Building a Semantic-Rich Service-Oriented Manufacturing Environment

2005 ◽  
pp. 623-632 ◽  
Author(s):  
Zhonghua Yang ◽  
Jing-Bing Zhang ◽  
Robert Gay ◽  
Liqun Zhuang ◽  
Hui Mien Lee
Keyword(s):  
Manufacturing Environment ◽  
Service Oriented

Building a Semantic-Rich Service-Oriented Manufacturing Environment

2007 ◽  
Vol 2 (3) ◽  
pp. 53-64 ◽  
Author(s):  
Zhonghua Yang ◽  
Jing Bing Zhang ◽  
Rober Gay ◽  
Liquin Zhuang ◽  
Hui Mien Lee
Keyword(s):  
Manufacturing Environment ◽  
Service Oriented

Analysis of Service-Oriented Manufacturing Network Based on Complex Network

2012 ◽  
Vol 271-272 ◽  
pp. 401-405
Author(s):  
Ji Li ◽  
Rong Mo ◽  
Ling Ling Liu
Keyword(s):  
Complex Network ◽  
Clustering Coefficient ◽  
Manufacturing Environment ◽  
The Status ◽  
Service Oriented ◽  
Manufacturing Network ◽  
The Relationship

Aiming at the description and analysis of service-oriented manufacturing network, the paper gives its definition on the basis of analyzing the relationship between enterprises and service. Besides, it not only defines, calculates and analyzes the statistic characteristics such as node strength and clustering coefficient by the complex weighted theory, but reveals the status of enterprise and correlations in the manufacturing environment of oriented service. This study can not only provide basis for the construction and management of service-oriented manufacturing network, but for search and grouping of collaborative partners.

Computational Trust in Cloud Manufacturing

2013 ◽  
Vol 774-776 ◽  
pp. 1908-1913 ◽  
Author(s):  
Lu Gao ◽  
Quan Liu ◽  
Ping Lou
Keyword(s):  
Manufacturing Systems ◽  
Service Providers ◽  
Cloud Manufacturing ◽  
Trust Model ◽  
Virtual Manufacturing ◽  
Manufacturing Environment ◽  
Collaborative Relationships ◽  
Computational Trust ◽  
Service Oriented ◽  
Manufacturing Resources

Cloud manufacturing is a new kind of advanced service-oriented network manufacturing paradigm. There are two kinds of nodes in this network manufacturing environment: manufacturing service nodes (service providers) encapsulated by manufacturing resources and task nodes (service customers). One of the bases of building up the collaborative relationships between customers and providers in cloud manufacturing environment is their reciprocal trust. However, vicious, mendacious, and inveracious information makes it quite difficult for customers to find reliable and high-quality providers to form virtual manufacturing systems for efficiently responding to market demands in cloud manufacturing environment, viz. service consumers often have insufficient information on service providers. The trustworthy network manufacturing environment is a prerequisite to implementation of cloud manufacturing. In this paper the notion of human trust is extended to the cloud manufacturing. A computational trust model which combines the direct computational reliability and the computational reputation is presented, and the simulating result confirms it valid.

Virtual Function Block Mechanism in the Cloud Manufacturing Environment

2013 ◽  
Vol 694-697 ◽  
pp. 2438-2441 ◽  
Author(s):  
Xi Vincent Wang ◽  
Xun W Xu
Keyword(s):  
Service Oriented Architecture ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Manufacturing Environment ◽  
Function Block ◽  
Integration Mechanism ◽  
Data Flows ◽  
Service Oriented ◽  
Function Blocks ◽  
Block Based

CManufacturing is a new manufacturing model that has evolved from Service-Oriented Architecture, networked manufacturing and CComputing. It provides intelligent, interoperable and distributed manufacturing model for the industry. This paper introduces a resource integration mechanism in the Cloud Manufacturing environment. Function Block technology is discussed from the Cloud Manufacturing perspective in detail. Next, a novel integration mechanism is proposed, namely the Virtual Function Block. Based on physical Function Blocks and software agents, Virtual Function Blocks are able to manipulate and integrate manufacturing resources via event states and data flows. During implementation, Creo Parametric was integrated as a Cloud Service with the help of VFBs to evaluate the mechanism.

