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

机械加工是一种基本的制造能力，对生产最终用户产品和系统以及几乎每个工业过程中使用的工具和设备都至关重要。支持这些工艺的机床编程对于生产和成本估算都是至关重要的。然而，当前可用的自动化工艺规划方法将工具约束为遵循几何上简单的路径以最小化计算要求，在简单路径期间将工具速度和/或工具方向限制为恒定值，还为了节省计算负担，和/或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，以提供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所需的知识。由此产生的新数学算法将推动对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。由于相对于其他工艺的灵活性、速度、成本和精度优势，这些能力将对国内经济产生广泛的影响，国内经济的绝大多数产品都使用机械加工。这项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。用于刀具路径优化的传统计算机辅助制造方法本质上是后自组织方法，其不能很好地集成以支持工艺计划的同时生成和优化。本研究将探讨自动刀轨优化的一般最佳化与控制架构，这需要在具有时变位置与方位的刀具运动的高维搜寻空间中，解决高度非线性、有约束的最佳化问题。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)自顶向下、多层次地将问题分解成基本模型运动(例如，曲线块、剥离层、工具滑动)；(2)对这些基本几何模型运动进行自下而上的优化。后一模式元素将完全支持选择刀具以最大化材料去除速率和/或表面的选项，并将建立在理论公式和体积保持偏移、稳定运动插补和球变形曲面插补的有效计算实现的基础上。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对扫描区域的快速分析、碰撞避免和计算材料去除速率，这些对于促进快速刀具路径优化至关重要。

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.