GetCM: A Vision of Cloud Manufacturing

2011 ◽  
Vol 213 ◽  
pp. 388-392 ◽  
Author(s):  
Jing Tao Zhou ◽  
Hai Cheng Yang ◽  
Ming Wei Wang ◽  
Shi Kai Jing ◽  
Rong Mo
Keyword(s):  
Large Scale ◽  
Cloud Manufacturing ◽  
Networked Manufacturing ◽  
Economic Aspects ◽  
Basic Principles ◽  
Dynamic Provisioning ◽  
On Demand ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Modern Manufacturing

Surviving in an increasing globalization, distribution and flexibility environment, modern manufacturing requires an extremely flexible, self-adaptive foundation capable of dynamic provisioning, coordinating and using infinite manufacturing resources available on demand over large-scale computer networks. In contrast to the conventional networked manufacturing approach, the cloud manufacturing vision (GetCM) introduced in this paper promises elasticity, flexibility and adaptability through the on-demand provisioning of manufacturing resources as a utility by reflecting the basic principles of cloud computing. The discussion is made from technological, functional, economic aspects to provide evidence of the benefits from GetCM in the context of networked manufacturing resource access, provision, sharing and coordination. A primary architecture for GetCM is introduced based on the analysis of key criteria in realizing the vision of a function for cloud manufacturing. Focuses of this paper are placed on the vision and the outline of GetCM architecture.

Study on the Multi-Granularity Virtualization of Manufacturing Resources

2013 ◽  
Author(s):  
Chunsheng Hu ◽  
Chengdong Xu ◽  
Xiaobo Cao ◽  
Pengfei Zhang
Keyword(s):  
Large Scale ◽  
Cloud Manufacturing ◽  
Virtual Manufacturing ◽  
Networked Manufacturing ◽  
Manufacturing Resources ◽  
Manufacturing Mode

As a new kind of networked manufacturing mode, Cloud Manufacturing needs to construct a large-scale virtual manufacturing resources pool firstly. For a reasonable and effective construction of the virtual manufacturing resources pool, the point of multi-granularity virtualization is proposed. Firstly, by analyzing the process of resources virtualization, the meanings of manufacturing resources, virtualization modeling and virtualization accessing are stated, and the relationships between them are illustrated; secondly, by analyzing the compositionality of resources, two resources categories are deduced; thirdly, the granularity factor, which have serious impacts on the resources-virtualization, resources-matching and resources-scheduling, are discussed; finally, a multi-granularity virtualization method of manufacturing resources is proposed.

Research on Mass Manufacturing Resource Sensory Data Management Based on Hadoop

2016 ◽  
Vol 693 ◽  
pp. 1880-1885 ◽  
Author(s):  
Kai Kai Su ◽  
Wen Sheng Xu ◽  
Jian Yong Li
Keyword(s):  
Distributed Storage ◽  
Cloud Manufacturing ◽  
Distributed File System ◽  
Service Platform ◽  
Sensory Data ◽  
Computing Model ◽  
Hadoop Distributed File System ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Management Method

Aiming at the management issue of mass sensory data from the manufacturing resources in cloud manufacturing, a management method for mass sensory data based on Hadoop is proposed. Firstly, characteristics of sensory data in cloud manufacturing are analyzed, meanings and advantages of Internet of Things and cloud computing are elaborated. Then the structure of the cloud manufacturing service platform is proposed based on Hadoop, the information model of manufacturing resources in cloud manufacturing is defined, and the data cloud in the cloud manufacturing service platform is designed. The distributed storage of mass sensory data is implemented and a universal distributed computing model of mass sensory data is established based on the characteristics of Hadoop Distributed File System (HDFS).

Design and Application of Comprehensive Evaluation System of Manufacturing Resource Deployment in Construction Machinery

2013 ◽  
Vol 694-697 ◽  
pp. 2404-2407 ◽  
Author(s):  
Ke Zhou ◽  
Xiao Dong Li
Keyword(s):  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Cloud Manufacturing ◽  
Construction Machinery ◽  
Evaluation Indexes ◽  
Enterprise Application ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
And Function ◽  
Resource Deployment

To save manufacturing resources in cloud manufacturing environment, a manufacturing resource deployment evaluation system in construction machinery was designed and applied. At first evaluation indexes of manufacturing resource deployment were analyzed. Then the architecture and function structure were designed, and the database were analyzed. And some technologies adopted in the system were introduced to ensure security, stability, and interoperability of the information. Feasibility and effectiveness of the system were verified by a enterprise application case.

