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Research for service flow module granularity design based on fuzzy spaces quotient theory

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Abstract

In the research of modular design of service flow, this paper proposes a method to partition the service flow module based on fuzzy spaces quotient theory to reduce the subjectivity of module granularity selection. On the basis of service elements identification, the interrelation among service elements is analyzed in detail. And the further evaluation is made from three aspects such as service flow relevance, service source relevance and service function relevance. By working out similarity matrix between service elements and clustering attributes, the integrated fuzzy similarity matrix is obtained. And the service flow module granularity space is educated by cluster service elements through acquiring hierarchical structure using algorithm. Finally by the grey relational analysis theory and the proper index system, the optimal project of service flow module can be obtained. In this paper, the feasibility of the method above is verified by the maintenance service flow and the module granularity design of the excavator walking mechanism.

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Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (51305417) and the Zhejiang government Science Foundation (16NDJC282YB, 2015Z032).

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  1. Institute of Mechanical Engineering, China Jiliang University, Hangzhou, 310027, China

    Fei Zhang

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  1. Fei Zhang
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Correspondence to Fei Zhang.

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Zhang, F. Research for service flow module granularity design based on fuzzy spaces quotient theory. Cluster Comput 22 (Suppl 3), 5825–5837 (2019). https://doi.org/10.1007/s10586-017-1623-8

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