An Internet of Things-Based Monitoring System for Shop-Floor Control

Author:

Mourtzis Dimitris1,Milas Nikolaos1,Vlachou Aikaterini1

Affiliation:

1. Laboratory for Manufacturing Systems and Automation, University of Patras, Patra 26500, Greece e-mail:

Abstract

With the advent of the fourth industrial revolution (Industry 4.0), manufacturing systems are transformed into digital ecosystems. In this transformation, the internet of things (IoT) and other emerging technologies pose a major role. To shift manufacturing companies toward IoT, smart sensor systems are required to connect their resources into the digital world. To address this issue, the proposed work presents a monitoring system for shop-floor control following the IoT paradigm. The proposed monitoring system consists of a data acquisition device (DAQ) capable of capturing quickly and efficiently the data from the machine tools, and transmits these data to a cloud gateway via a wireless sensor topology. The monitored data are transferred to a cloud server for further processing and visualization. The data transmission is performed in two levels, i.e., locally in the shop-floor using a star wireless sensor network (WSN) topology with a microcomputer gateway and from the microcomputer to Cloud using Internet protocols. The developed system follows the loT paradigm in terms of connecting the physical with the cyber world and offering integration capabilities with existing industrial systems. In addition, the open platform communication—unified architecture (OPC-UA) standard is employed to support the connectivity of the proposed monitoring system with other IT tools in an enterprise. The proposed monitoring system is validated in a laboratory as well as in machining and mold-making small and medium-sized enterprises (SMEs).

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications,Software

Reference49 articles.

1. The Evolution of Manufacturing Systems: From Craftsmanship to the Era of Customization,2014

2. Optimizing Energy Consumption in a Decentralized Manufacturing System;ASME. J. Comput. Inf. Sci. Eng.,2017

3. Internet of Things and the Future of Manufacturing,2013

4. Toward Knowledge Management for Smart Manufacturing;ASME. J. Comput. Inf. Sci. Eng.,2017

Cited by 38 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Emerging Technologies and Evolving Work Practices Impacting Employee Engagement- Automobile Industry;Journal of Law and Sustainable Development;2023-11-29

2. IoT-Enabled Deep Learning Algorithm for Estimation of State-of-Charge of Lithium-ion Batteries;Journal of Circuits, Systems and Computers;2023-11-23

3. Cloud manufacturing architectures: State-of-art, research challenges and platforms description;Journal of Industrial Information Integration;2023-08

4. An IoT system for managing machine tool spindles in operation;The International Journal of Advanced Manufacturing Technology;2023-07-28

5. Development of IoT Based Pneumatic Punching Machine;Journal of Mines, Metals and Fuels;2023-03-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3