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The State of Integrated CAM/CNC Control Systems: Prior Developments and the Path Towards a Smarter CNC.集成式计算机辅助制造/计算机数控(CAM/CNC)控制系统的现状:先前的发展以及通往更智能数控系统的道路。
Smart Sustain Manuf Syst. 2020 Jul;4(2). doi: 10.1520/SSMS20190046.
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The Current State of Sensing, Health Management, and Control for Small-To-Medium-Sized Manufacturers.中小型制造商的传感、健康管理与控制现状
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Towards a Lifecycle Information Framework and Technology in Manufacturing.迈向制造业中的生命周期信息框架与技术
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集成式计算机辅助制造/计算机数控(CAM/CNC)控制系统的现状:先前的发展以及通往更智能数控系统的道路。

The State of Integrated CAM/CNC Control Systems: Prior Developments and the Path Towards a Smarter CNC.

作者信息

Lynn Roby, Helu Moneer, Sati Mukul, Tucker Tommy, Kurfess Thomas

机构信息

771 Ferst Dr NW Atlanta, GA 30332.

100 Bureau Dr Gaithersburg, MD 20899.

出版信息

Smart Sustain Manuf Syst. 2020 Jul;4(2). doi: 10.1520/SSMS20190046.

DOI:10.1520/SSMS20190046
PMID:39391869
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11465454/
Abstract

Current industrial practice in automated manufacturing operations relies on low fidelity data transmission methods between computer numerical control (CNC) machine tools and the computer-aided manufacturing (CAM) systems used to program them. The typical language used to program CNC machines, known as G-Code, has been in existence for nearly sixty years and offers limited resolution for command data. In addition, the proprietary nature of industrial CNC systems hampers the ability of manufacturers to expand and improve upon the capability of existing machine tools. G-Code was not designed to support transmission of feedback data, and thus both the CAM system and higher level organizational control systems are frequently blind to the state of the production process; in response, separate standards that enable data exchange with machine tools have been used by industry, such as MTConnect and Open Platform Communications Unified Architecture (OPC UA). However, these standards enable data pathways that are independent of the G-Code command data pathway, and thus provide practically no means to affect the state of a process on receipt of feedback data. As a result, control and data acquisition exist in separate realms, which makes the implementation of self-optimizing smart CNC systems challenging. This state-of-the-art review surveys existing methods for data transmission to and from machine tools and explores the current state of so-called integrated CAM/CNC systems that enable more thorough control of the machining process using intelligence built in to the CAM system. The literature survey reveals that integrated CAM/CNC systems are impeded both by the data exchange methods used to interface with CNC systems in addition to the proprietary and closed architecture of the CNC systems themselves. Future directions in integrated CAM/CNC research are identified based on the requirements identified for such systems.

摘要

当前自动化制造操作中的工业实践依赖于计算机数控(CNC)机床与用于对其编程的计算机辅助制造(CAM)系统之间的低保真数据传输方法。用于对CNC机床进行编程的典型语言,即G代码,已经存在了近60年,并且命令数据的分辨率有限。此外,工业CNC系统的专有性质阻碍了制造商扩展和改进现有机床功能的能力。G代码并非设计用于支持反馈数据的传输,因此CAM系统和更高级别的组织控制系统常常对生产过程的状态一无所知;作为回应,行业使用了诸如MTConnect和开放平台通信统一架构(OPC UA)等能够与机床进行数据交换的单独标准。然而,这些标准所实现的数据路径独立于G代码命令数据路径,因此在接收到反馈数据时几乎无法影响过程状态。结果,控制和数据采集处于分离的领域,这使得实现自我优化的智能CNC系统具有挑战性。这篇综述文章调查了与机床之间进行数据传输的现有方法,并探讨了所谓的集成CAM/CNC系统的当前状态,这些系统能够利用CAM系统中内置的智能对加工过程进行更全面的控制。文献调查表明,集成CAM/CNC系统不仅受到用于与CNC系统接口的数据交换方法的阻碍,还受到CNC系统本身专有和封闭架构的阻碍。基于为此类系统确定的要求,确定了集成CAM/CNC研究的未来方向。