana, Christopher
• 通讯作者: Saldana, Christopher

Adaptive repair and digitization for hybrid manufacturing

• DOI: 10.1016/j.promfg.2019.06.133
• 发表时间: 2019
• 期刊: Procedia Manufacturing
• 作者: Myong Joon Kim;M. Praniewicz;T. Kurfess;C. Saldana

Conceptualization and Design of a Low-Cost MTConnect-Enabled Refractometer for Coolant Health Monitoring

用于冷却剂健康监测的低成本 MTConnect 折光仪的概念化和设计

• DOI: 10.1115/msec2019-2755
• 发表时间: 2019
• 期刊: ASME 2019 14th International Manufacturing Science and Engineering Conference
• 作者: Feldhausen, Thomas;Hirani, Asimm;King, Walter;Lynn, Roby;Kurfess, Thomas
• 通讯作者: Kurfess, Thomas