Ding Kai, Zheng Kangqian, Ma Lin, Zhang Fuqiang, Qu Ting, Zhang Haixin. Business Process Modeling and Performance Analysis of Human-Object-Business Coupled Large-scale Manufacturing Value ChainJ. Industrial Engineering Journal. DOI: 10.3969/j.issn.1007-7375.250201
    Citation: Ding Kai, Zheng Kangqian, Ma Lin, Zhang Fuqiang, Qu Ting, Zhang Haixin. Business Process Modeling and Performance Analysis of Human-Object-Business Coupled Large-scale Manufacturing Value ChainJ. Industrial Engineering Journal. DOI: 10.3969/j.issn.1007-7375.250201

    Business Process Modeling and Performance Analysis of Human-Object-Business Coupled Large-scale Manufacturing Value Chain

    • In large-scale manufacturing value chain (LSMVC), typically represented by household appliances, the elements of people, objects, and business processes exhibit deeply coupled and intricately intertwined characteristics. This complexity results in a lack of systematic approaches to business process modeling and performance analysis for the design and optimization of LSMVC, which severely constrains the leading enterprises’ ability to analyze and collaboratively optimize operational performance within the value chain. To address this issue, this study transcends the limitations of traditional single-element modeling and proposes an LSMVC collaborative business process modeling method that accounts for the coupling among human, object, and process factors. A Petri net model is constructed to represent the LSMVC business processes with “human-object-business” coupling. Furthermore, a P-invariant analysis method based on correlation matrix theory and a business node performance analysis method based on Markov chain theory are introduced. Finally, a case study is carried out on a representative LSMVC scenario of a leading home appliance manufacturing enterprise in the Guangdong–Hong Kong–Macao Greater Bay Area. The results demonstrate that extending from single-element to multi-element coupling in the modeling approach provides a multi-dimensional and comprehensive evaluation advantage over traditional methods. Furthermore, integrating both global and local performance analysis significantly enhances the efficiency of identifying and alleviating business process bottlenecks.
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