Year: 2025
Type: article
Abstract: This paper addresses the intelligent transformation needs of the traditional injection molding industry by proposing a comprehensive intelligent production decision-making system inte-grating smart scheduling, auxiliary decision-making, and digital twin simulation. By combining the Weighted Shortest Processing Time (WSPT) algorithm, dynamic programming, and equip-ment health assessment, the system achieves dynamic multi-machine scheduling and resource optimization. An injection molding industry-specific large model is constructed, leveraging re-al-time data analysis and a knowledge base to optimize process parameters and enable anomaly early warning. A digital twin platform is developed using Unity and OPC UA protocols, employing multi-physics simulation and Markov decision processes to predict production issues. The re-search provides a practical technical solution for the intelligent upgrading of injection molding factories, offering both theoretical innovation and engineering application value.
Source: 计算机科学辑要
DOI: 10.63313/cs.8012
Authors: Duang Chen, Feng Xu, Youwei Zu, Haoyi Zhao, Shiwei Xu
Institution: Wenzhou Polytechnic
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410213803