Virtualization of Manufacturing Resources in Cloud Manufacturing Environment

2019 ◽  
Author(s):  
Zhang Zhe ◽  
Chen You-ling ◽  
Lyu Song-yang
Keyword(s):  
Cloud Manufacturing ◽  
Manufacturing Environment ◽  
Manufacturing Resources

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.

scholarly journals Optimized Configuration of Manufacturing Resources for Middle and Lower Batch Customization Enterprises in Cloud Manufacturing Environment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yinyun Yu ◽  
Wei Xu
Keyword(s):  
Customer Satisfaction ◽  
Manufacturing Systems ◽  
Programming Model ◽  
Model Simulation ◽  
Cloud Manufacturing ◽  
Economic Benefits ◽  
Optimal Configuration ◽  
Manufacturing Environment ◽  
Kano Model ◽  
Manufacturing Resources

The optimal configuration of manufacturing resources in the cloud manufacturing environment has always been the focus of research on various advanced manufacturing systems. Aiming at the problem of manufacturing resources optimization configuration for middle and lower batch customization enterprises in cloud manufacturing environment, this paper gives a bi-level programming model for manufacturing resources optimization configuration in cloud manufacturing environment which fully considers customer satisfaction and enterprise customization economic benefits. The method firstly identifies the relationship between customer demands and customer satisfaction through questionnaires and quantifies the Kano model effectively. Then, it uses Quality Function Deployment (QFD) to transform customer demand characteristics into engineering characteristics and integrates the qualitative and quantitative results of the Kano model. Next, the method establishes enterprise economic benefits function according to the factors of order quantity and input cost. Furthermore, a comprehensive nonlinear bi-level programming model is established based on cost, time, and quality constraints. The model is solved by intelligent algorithm. Finally, the validity and feasibility of the model are verified by model simulation of actual orders of an enterprise. This method effectively realizes the optimal configuration of manufacturing resources in the cloud manufacturing environment, while maximizing the interests of both suppliers and demanders.

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).

Trust Model Based on Feedback Evaluation in Cloud Manufacturing Environment

2011 ◽  
Vol 308-310 ◽  
pp. 1740-1745 ◽  
Author(s):  
Xiao Lan Xie ◽  
Liang Liu ◽  
Ying Zhong Cao
Keyword(s):  
Cloud Manufacturing ◽  
Trust Model ◽  
Human Society ◽  
Manufacturing Environment ◽  
Trust Mechanism ◽  
Model Based ◽  
Service Behavior ◽  
Relationship Of ◽  
Dynamic Adaptability ◽  
Feedback Evaluation

Aiming at the existing trust issues under manufacturing environment. This paper proposes a trust model based on feedback evaluation, TMBFCM, from the characteristics of human of trust relationship of human society. The model proposed a set of evaluation indicators of cloud manufacturing services properties, introduced the dynamic trust mechanism for attenuation by time,established the service which cloud manufacturing services providers provided and the feedback evaluation and incentive mechanism given by the user of cloud manufacturing service, improved the dynamic adaptability of the model. The results show that, compared with the existing trust model, the evaluation results are closer to the true service behavior of cloud manufacturing services provider, it can resist all kinds of malicious attacks acts effectively, demonstrated good robustness and recognition.

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.

Cloud Manufacturing Resource Management Based on Metadata

2015 ◽  
Author(s):  
Chun Zhao ◽  
Lin Zhang ◽  
Xuesong Zhang ◽  
Liang Zhang
Keyword(s):  
Resource Management ◽  
Cloud Manufacturing ◽  
State Monitoring ◽  
Knowledge Resources ◽  
Centralized Management ◽  
Service Oriented ◽  
Manufacturing Resources ◽  
Resource Data ◽  
Manufacturing Platform ◽  
Management Approaches

Centralized management and sharing of manufacturing resources is one of the important functions of cloud manufacturing platform. There are many kinds of manufacturing resources, centralized management, optimized scheduling, quick searching for various manufacturing resources become important issues in a cloud manufacturing platform. This paper presents a resource management model based on metadata to realize the access and unified management of the hardware resources, software resources and knowledge resources. Two management approaches respectively for static and dynamic resource data are introduced to realize resource state monitoring and real-time information collecting. On this basis, the relationship between static and dynamic data is determined and service-oriented of resources is realized.

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