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As a novel discrete manufacturing unit, the Matrix Manufacturing System (MMS) is characterized by strong local integration capability and high overall discrete adaptability, rendering it a new production paradigm suitable for small-batch and diversified manufacturing scenarios.However, to fully leverage the advantages of the Matrix Manufacturing System, it is essential to have production scheduling technologies with high response speed and fast time-varying adaptability as support.Based on this, this paper combines Petri Nets with an improved Ant Colony Algorithm (incorporating heuristic function optimization, anticipatory function introduction, and NSGA-II-based multi-objective strategy) to study the scheduling algorithm and application technology for matrix manufacturing units.Results show that integrating Petri Nets with the Ant Colony Algorithm achieves production scheduling for matrix manufacturing systems. Specifically, the improved Ant Colony Algorithm reduces total unit idle time by 58.50 min, decreases average system idle time by 6.50 min, enhances average system utilization rate by 16.89%, and lowers system idle energy consumption by 1.950 kWh.This indicates that the improved ant colony algorithm performs better in optimizing the average processing time and is more effective in enhancing system utilization and reducing system idle energy consumption.

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Research on Production Scheduling Technology for Matrix Manufacturing Systems

  • 会议论文

  • 发表日期：

    2026年

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  • Xianming Gao,
  • Junqi Fan,
  • Hao Zhang,
  • Yinghao Wang,
  • Hanwen Chen

摘要

As a novel discrete manufacturing unit, the Matrix Manufacturing System (MMS) is characterized by strong local integration capability and high overall discrete adaptability, rendering it a new production paradigm suitable for small-batch and diversified manufacturing scenarios.However, to fully leverage the advantages of the Matrix Manufacturing System, it is essential to have production scheduling technologies with high response speed and fast time-varying adaptability as support.Based on this, this paper combines Petri Nets with an improved Ant Colony Algorithm (incorporating heuristic function optimization, anticipatory function introduction, and NSGA-II-based multi-objective strategy) to study the scheduling algorithm and application technology for matrix manufacturing units.Results show that integrating Petri Nets with the Ant Colony Algorithm achieves production scheduling for matrix manufacturing systems. Specifically, the improved Ant Colony Algorithm reduces total unit idle time by 58.50 min, decreases average system idle time by 6.50 min, enhances average system utilization rate by 16.89%, and lowers system idle energy consumption by 1.950 kWh.This indicates that the improved ant colony algorithm performs better in optimizing the average processing time and is more effective in enhancing system utilization and reducing system idle energy consumption.