Evolution Process and Simulation of Advanced Equipment Manufacturing Innovation Network Based on Intelligent System

Area of Science:

• Industrial Economics
• Network Science
• Manufacturing Engineering

Background:

• The shift to advanced equipment manufacturing necessitates understanding industry innovation dynamics.
• Innovation networks are critical for industrial innovation capability, yet understudied in advanced manufacturing.
• Intelligent systems are driving widespread industrial transformation.

Purpose of the Study:

• To investigate the innovation network characteristics in the advanced equipment manufacturing industry.
• To develop and validate an evolution model for this specific innovation network.
• To analyze the network's geometric properties and evolutionary trajectory.

Main Methods:

• Analysis of basic geometric characteristics of the innovation network.
• Development of an evolution model based on the small-world network model.
• Simulation experiments to observe network evolution dynamics.

Main Results:

• The innovation network exhibits distinct evolutionary stages with changing clustering coefficients and average distances.
• The network eventually stabilizes, achieving a clustering coefficient of 0.484 and an average distance of 1.854.
• The degree of small-worldness was calculated as 0.497.

Conclusions:

• The developed simulation model effectively illustrates the evolution process of advanced equipment manufacturing innovation networks.
• The stabilized network structure suggests efficient information flow and collaboration potential.
• Understanding these network dynamics is key to enhancing innovation capability in the sector.