Research on Computational Experiment of the Service Operation Strategy in Collaborative Manufacturing

As a new type of business pattern, "Cluster Supply Chain" (CSC) can help manufacturers to face the changing market demands through the dynamic matching and composition of all kinds of manufacturing service resources. However, the non-equalization phenomenon is common in the manufacturing s...

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Bibliographic Details
Published in2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom) pp. 436 - 443
Main Authors Xue Xiao, Kou Yan-Min
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2015
Subjects
Cluster Supply Chain
Collaboration
Collaborative manufacturing
computational experiments
Computational modeling
Manufacturing
Quality of service
Service Equalization
services operation strategy
Supply chains
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Summary:As a new type of business pattern, "Cluster Supply Chain" (CSC) can help manufacturers to face the changing market demands through the dynamic matching and composition of all kinds of manufacturing service resources. However, the non-equalization phenomenon is common in the manufacturing service matching, which not only results in the waste of service resources, but also reduces customer satisfaction of needs. In order to achieve the best service equalization performance of collaborative manufacturing, how to select the most appropriate service operation strategy in complex environments has become a serious challenge in the field. To solve this problem, this paper proposes the computational experiment method, which is composed of three parts: the construction of experiment system of collaborative manufacturing, the classification of service operation strategy, and the experiment evaluation of service operation strategy. In the paper, three service strategies (non-equalization strategy, equalization strategy, collaborative equalization strategy) are compared by means of computational experiments. The results show that the collaborative equalization strategy can effectively enhance the service utilization rate and reduce the completion time, which verifies the feasibility of the computational experiment method.
DOI:10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.94