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.
Skip Nav Destination
Article navigation
August 2015
Research-Article
Dynamic Modeling of Manufacturing Equipment Capability Using Condition Information in Cloud Manufacturing
Wenjun Xu,
Wenjun Xu
1
School of Information Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
Key Laboratory of Fiber Optic Sensing
Technology and Information Processing,
e-mail: xuwenjun@whut.edu.cn
Technology and Information Processing,
Ministry of Education
,122 Luoshi Road
,Wuhan 430070
, China
e-mail: xuwenjun@whut.edu.cn
1Corresponding author.
Search for other works by this author on:
Jiajia Yu,
Jiajia Yu
School of Mechanical
and Electronic Engineering,
and Electronic Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
Key Laboratory of Fiber Optic Sensing
Technology and Information Processing,
e-mail: yujj1991@126.com
Technology and Information Processing,
Ministry of Education
,Wuhan 430070
, China
e-mail: yujj1991@126.com
Search for other works by this author on:
Zude Zhou,
Zude Zhou
School of Information Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
School of Mechanical
and Electronic Engineering,
e-mail: zudezhou@whut.edu.cn
and Electronic Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
e-mail: zudezhou@whut.edu.cn
Search for other works by this author on:
Yongquan Xie,
Yongquan Xie
School of Information Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
Key Laboratory of Fiber Optic Sensing
Technology and Information Processing,
e-mail: xyqwhut0728@163.com
Technology and Information Processing,
Ministry of Education
,122 Luoshi Road
,Wuhan 430070
, China
e-mail: xyqwhut0728@163.com
Search for other works by this author on:
Duc Truong Pham,
Duc Truong Pham
School of Mechanical Engineering,
e-mail: d.t.pham@bham.ac.uk
University of Birmingham
,Edgbaston
,Birmingham B15 2TT
, UK
e-mail: d.t.pham@bham.ac.uk
Search for other works by this author on:
Chunqian Ji
Chunqian Ji
School of Mechanical Engineering,
e-mail: c.ji@bham.ac.uk
University of Birmingham
,Edgbaston
,Birmingham B15 2TT
, UK
e-mail: c.ji@bham.ac.uk
Search for other works by this author on:
Wenjun Xu
School of Information Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
Key Laboratory of Fiber Optic Sensing
Technology and Information Processing,
e-mail: xuwenjun@whut.edu.cn
Technology and Information Processing,
Ministry of Education
,122 Luoshi Road
,Wuhan 430070
, China
e-mail: xuwenjun@whut.edu.cn
Jiajia Yu
School of Mechanical
and Electronic Engineering,
and Electronic Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
Key Laboratory of Fiber Optic Sensing
Technology and Information Processing,
e-mail: yujj1991@126.com
Technology and Information Processing,
Ministry of Education
,Wuhan 430070
, China
e-mail: yujj1991@126.com
Zude Zhou
School of Information Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
School of Mechanical
and Electronic Engineering,
e-mail: zudezhou@whut.edu.cn
and Electronic Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
e-mail: zudezhou@whut.edu.cn
Yongquan Xie
School of Information Engineering,
Wuhan University of Technology
,Wuhan 430070
, China
Key Laboratory of Fiber Optic Sensing
Technology and Information Processing,
e-mail: xyqwhut0728@163.com
Technology and Information Processing,
Ministry of Education
,122 Luoshi Road
,Wuhan 430070
, China
e-mail: xyqwhut0728@163.com
Duc Truong Pham
School of Mechanical Engineering,
e-mail: d.t.pham@bham.ac.uk
University of Birmingham
,Edgbaston
,Birmingham B15 2TT
, UK
e-mail: d.t.pham@bham.ac.uk
Chunqian Ji
School of Mechanical Engineering,
e-mail: c.ji@bham.ac.uk
University of Birmingham
,Edgbaston
,Birmingham B15 2TT
, UK
e-mail: c.ji@bham.ac.uk
1Corresponding author.
Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received October 15, 2014; final manuscript received March 7, 2015; published online July 8, 2015. Assoc. Editor: Xun Xu.
J. Manuf. Sci. Eng. Aug 2015, 137(4): 040907 (14 pages)
Published Online: August 1, 2015
Article history
Received:
October 15, 2014
Revision Received:
March 7, 2015
Online:
July 8, 2015
Citation
Xu, W., Yu, J., Zhou, Z., Xie, Y., Pham, D. T., and Ji, C. (August 1, 2015). "Dynamic Modeling of Manufacturing Equipment Capability Using Condition Information in Cloud Manufacturing." ASME. J. Manuf. Sci. Eng. August 2015; 137(4): 040907. https://doi.org/10.1115/1.4030079
Download citation file:
Get Email Alerts
Special Issue on the State-of-the-Art in Japanese Manufacturing Research
J. Manuf. Sci. Eng
A Review of Advanced Roll-to-Roll Manufacturing: System Modeling and Control
J. Manuf. Sci. Eng (April 2025)
Related Articles
Special Issue: Data Science-Enhanced Manufacturing
J. Manuf. Sci. Eng (October,2017)
Cloud-Based Parallel Machine Learning for Tool Wear Prediction
J. Manuf. Sci. Eng (April,2018)
Digital Twins: Review and Challenges
J. Comput. Inf. Sci. Eng (June,2021)
A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests
J. Manuf. Sci. Eng (July,2017)
Related Proceedings Papers
Related Chapters
Quality Systems and Standards
Metrology and Instrumentation: Practical Applications for Engineering and Manufacturing
Fundamentals of Computer-Integrated Manufacturing
Manufacturing Engineering: Principles for Optimization, Third Edition
Computer-Aided Process Planning and Data Collection
Manufacturing Engineering: Principles for Optimization, Third Edition