Open AccessInfluential node identification method of assembly system based on TOPSIS and Topology
Author(s) -
Bo Yuan,
Jian-e Chang,
Feng Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1605/1/012019
Subject(s) - topsis , weighting , ranking (information retrieval) , computer science , analytic hierarchy process , key (lock) , complex network , node (physics) , data mining , network topology , topology (electrical circuits) , artificial intelligence , operations research , engineering , computer network , medicine , computer security , electrical engineering , structural engineering , world wide web , radiology
In order to find the influential manufacturing resources in a complex assembly system, a topology model of a complex assembly system was constructed based on the complex network theory. Complex network evaluation indicators with different attributes were used to evaluate the network, and AHP subjective weight method was used to determine the subjective weights between different evaluation indicators. Then the CRITIC weighting method was used to give the objective weights of each evaluation index, and perform subjective evaluation. The combination was modified to obtain the final combination weight, and the importance of key manufacturing resources was ranked by the TOPSIS comprehensive decision method. Based on the simulation calculation of the automobile assembly line network, the analysis and comparison of the ranking results were performed. The analysis results show that the comprehensive evaluation and comparison method has the comparative advantage of identifying key resources.