Research of Resource Virtualization Technology Based on Cloud Manufacturing

Li, Chun Quan; Hu, Chun Yang; Wang, Yan Wei

doi:10.4028/www.scientific.net/amr.201-203.681

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…At present, most manufacturing companies resort to intelligent methods (cloud manufacturing, cloud service, Internet of Things, etc.) to optimize the production and processing scheduling of single-piece customized products and obtain real-time information on production scheduling and logistics through the cloud manufacturing platform [6][7][8][9][10][11]. Production and processing planning, as the core of production scheduling, is the foundation for the optimal processing and rational resource allocation of single-piece products.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Intelligent Workshop Control Based on the Improved Group Leadership Optimization Algorithm

Xue¹,

Jiang²,

Wei³

et al. 2018

Int. j. simul. model.

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This paper takes the existing optimized single product production scheduling scheme as the cloud service resource, and the production planning scheme for the product to be processed as the request task, and then subjects the two to semantic search and matching to generate a set of optimal production planning schemes. Then this paper innovatively takes the minimum production and processing cost, processing time, equipment state and minimum transport distance in product processing as the objective functions, and uses the penalty function to establish the fitness function to constrain the group leader optimization algorithm. After that, the proposed improved group leader optimization algorithm (GLOA) is used to screen the generated scheme set, and finally the optimal intelligent workshop control and scheduling scheme is obtained. The simulation results show that the proposed GLOA algorithm achieves a good convergence and is well adaptable. The research conclusions can provide theoretical reference for the intelligent workshop control and scheduling in single product manufacturing.

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Section: Introductionmentioning

confidence: 99%

Optimization of the Intelligent Workshop Control Based on the Improved Group Leadership Optimization Algorithm

Xue¹,

Jiang²,

Wei³

et al. 2018

Int. j. simul. model.

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“…The emergence of cloud computing technology provides a new service platform with integrated, open, virtual and autonomous characteristics [2] which can effectively solve the problem of resource sharing and collaboration in the field of product diversification in the current manufacturing field. Based on cloud computing technology, the design and manufacturing and application system's support space spread from a single enterprise to the group, and then to the whole society [3], leading to the formation of private cloud or public cloud, in the product platform development process of product design, simulation, testing and other aspects of the application need a large number of data and software resources, so the reasonable allocation and full use of the massive data and software resources is a core issue of the product design cloud service [4].…”

Section: Research Backgroundmentioning

confidence: 99%

Construction of the Integrated Computer-Aided Design Platform of Hydraulic Pressure Support

Hui‐min¹,

Li²,

Tan³

2015

Proceedings of the 3rd International Conference on Mechanical Engineering and Intelligent Systems (ICMEIS 2015)

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Abstract. As a key device to coal mining, the hydraulic pressure support is important for the safety of coal mine. Currently, most of design software for hydraulic pressure support are stand-alone version and only capable of fulfilling partial design work. They have been used for a long time and lacked software maintenance, moreover, which use different development languages and database, structure of data table. Current using software become networking and integration for purpose, and also for the requirement of Zhengzhou coal mine machinery group co.,ltd, utilizing cloud technology, specific 10 design software is SaaS and networking, which are in order to build the overall design platform of hydraulic pressure support. According to the requirement of company designing accessories, a visual design platform for accessories of hydraulic pressure support based on B/S structure is presented, plus collaborates with overall design platform as one-the integrated computer-aided design platform of hydraulic pressure support. Finally, the feasibility and validity of the presented method is demonstrated.

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A state-of-the-art survey of cloud manufacturing

2014

International Journal of Computer Integrated Manufacturing

211

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Given the complexity and heterogeneity in Cloud computing scenarios, the mod-eling approach has widely been employed to investigate and analyze the energy consumption of Cloud applications, by abstracting real-world objects and processes that are difficult to observe or understand directly. It is clear that the abstraction sacrifices, and usually does not need, the complete reflection of the reality to be modeled. Consequently, current energy consumption models vary in terms of purposes, assumptions, application characteristics and environmental conditions, with possible overlaps between different research works. There-Email addresses: zheng.li@eit.lth.se (Zheng Li), selome@cs.umu.se (Selome Tesfatsion), saeed.bastani@eit.lth.se (Saeed Bastani), ahmeda@cs.umu.se (Ahmed Ali-Eldin), raj.ranjan@ncl.ac.uk (Rajiv Ranjan), fore, it would be necessary and valuable to reveal the state-of-the-art of the existing modeling efforts, so as to weave different models together to facilitate comprehending and further investigating application energy consumption in the Cloud domain. By systematically selecting, assessing and synthesizing 76 relevant studies, we rationalized and organized over 30 energy consumption models with unified notations. To help investigate the existing models and facilitate future modeling work, we deconstructed the runtime execution and deployment environment of Cloud applications, and identified 18 environmental factors and 12 workload factors that would be influential on the energy consumption. In particular, there are complicated trade-offs and even debates when dealing with the combinational impacts of multiple factors.

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Research of Resource Virtualization Technology Based on Cloud Manufacturing

Cited by 4 publications

References 2 publications

Optimization of the Intelligent Workshop Control Based on the Improved Group Leadership Optimization Algorithm

Optimization of the Intelligent Workshop Control Based on the Improved Group Leadership Optimization Algorithm

Construction of the Integrated Computer-Aided Design Platform of Hydraulic Pressure Support

A state-of-the-art survey of cloud manufacturing

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