Cloud Manufacturing Based on Cooperative Concept of SDN

2012 ◽  
Vol 482-484 ◽  
pp. 2424-2429 ◽  
Author(s):  
De Yi Tai ◽  
Fu Yuan Xu
Keyword(s):  
Cloud Computing ◽  
Supply And Demand ◽  
Cloud Manufacturing ◽  
Added Value ◽  
Three Dimension ◽  
New Paradigm ◽  
On Demand ◽  
Service Oriented ◽  
Manufacturing Resource

As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) was proposed to realize the added-value and on-demand use of manufacturing resource and ability. Compared with cloud computing, the complexity of CMfg cooperation was analyzed. Supply and demand network of enterprises with multifunction and opening characteristics (SDN) was introduced as a new paradigm of manufacturing cooperation. Dynamic, diversity, fully open and inclusive cooperation are the key concept of SDN. The CMfg cooperation based on SDN was analyzed, from three-dimension of lever, function and space. A model of cooperation-oriented CMfg was built. Resource-oriented, service-oriented and innovation-oriented cooperation were proposed to prompt the implementation and the platform building of CMfg, from the business cooperation perspective.

Multi-Hierarchy Relevance Model of Cloud Manufacturing Resource Based on OWL

2014 ◽  
Vol 635-637 ◽  
pp. 1861-1865
Author(s):  
Bai Gang Du ◽  
Jun Guo ◽  
Hong Tao Tang ◽  
Xi Xing Li
Keyword(s):  
Cloud Manufacturing ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Environmental Level ◽  
Relevance Model

Aiming at the diversity and heterogeneity of manufacturing resources in cloud manufacturing, the multi-hierarchy relevance model (MHRM) based on category and environmental level was proposed. Moreover, the OWL was used to describe the cloud manufacturing resources. Finally, cloud manufacturing resource ontology instance was built by Protégé.

scholarly journals A Bilayer Resource Model for Cloud Manufacturing Services

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Linan Zhu ◽  
Yanwei Zhao ◽  
Wanliang Wang
Keyword(s):  
Manufacturing Industry ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Service Description ◽  
Resource Model ◽  
Attribute Model ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Manufacturing Platform ◽  
Resource Service

Cloud Manufacturing and Cloud Service is currently one of the main directions of development in the manufacturing industry. Under the Cloud Manufacturing environment, the characteristics of publishing, updating, searching, and accessing manufacturing resources are massive, complex, heterogeneous, and so forth. A bilayer manufacturing resource model with separation of Cloud End and Cloud Manufacturing Platform is proposed in this paper. In Cloud End, manufacturing resources are divided into single resource and complex resource, and a basic data model of manufacturing resources oriented to enterprise interior is established to store the physical characteristics. In Cloud Manufacturing Platform, a resource service attribute model oriented to actual users is established to store the service characteristics. This model is described in detail and realized with stateful Web Service Description Language (WSDL) document. An example is provided for illustrating the implementation of the concept.

A Method for Multimedia Resources Management and Sharing in Cloud Manufacturing System

2014 ◽  
Vol 945-949 ◽  
pp. 3454-3457
Author(s):  
Zheng Hong Liu
Keyword(s):  
Cloud Computing ◽  
Manufacturing System ◽  
New Product ◽  
Cloud Manufacturing ◽  
Entire Life ◽  
Entire Life Cycle ◽  
Resources Management ◽  
On Demand ◽  
Multimedia Resources ◽  
Manufacturing Resources

In the entire life-cycle of manufacturing of a new product, a great number of multimedia resources are generated, which is belong to manufacturing resources too. How to manage and fully sharing these multimedia resources is a key research part for cloud manufacturing (CMfg), which is aim at realize the full sharing and on-demand use of various manufacturing resources. In this paper, after introduce the concept of cloud computing and cloud manufacturing, a cloud based multimedia resources management and sharing method is proposed, as well as is architecture.

