Dynamic Modeling of Manufacturing Equipment Capability Using Condition Information in Cloud Manufacturing

Author:

Xu Wenjun12,Yu Jiajia34,Zhou Zude15,Xie Yongquan12,Pham Duc Truong6,Ji Chunqian6

Affiliation:

1. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China

2. Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, 122 Luoshi Road, Wuhan 430070, China e-mail:

3. School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China

4. Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan 430070, China e-mail:

5. School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China e-mail:

6. School of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK e-mail:

Abstract

There is a growing need of knowledge description of manufacturing equipment and their capabilities for users, in order to efficiently obtain the on-demand services of manufacturing equipment in cloud manufacturing, and the understanding of the manufacturing capability of equipment is the most important basis for optimizing the cloud service management. During the manufacturing processes, a number of uncertain incidents may occur, which could degrade the manufacturing system performance or even paralyze the production line. Hence, all aspects about the equipment should be reflected within the knowledge description, and the static and dynamic information are both included in the knowledge model of manufacturing equipment. Unification and dynamics are the most important characteristics of the framework of knowledge description. The primary work of this study is fourfold. First, three fundamental ontologies are built, namely, basic information ontology, functional ontology, and manufacturing process ontology. Second, the correlation between the equipment ontology and the fundamental ontology that forms the unified description framework is determined. Third, the mapping relationship between the real-time condition data and the model of manufacturing equipment capability ontology is established. On the basis of the mapping relationship, the knowledge structure of the manufacturing equipment capability ontology is able to update in real-time. Finally, a prototype system is developed to validate the feasibility of the proposed dynamic modeling method. The system implementation demonstrates that the proposed knowledge description framework and method are capable of reflecting the current conditions and the dynamic capability of manufacturing equipment.

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering

Reference46 articles.

1. Cloud Manufacturing: A New Service-Oriented Networked Manufacturing Model;Comput. Integr. Manuf. Syst.,2010

2. A Review of Engineering Research in Sustainable Manufacturing;ASME J. Manuf. Sci. Eng.,2013

3. From Cloud Computing to Cloud Manufacturing;Robot. Comput. Integr. Manuf.,2012

4. Cloud Manufacturing: A New Manufacturing Paradigm;Enterp. Inform. Syst.,2014

Cited by 30 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. From cloud manufacturing to cloud–edge collaborative manufacturing;Robotics and Computer-Integrated Manufacturing;2024-12

2. Reconfigurable Digital Twin from the Perspective of Smart Manufacturing Systems in Industry 4.0/5.0;Journal of Physics: Conference Series;2024-08-01

3. Industry 5.0 or industry 4.0S? Introduction to industry 4.0 and a peek into the prospective industry 5.0 technologies;International Journal on Interactive Design and Manufacturing (IJIDeM);2023-02-05

4. A methodology for creating semantic digital twin models supported by knowledge graphs;2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA);2022-09-06

5. Cloud remanufacturing: Remanufacturing enhanced through cloud technologies;Journal of Manufacturing Systems;2022-07

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