Building a Semantic-Rich Service-Oriented Manufacturing Environment

2011 ◽  
pp. 255-265
Author(s):  
Zhonghua Yang ◽  
Jing Bing Zhang ◽  
Robert Gay ◽  
Liqun Zhuang
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Manufacturing Sector ◽  
Service Orientation ◽  
Enterprise Integration ◽  
Manufacturing Environment ◽  
Integration Architecture ◽  
Service Oriented ◽  
Semantic Markup ◽  
Semantic Web Service Composition

Service-orientation has emerged as a new promising paradigm for enterprise integration in the manufacturing sector. In this paper, we focus on the approach and technologies for constructing a service oriented manufacturing environment. The service orientation is achieved via virtualization in which every thing, including machines, equipments, devices, various data sources, applications, and processes, are virtualized as standard-based Web services. The virtualization approach is based on the emerging Web Services Resource Framework (WS-RF). A case study of virtualizing an AGV system using WS-RF is described. The use of Semantic Web Services technologies to enhance manufacturing Web services for a semantic-rich environment is discussed, focusing on OWL-S for semantic markup of manufacturing Web services and OWL for the development of ontologies in the manufacturing domain. An enterprise integration architecture enabled by Semantic Web service composition is also discussed.

Building a Semantic-Rich Service-Oriented Manufacturing Environment

2011 ◽  
Author(s):  
Zhonghua Yang ◽  
Jing Bing Zhang ◽  
Robert Gay ◽  
Liqun Zhuang
Keyword(s):  
Manufacturing Environment ◽  
Service Oriented

scholarly journals A Hierarchical Structure of Service-Oriented Manufacturing Mode

2011 ◽  
Vol 1 ◽  
pp. 145-149
Author(s):  
Ming Shun Yang ◽  
Xin Qin Gao ◽  
Yong Liu ◽  
Yan Li
Keyword(s):  
Conceptual Model ◽  
Hierarchical Structure ◽  
Hierarchical Architecture ◽  
Manufacturing Environment ◽  
Manufacturing Enterprises ◽  
Key Technologies ◽  
Service Oriented ◽  
Manufacturing Mode

With fiercer competition and more complex manufacturing environment, as a new manufacturing mode, service-oriented manufacture integrating manufacturing and service is used to mine new value source for manufacturing enterprises. The characteristics of the new manufacturing mode are analyzed, then a conceptual mode of the service-oriented manufacturing is concluded, and the features of the conceptual model are summarized from three different stages of the upstream, midstream and downstream. Based on these, a hierarchical architecture of service-oriented manufacturing mode is presented, and the different layers are described, which will provide good guideline to study the key technologies of service-oriented manufacturing.

Scanning-probe microscope analysis of optical thin films: A new analytical tool in a manufacturing environment

1994 ◽  
Vol 52 ◽  
pp. 1068-1069
Author(s):  
S. P. Sapers ◽  
R. Clark ◽  
P. Somerville
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Thermal Control ◽  
Scanning Probe Microscope ◽  
Scanning Probe ◽  
List Type ◽  
Manufacturing Environment ◽  
Physical Measurements ◽  
Probe Microscope

OCLI is a leading manufacturer of thin films for optical and thermal control applications. The determination of thin film and substrate topography can be a powerful way to obtain information for deposition process design and control, and about the final thin film device properties. At OCLI we use a scanning probe microscope (SPM) in the analytical lab to obtain qualitative and quantitative data about thin film and substrate surfaces for applications in production and research and development. This manufacturing environment requires a rapid response, and a large degree of flexibility, which poses special challenges for this emerging technology. The types of information the SPM provides can be broken into three categories:(1)Imaging of surface topography for visualization purposes, especially for samples that are not SEM compatible due to size or material constraints;(2)Examination of sample surface features to make physical measurements such as surface roughness, lateral feature spacing, grain size, and surface area;(3)Determination of physical properties such as surface compliance, i.e. “hardness”, surface frictional forces, surface electrical properties.

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