Order-Oriented Manufacturing Resource Services Sharing of Building Material and Equipment Enterprise in Cloud Manufacturing

2013 ◽  
Vol 823 ◽  
pp. 565-571 ◽  
Author(s):  
Bai Gang Du ◽  
Shun Sheng Guo ◽  
Yi Bing Li ◽  
Jun Guo
Keyword(s):  
Resource Sharing ◽  
Building Material ◽  
Manufacturing Industry ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Remote Collaboration ◽  
Related Services ◽  
Service Oriented ◽  
Manufacturing Resource ◽  
Manufacturing Resources

The cloud manufacturing brings forward a new idea of manufacturing resource sharing with service-oriented. Recent advances in information technology, such as cloud computing, internet of things, make it easier for heterogeneous resources in different regions to remote collaboration in cloud manufacturing. To help improve the success of distributed manufacturing resource sharing for service provider and user in building material and equipment enterprise (BMEE), the order-oriented cloud service library (OCSL) and order-based model for shared manufacturing resources (OMSMR) are proposed after analysing the management features of manufacturing resources in BMEE. The OCSL gives a relationship description between task orders and related services. Moreover, a case study is undertaken to evaluate the proposed model. The model brings into manufacturing industry for manufacturing resource sharing with a number of benefits such as openness, integrity and traceability.

Part Features Oriented Optimizing of Manufacturing Resources for Cloud Manufacturing

2013 ◽  
Vol 432 ◽  
pp. 598-602
Author(s):  
Zhao Yang Dong ◽  
Lin Zhang
Keyword(s):  
Cloud Manufacturing ◽  
Processing Route ◽  
Executive Processing ◽  
Ontology Model ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Task Ontology ◽  
Intelligent Searching ◽  
The Relationship ◽  
Manufacturing Features

The research is targeted at the bottleneck technology of manufacturing resources optimizing configuration in cloud manufacturing, namely, the modeling of manufacturing resource and manufacturing task, the intelligent searching of manufacturing resource, and the optimizing of executive processing routes. Manufacturing resources are classified by manufacturing features. The framework of ontology concept is constructed, and the relationship among various concepts is made clear. Then the ontology model of manufacturing resources is constructed. The part features of manufacturing tasks are extracted, and the part features are expanded to include the information of manufacturing methods. Then the ontology model of manufacturing task is constructed. The concept tree method is adopted to compute the semantic similarity between manufacturing resource concept tree and manufacturing task concept tree, so to realize the mapping of manufacturing resource ontology to manufacturing task ontology, and the intelligent searching of manufacturing resources is accomplished. The best manufacturing resources are chosen from candidate resources for each job in processing route during the optimizing of executable processing routes. This problem belongs to a complicated multi objectives, multi choices, and multi constraints knapsack problem. A compromise based parallel multiple objective genetic algorithm is proposed to solve it. Finally, the compromised solution is obtained for the decision-maker.

Automatic Manufacturing Cloud Service Composition Based on AI Plan

2014 ◽  
Vol 513-517 ◽  
pp. 990-993 ◽  
Author(s):  
Pei Si Zhong ◽  
Shao Qi Zhu ◽  
De Jie Huang ◽  
Hai Liang Xin
Keyword(s):  
Service Composition ◽  
Large Scale ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Search Method ◽  
Added Value ◽  
Service Environment ◽  
Manufacturing Resources ◽  
Cloud Service Composition ◽  
Automatic Manufacturing

Manufacturing cloud service composition is the key way to improve the utilization of manufacturing resources and manufacturing capabilities, realize added value and efficiency of manufacturing resources and manufacturing capabilities. It has great significance on cloud manufacturing implementation and carry. Therefore, the paper presents automatic forwarding search method called AMCSC-HFS for manufacturing cloud service composition based on AI plan. The main purpose is to support meeting the actual need of large-scale and dynamic cloud manufacturing cloud service environment.

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