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物联网:为新兴产业应用开发智能可编程物联网控制器。

Internet of Things: Development Intelligent Programmable IoT Controller for Emerging Industry Applications.

作者信息

Chen Ti-An, Chen Shu-Chuan, Tang William, Chen Bo-Tsang

机构信息

Department of Business Administration, JinWen University of Science & Technology, New Taipei City 231307, Taiwan.

Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan.

出版信息

Sensors (Basel). 2022 Jul 8;22(14):5138. doi: 10.3390/s22145138.

Abstract

The Internet of Things (IoT) has become critical to the implementation of Industry 4.0. The successful operation of smart manufacturing depends on the ability to connect everything together. In this research, we applied the TOC (Theory of Constraints) to develop a wireless Wi-Fi intelligent programmable IoT controller that can be connected to and easily control PLCs. By applying the TOC-focused thinking steps to break through their original limitations, the development process guides the user to use the powerful and simple flow language process control syntax to efficiently connect to PLCs and realize the full range of IoT applications. Finally, this research uses oil-water mixer equipment as the target of continuous improvement and verification. The verification results meet the requirements of the default function. The IoT controller developed in this research uses a marine boiler to illustrate the application. The successful development of flow control language by TOC in this research will enable academic research on PLC-derivative applications. The results of this research will help more SMEs to move into smart manufacturing and the new realm of Industry 4.0.

摘要

物联网(IoT)已成为实现工业4.0的关键。智能制造的成功运行取决于将所有事物连接在一起的能力。在本研究中,我们应用约束理论(TOC)开发了一种无线Wi-Fi智能可编程物联网控制器,该控制器可以连接到可编程逻辑控制器(PLC)并轻松对其进行控制。通过应用以TOC为重点的思维步骤来突破其原有局限,开发过程引导用户使用强大且简单的流程语言过程控制语法来高效连接到PLC并实现全方位的物联网应用。最后,本研究以油水混合器设备作为持续改进和验证的对象。验证结果符合默认功能的要求。本研究中开发的物联网控制器以船用锅炉为例进行应用说明。本研究中TOC成功开发的流程控制语言将推动PLC衍生应用的学术研究。本研究结果将帮助更多中小企业进入智能制造和工业4.0的新领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c350/9317047/3ef475eba682/sensors-22-05138-g001.jpg

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