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机器人操纵器在智能制造系统中的实际应用。

Practical Use of Robot Manipulators as Intelligent Manufacturing Systems.

机构信息

Department of Systems Engineering and Automation, University of Carlos III, Escuela Politécnica Superior, Avd. de la Universidad 30, 28911 Leganés, Spain.

出版信息

Sensors (Basel). 2018 Aug 31;18(9):2877. doi: 10.3390/s18092877.

Abstract

This paper presents features and advanced settings for a robot manipulator controller in a fully interconnected intelligent manufacturing system. Every system is made up of different agents. As also occurs in the Internet of Things and smart cities, the big issue here is to ensure not only that implementation is key, but also that there is better common understanding among the main players. The commitment of all agents is still required to translate that understanding into practice in Industry 4.0. Mutual interactions such as machine-to-machine and man-to-machine are solved in real time with cyber physical capabilities. This paper explores intelligent manufacturing through the context of industrial robot manipulators within a Smart Factory. An online communication algorithm with proven intelligent manufacturing abilities is proposed to solve real-time interactions. The algorithm is developed to manage and control all robot parameters in real-time. The proposed tool in conjunction with the intelligent manufacturing core incorporates data from the robot manipulators into the industrial big data to manage the factory. The novelty is a communication tool that implements the Industry 4.0 standards to allow communications among the required entities in the complete system. It is achieved by the developed tool and implemented in a real robot and simulation.

摘要

本文介绍了全互联智能制造系统中机器人控制器的特点和高级设置。每个系统都是由不同的代理组成的。正如物联网和智慧城市中发生的那样,这里的大问题不仅是确保实施是关键,而且是确保主要参与者之间有更好的共同理解。所有代理的承诺仍然需要将这种理解转化为工业 4.0 中的实践。机器对机器和人机交互等相互作用通过网络物理能力实时解决。本文通过智能工厂内工业机器人操纵器的上下文探索智能制造。提出了一种具有证明的智能制造能力的在线通信算法来解决实时交互问题。该算法旨在实时管理和控制所有机器人参数。所提出的工具与智能制造核心相结合,将机器人操纵器的数据纳入工业大数据中以管理工厂。新颖之处在于一种通信工具,它实现了工业 4.0 标准,允许在完整系统中的所需实体之间进行通信。它是通过开发的工具并在实际机器人和模拟中实现的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d22b/6164753/71f335d257a8/sensors-18-02877-g001.jpg

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