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.

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.

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.

INTEGRATION OF REAL-TIME CONTROL SIMULATION TO A VIRTUAL MANUFACTURING ENVIRONMENT

2002 ◽  
Vol 01 (01) ◽  
pp. 67-87 ◽  
Author(s):  
BYUNG-KWON MIN ◽  
ZHENGDONG HUANG ◽  
ZBIGNIEW J. PASEK ◽  
DEREK YIP-HOI ◽  
FORBES HUSTED ◽  
...  
Keyword(s):  
Machine Tool ◽  
Real Time ◽  
Machine Tools ◽  
Manufacturing Systems ◽  
Early Stage ◽  
Virtual Manufacturing ◽  
System Level ◽  
Manufacturing Environment ◽  
Manufacturing Environments ◽  
Virtual Manufacturing Environment

This paper presents a new integrated approach for simulation developed to improve the accuracy of virtual manufacturing environments. While machine tool simulation and virtual manufacturing for factory simulation have been frequently used in early stage plant development, each of these technique has been researched and implemented separately. This paper focuses on the utilization of real-time simulation of machine tools or active axes in manufacturing systems and integration of this simulation capability with virtual manufacturing environments. Machine-level simulation results are generated in real-time with a real machine tool controller and are fed to a virtual manufacturing environment. To integrate these two simulation techniques, system-level software is utilized as a communication platform. This system-level software was originally developed to control and configure whole manufacturing systems. The method has been successfully implemented within a testbed with full-scale machine tools. The results demonstrate that the proposed method advances the virtual manufacturing environments toward improved accuracy of factory level simulation, reduced effort for modeling and expanded functionality of machine-level simulations.

Resource Virtualization Model in Cloud Manufacturing

2010 ◽  
Vol 143-144 ◽  
pp. 1250-1253 ◽  
Author(s):  
Lei Wu
Keyword(s):  
Resource Sharing ◽  
Cloud Manufacturing ◽  
Application Layer ◽  
Resource Virtualization ◽  
Service Oriented ◽  
Model Cloud ◽  
Manufacturing Resources ◽  
Support Resource ◽  
Future Work ◽  
Manufacturing Problems

To solve more complex manufacturing problems and perform larger scale collaborative manufacturing, a new service-oriented networked manufacturing model—Cloud Manufacturing is presented. The paper presents a resource virtualization model to support resource sharing in cloud manufacturing environment. It can be decomposed into four layers: manufacturing resources layer, concrete web service layer, logical service layer and application layer. The relationships of every layer are discussed in detail. At last, we make a conclusion and put forward the future work.

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.

scholarly journals Building Innovative Service Composition Based on Two-Way Selection in Cloud Manufacturing Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Jinhui Zhao ◽  
Muzi Li ◽  
Yu Zhou ◽  
Peichong Wang
Keyword(s):  
Prospect Theory ◽  
Service Composition ◽  
Manufacturing Industry ◽  
Service Providers ◽  
Cloud Manufacturing ◽  
Reference Points ◽  
Uncertain Information ◽  
Manufacturing Environment ◽  
Teaching Learning ◽  
Gains And Losses

In the cloud manufacturing environment, innovative service composition is an important way to improve the capability and efficiency of resource integration and realize the upgrading and transformational upgrade of the manufacturing industry. In order to build a stable innovative service composition, we propose a novel composite model, which uses two-way selection according to their cooperation to recommend the most suitable partners. Firstly, a rough number is applied to quantify the semantic evaluation. Using the expectation of cooperative condition as reference points, prospect theory is then applied to calculate the cooperative desires for both sides based on participants’ psychological attitudes toward gains and losses. Next, the cooperative desires are used to establish the two-way selection model of innovative service composition. The solution is determined by using an improved teaching-learning-based optimization algorithm. Compared with traditional combined methods in the cloud manufacturing environment, the proposed model fully considers the long-neglected needs and interests of service providers. Prospect theory takes psychological expectations and varying attitudes of decision makers towards gains and losses into account. Moreover, an interval rough number is used to better preserve the uncertain information during semantic quantification. Experimental results verify the applicability and effectiveness of the proposed method.

scholarly journals A Smart Cloud-Based System for the WEEE Recovery/Recycling

2014 ◽  
Author(s):  
Xi Vincent Wang ◽  
Brenda N. Lopez N. ◽  
Lihui Wang ◽  
Jinhui Li ◽  
Winifred Ijomah
Keyword(s):  
Manufacturing Systems ◽  
Service Oriented Architecture ◽  
Intelligent System ◽  
Hazardous Materials ◽  
Cloud Manufacturing ◽  
Data Management System ◽  
Manufacturing Processes ◽  
Component Level ◽  
Recovery System ◽  
Service Oriented

Waste Electrical and Electronic Equipment (WEEE) is both valuable and harmful since it contains a large number of profitable and hazardous materials and elements at the same time. At component level, many parts of the discarded equipment are still functional and recoverable. Thus it is necessary to develop a distributed and intelligent system to support WEEE recovery and recycling. In recent years, the Cloud concept has gained increasing popularity since it provides a service-oriented architecture that integrates various resources over the network. Cloud Manufacturing systems are proposed world-wide to support operational manufacturing processes. In this research, Cloud Manufacturing is further extended to the WEEE recovery and recycling context. A Cloud-based WEEE Recovery system is developed to provide modularized recovery services on the Cloud. A data management system is developed as well, which maintains the knowledge throughout the product lifecycle. A product tracking mechanism is also proposed with the help of the Quick Respond code method.

Production as a Service: Optimizing Utilization in Manufacturing Systems

2016 ◽  
Author(s):  
Matthew Porter ◽  
Vikram Raghavan ◽  
Yikai Lin ◽  
Z. Morley Mao ◽  
Kira Barton ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Theoretical Work ◽  
Small Companies ◽  
Efficient Manner ◽  
Service Oriented Architectures ◽  
Service Oriented ◽  
Manufacturing Resources ◽  
Industrial Use ◽  
Service Framework

While advances in technology have greatly improved the process of mass production, producing small batches or one-offs in an efficient manner has remained challenging for the manufacturing industry. Additionally, in both large and small companies, there are often available manufacturing resources that sit idle between projects. In this paper we present a Production as a Service framework for providing manufacturing options to designers of new products based on available manufacturing resources. The designed framework aims to bridge the gap between the theoretical work that has been done on Service Oriented Architectures in manufacturing, and what is required for implementation. An industrial use case is provided as an example of the framework.

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