IET Collaborative Intelligent Manufacturing (Mar 2023)

A hybrid model for value‐added process analysis of manufacturing value chains

  • Jingwen Song,
  • Aihui Wang,
  • Ping Liu,
  • Daming Li,
  • Xiaobo Han,
  • Yuhao Yan

DOI
https://doi.org/10.1049/cim2.12071
Journal volume & issue
Vol. 5, no. 1
pp. n/a – n/a

Abstract

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Abstract In the digital era, realising intelligent digital transformation is a major challenge in the manufacturing field. Digital transformation means bringing more profit appreciation. To improve the analysis reliability of value‐added processes, this study proposes a method for assessing enterprises value‐adding activities. For this purpose, a hybrid model is constructed based on data and mathematics, bridged by a server. The research builds an element group model that identifies data from different sources, and also gives a mathematical model to describe the relationship of the supply, marketing and service. Taking an automobile manufacturing value chain as an example, to theoretically analyse the composition of value‐added activities. Then, the assembly process of an automobile manufacturing plant was used as a value‐added case study. The simulation results show the impact of changing production layout and product handling angle on the whole value chain. The study can provide new ideas for the intelligent digital transformation of the manufacturing industry.

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