Study on Community Structures in Manufacturing Grid and the Algorithm for Community Partition of its Resource Nodes

2014 ◽  
Vol 526 ◽  
pp. 222-229 ◽  
Author(s):  
Yong Yin ◽  
Yu Li ◽  
Chao Yong Zhang
Keyword(s):  
Community Structure ◽  
Complex Network ◽  
Resource Sharing ◽  
Collaborative Design ◽  
Manufacturing Grid ◽  
Network Community ◽  
Design And Manufacturing ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Set Up

The Manufacturing Grid supplies a public platform for global resource sharing, collaborative design and manufacturing; its resource nodes constitute a complex network. Community partition of the complex network composed of the manufacturing resource nodes may be of some benefit for the sharing of manufacturing resources efficiently. In this paper, the resource nodes in the Manufacturing Grid are treated as the nodes of the complex network and the node-to-node link as its edges or arcs. The features of the resource nodes are analyzed based on which a model of the complex network composed of resource nodes in the Manufacturing Grid is set up. The nature phenomenon of the community structure in the complex network of manufacturing resource nodes is described according to the division of the manufacturing task into subtasks. Referring to Newmans idea, a criterion to evaluate the partition of community structure is discussed. Then, an improved algorithm based on Newman's Fast Algorithm is put forward to partition the community. The algorithm fully considers the characteristics of the direction and weight in the complex network for manufacturing resource nodes. Examples show that the algorithm presented in the paper can partition the community with favorable results.

Deep learning and complex network theory based analysis on socialized manufacturing resources utilisations and an application case study

2021 ◽  
pp. 1063293X2110031
Author(s):  
Maolin Yang ◽  
Auwal H Abubakar ◽  
Pingyu Jiang
Keyword(s):  
Deep Learning ◽  
Complex Network ◽  
Network Models ◽  
Neural Network Models ◽  
Complex Network Theory ◽  
New Type ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Resource Characteristics

Social manufacturing is characterized by its capability of utilizing socialized manufacturing resources to achieve value adding. Recently, a new type of social manufacturing pattern emerges and shows potential for core factories to improve their limited manufacturing capabilities by utilizing the resources from outside socialized manufacturing resource communities. However, the core factories need to analyze the resource characteristics of the socialized resource communities before making operation plans, and this is challenging due to the unaffiliated and self-driven characteristics of the resource providers in socialized resource communities. In this paper, a deep learning and complex network based approach is established to address this challenge by using socialized designer community for demonstration. Firstly, convolutional neural network models are trained to identify the design resource characteristics of each socialized designer in designer community according to the interaction texts posted by the socialized designer on internet platforms. During the process, an iterative dataset labelling method is established to reduce the time cost for training set labelling. Secondly, complex networks are used to model the design resource characteristics of the community according to the resource characteristics of all the socialized designers in the community. Two real communities from RepRap 3D printer project are used as case study.

scholarly journals LIMITED RESOLUTION AND MULTIRESOLUTION METHODS IN COMPLEX NETWORK COMMUNITY DETECTION

2007 ◽  
Vol 07 (03) ◽  
pp. L209-L214 ◽  
Author(s):  
JUSSI M. KUMPULA ◽  
JARI SARAMÄKI ◽  
KIMMO KASKI ◽  
JÁNOS KERTÉSZ
Keyword(s):  
Simulated Annealing ◽  
Community Structure ◽  
Complex Network ◽  
Community Detection ◽  
Real World ◽  
Tuning Parameter ◽  
Challenging Problem ◽  
Resolution Limit ◽  
Network Community ◽  
Multiresolution Methods

Detecting community structure in real-world networks is a challenging problem. Recently, it has been shown that the resolution of methods based on optimizing a modularity measure or a corresponding energy is limited; communities with sizes below some threshold remain unresolved. One possibility to go around this problem is to vary the threshold by using a tuning parameter, and investigate the community structure at variable resolutions. Here, we analyze the resolution limit and multiresolution behavior for two different methods: a q-state Potts method proposed by Reichard and Bornholdt, and a recent multiresolution method by Arenas, Fernández, and Gómez. These methods are studied analytically, and applied to three test networks using simulated annealing.

Complex Network Based Modeling and Analysis of Resource Nodes for MG

2014 ◽  
Vol 619 ◽  
pp. 332-336 ◽  
Author(s):  
Yong Yin ◽  
Chao Yong Zhang ◽  
De Jun Chen
Keyword(s):  
Complex Network ◽  
Network Model ◽  
Element Model ◽  
Optimal Composition ◽  
Manufacturing Grid ◽  
Modeling And Analysis ◽  
Static Parameter ◽  
Scale Free ◽  
Manufacturing Resource ◽  
Synchronization Performance

Manufacturing Grid (MG) is one of the most promising manufacturing modes in recent years, which has been proved to be a complex network characterized with scale-free. In this paper, the resource nodes of MG are treated as the nodes of a network and the linkage among each node is treat as the edges or arcs, based on which a three-element model of G = ( V, E, R) is proposed, and a scene of the optimal composition strategy among the 50 candidate nodes aiming at task A is modeled. Next the static parameter of the degree for a resource node and the synchronization performance of the complex network model for the resource nodes are studied. Results of the paper can promote the management of the manufacturing resource nodes and improve the efficiency of sharing MG resources, so as to facilitate the application and popularization of MG.

Key Technologies of Digital Pre-Assembly in Networked Collaborative Design and Manufacturing

2012 ◽  
Vol 157-158 ◽  
pp. 171-174 ◽  
Author(s):  
Hui Fen Wang ◽  
Feng Qiang Nan ◽  
Ting Ting Liu
Keyword(s):  
Product Development ◽  
Collaborative Design ◽  
Manufacturing System ◽  
Assembly Model ◽  
Collaborative Product Development ◽  
Assembly Sequences ◽  
Key Technologies ◽  
Design And Manufacturing ◽  
Automatic Search ◽  
Set Up

According to the requirement of collaborative product development, a networked collaborative design and manufacturing system is put forward. A neuter digital assembly model which is independent from all kinds of the commercial CAD software is set up. The quick planning of the assembly sequences and the automatic search of the assembly dimension chain can be realized by the simulation.

The Selection of Manufacturing Grid Resources Node Based on the Model

2014 ◽  
Vol 926-930 ◽  
pp. 842-845 ◽  
Author(s):  
Fan Hua Hu ◽  
Hao You
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Clustering Coefficient ◽  
Manufacturing Grid ◽  
Intelligent Algorithm ◽  
Node Selection ◽  
Complex Network Theory ◽  
Manufacturing Resource ◽  
Grid Resources ◽  
Selection Of

The complex network model of the manufacturing grid was built based on complex network theory. Based on the model, the degree and its distribution, the mode dole, the average path length and clustering coefficient were studied. Taking an actual manufacturing task as example, the manufacturing resource node selection was performed integrated with the classical intelligent algorithm and the node selection performance is promoted. The research results are help to enhance the global optimization selection ability on the manufacturing resource node.

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