4.7 Article

LMPF: A novel method for bill of standard manufacturing services construction in cloud manufacturing

期刊

JOURNAL OF MANUFACTURING SYSTEMS
卷 62, 期 -, 页码 402-416

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jmsy.2021.12.012

关键词

Cloud manufacturing (CMfg); Bill of standard manufacturing service (BOSS); Maximum spanning tree (MST); Latent relation graph (LRG); Prims algorithm

资金

  1. National Natural Science Foun-dation of China [71571161]
  2. Science Fund for Creative Research Groups of National Natural Science Foundation of China [51821093]

向作者/读者索取更多资源

Cloud manufacturing aims to transform the manufacturing industry into a cloud-based service with efficient service standard expression, publication, collaboration, and sharing being a major challenge. To address this, the authors propose the concept of Bill Of Standard manufacturing Service (BOSS) and a synthesized algorithm called LMPF for quickly building a product-oriented BOSS tree.
Cloud manufacturing (CMfg) intends to transform the manufacturing industry into a cloud-based service -provision commercial mode, which poses a great challenge for efficient service standard expression, publication, collaboration, and sharing. To address this issue, the authors previously proposed the Bill Of Standard manufacturing Service (BOSS) concept, which aimed to construct a tree-type service standard catalog for CMfg. In order to quickly build a product-oriented BOSS tree, a synthesized algorithm, Latent-relation-graph's Maximum-spanning-tree solving by the modified-Prim's with FP-growth algorithm (LMPF) is proposed, in which a latent relation model of services is established and the latent relation graph (LRG) is constructed using the services as nodes and their latent relation strength as edge weights; the BOSS tree can then be constructed with the solution of the maximum spanning tree (MST) problem for the LRG using modified-Prim's with FP-growth algorithm. To verify the performance of the LMPF algorithm, a comprehensive comparative experiment is carried out based on a real dataset collected from e-commerce websites, and the effectiveness of the proposed LMPF algorithm has been proved comparing to the other three typical algorithms.

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