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Service Composition Optimization Method of Guide Roller in Cloud Manufacturing Environment
Received:August 30, 2024  
DOI：10.11980/j.issn.0254-508X.2025.03.019
Key Words:cloud manufacturing  guide roller  composition optimization  papermaking machinery  improved NSGA-Ⅱ
Fund Project:国家重点研发计划项目（2023YFB3308800）；渭南市重点研发计划项目（2024ZDYFJH-767）。
Author NameAffiliationPostcode
ZHU Langze Faculty of Printing， Packaging Engineering and Digital Media Technology， Xi’an University of Technology， Xi’an， Shaanxi Province， 710048 710048
LIU Shanhui* Faculty of Printing， Packaging Engineering and Digital Media Technology， Xi’an University of Technology， Xi’an， Shaanxi Province， 710048 710048
CAO Yangzhen Faculty of Printing， Packaging Engineering and Digital Media Technology， Xi’an University of Technology， Xi’an， Shaanxi Province， 710048 710048
YANG Hongen Faculty of Printing， Packaging Engineering and Digital Media Technology， Xi’an University of Technology， Xi’an， Shaanxi Province， 710048 710048
WANG Yuanyang Faculty of Printing， Packaging Engineering and Digital Media Technology， Xi’an University of Technology， Xi’an， Shaanxi Province， 710048 710048
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Abstract:To enhance the production efficiency of guide rollers in cloud manufacturing environment， this study proposed a service composition optimization method for guide roller manufacturing based on an improved NSGA-Ⅱ algorithm. First， the composition and production processes of guide rollers were analyzed to identify required manufacturing resource services. An evaluation index system for manufacturing service composition was established based on quality-of-service （QoS） metrics and flexibility indicators. Second， the bi-level programming concept was introduced into the field of manufacturing service composition optimization， and a mathematical model for guide roller manufacturing service composition optimization was formulated. Finally， improvements to the NSGA-Ⅱ algorithm were implemented from two aspects： population initialization and genetic operations， to solve the model. The performance advantages of the proposed method were systematically verified compared with traditional optimization methods by two sets of experiments. The results showed that the proposed method greatly improved the population diversity and convergence speed， and significantly improved the solving efficiency of the service composition optimization problem of guide roller manufacturing.
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