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.

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.

Modeling and Matching Technology of Manufacturing Resources Based on Semantic

2012 ◽  
Vol 586 ◽  
pp. 288-294 ◽  
Author(s):  
Bo Gao ◽  
Yan Yan ◽  
Fa Ping Zhang
Keyword(s):  
Semantic Similarity ◽  
Cloud Manufacturing ◽  
Modeling Method ◽  
Matching Problems ◽  
Mapping Rules ◽  
Capacity Evaluation ◽  
Manufacturing Resources ◽  
Manufacturing Mode ◽  
Manufacturing Feature

To solve manufacturing resources heterogeneous description and matching problems on cloud manufacturing mode，manufacturing resources modeling and matching technology based on semantic was proposed. The modeling method based on manufacturing feature for manufacturing resources by ontology semantic was presented. Manufacturing resources based on manufacturing feature were encapsulated as manufacturing capacity which can be catch with manufacturing feature of product by semantic similarity. Mapping rules were structured between feature of manufacturing capacity and manufacturing feature of products. Manufacturing capacity evaluation of enterprise was achieved. An application prototype with manufacturing resources modeling and matching based on manufacturing feature was developed.

An Optimal Allocation Method for Virtual Resource Considering Variable Metrics of Cloud Manufacturing Service

2015 ◽  
Author(s):  
Jin Cui ◽  
Lei Ren ◽  
Lin Zhang ◽  
Qiong Wu
Keyword(s):  
High Efficiency ◽  
Optimal Allocation ◽  
Pso Algorithm ◽  
Agile Manufacturing ◽  
Cloud Manufacturing ◽  
Virtual Manufacturing ◽  
Allocation Problem ◽  
Allocation Model ◽  
Manufacturing Resources ◽  
Optimization Allocation

Based on the concept of Cloud Computing, a new service-oriented, high efficiency low consumption, knowledge-based, and intelligent networked agile manufacturing model Cloud Manufacturing (CMfg) has been proposed recently. The manufacturing resources optimization allocation model (MROAM) is one of the core parts for implementing CMfg. In this paper, a new MROAM is proposed in the background of CMfg system. In this model, variable metrics such as a variety of evaluation indicators for different types of manufacturing services are taken into account. In addition, time, cost, virtual manufacturing resource interface, and so on constrains are considered as well. To solve the manufacturing resources optimization allocation problem, a new improved intelligent algorithm named Kmeans-PSO was presented by combining the particle swarm optimization (PSO) algorithm and the K-means clustering. Experiment results demonstrate the effectiveness of the designed algorithm and show Kmeans-PSO’s high performances for addressing the manufacturing resources allocation problem compared with other intelligent algorithms.

Cloud Logistics Path Optimization Based on Ant Colony Algorithm

2014 ◽  
Vol 722 ◽  
pp. 442-445
Author(s):  
Zhi Gao Chen
Keyword(s):  
Ant Colony Algorithm ◽  
Cloud Manufacturing ◽  
Ant Algorithm ◽  
Composite Service ◽  
Execution Path ◽  
Logistics Mode ◽  
Manufacturing Service Composition ◽  
Manufacturing Resources ◽  
Manufacturing Mode ◽  
Made In

Cloud Manufacturing is developed in the cloud computing, which is based on the idea of "Made in service" recently. Cloud manufacturing mode connect all sorts of manufacturing resources and capability together and form standard manufacturing services which customers can obtain according to their demand at any time. Logistics mode should coincide with manufacturing mode for the certain correlation between logistics and manufacturing process,so the production and development of cloud manufacturing mode had the logistics mode reformed. In this paper we present a cloud manufacturing service composition method considering execution reliability based on ant algorithm, to optimize the use of composite service execution path to save the costs.

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.

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.

Multi-Tenant Access Control Model for Cloud Manufacturing

2017 ◽  
Author(s):  
Qianwen Chen ◽  
Zude Zhou ◽  
Xiaomei Zhang ◽  
Xuemei Jiang
Keyword(s):  
Access Control ◽  
Cloud Manufacturing ◽  
Control Model ◽  
Utilization Efficiency ◽  
Access Control Model ◽  
On Demand ◽  
Manufacturing Resources ◽  
Manufacturing Platform ◽  
Manufacturing Mode ◽  
Demand Service

Cloud manufacturing is a new service-oriented networked manufacturing mode based on the concept of “Manufacture as a Service” and achieves the sharing of manufacturing resources and manufacturing capacity. Multi-tenancy technology can improve utilization efficiency of manufacturing resources and ensure information security among tenants, enabling users to share the cloud manufacturing resources better. To execute this new mode, isolation access and on-demand services are indispensable. However, the traditional access control model cannot satisfy the demands of multi-tenant environment on cloud manufacturing platform. To solve the demands in such an environment, a model named Multi-Tenant Access Control Model for Cloud Manufacturing (CM-MTAC) is proposed. Based on cloud manufacturing architecture, we build a hierarchical cloud manufacturing access control architecture combining multi-tenancy. Considering the demands under this condition, the elements of cloud manufacturing access control model and the relationships between them are redefined by extending the ABAC model. Then multi-tenancy authorization framework is proposed and XACML language is used to describe the policy to provide our model with on-demand service, isolation access and inter-tenant collaboration. Finally, we develop this model into the cloud manufacturing monitoring platform. Results show that our model, compared with traditional models, has a better performance of on-demand service, isolation access and inter-tenant cooperation under the environment of cloud manufacturing.

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).

An OSGi-Based Adaptation Access of Machine Tools in the Cloud Manufacturing Environment

2021 ◽  
Author(s):  
Xiaobin Li ◽  
Chao Yin
Keyword(s):  
Information Acquisition ◽  
Machine Tools ◽  
Universal Access ◽  
Cloud Manufacturing ◽  
Manufacturing Environment ◽  
Access Method ◽  
Manufacturing Enterprises ◽  
Cloud Application ◽  
Key Enabling Technologies ◽  
Manufacturing Mode

Abstract Machine tools (MTs) are the core manufacturing resources for discrete manufacturing enterprises. In the cloud manufacturing environment, MTs are massive, heterogeneous, widely dispersed and highly autonomous, which makes it difficult for cloud manufacturing mode to be deeply applied to support the networked collaboration operation among manufacturing enterprises. Realizing universal access and cloud application of various MTs is an essential prerequisite to solve the above problem. In this paper, an OSGi-based adaptation access method of MTs is proposed. First, the MTs information description model in the cloud manufacturing environment is built. Then, an OSGi-based adaptation access framework of MTs is constructed, and key enabling technologies, including machine tool information acquisition and processing, Bundle and Subsystem construction, are studied. Finally, an application case is conducted to verify the effectiveness and feasibility of the proposed method.

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